SEBATIK is a collection of research articles, scientific works, and dedication from all academic community in order to integrate information. SEBATIK provides open publication services for all members of the public, both in all tertiary educational and teacher environments and other research institutions, with the freedom to exchange information that is dedicated to facilitating collaboration between researchers, writers and readers through information exchange. SEBATIK was introduced and developed in the STMIK Widya Cipta Dharma environment since 2001 and is wide open for continuous development. SEBATIK is published periodically twice a year, in June and December, this Journal contains the results of research activities, discoveries and ideas in the field of ICT (Information and Communication Technology) covering the topics of information systems, artificial intelligence, multimedia technology, and others. SEBATIK is also open to topics of research and service outside the field of ICT topics such as topics on public relations, economic improvement, and others. Hopefully with the articles in cultivation researchers can share knowledge in order to advance Indonesia, especially East Kalimantan. ISSN : 1410-3737 E-ISSN : 2621-069X
<div class="per-detail_abstract" style="box-sizing: border-box; font-size: 10px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 200; letter-spacing: normal; orphans: 0; text-indent: 0px; text-transform: none; white-space: normal; widows: 0; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; margin: 0px; padding: 10px; cursor: default; border: 1px solid #e8e3e3; color: #424242; text-align: justify; font-family: 'Microsoft YaHei', Arial, Helvetica, sans-serif; background-color: #ffffff;"> Authors retain all their rights to the published works, such as (but not limited to) the following rights; Copyright and other proprietary rights relating to the article, such as patent rights, The right to use the substance of the article in own future works, including lectures and books, The right to reproduce the article for own purposes, The right to self-archive the article
Sentiment Analysis of Grab Driver Motorbike User Reviews as a Basis for Service Improvement Recommendations
The development of information technology has driven the growth of application-based transportation services, one of which is Grab Motor, which is widely used by the public to meet their daily mobility needs. Service quality is an important factor influencing user satisfaction levels. One source of information that can be utilized to evaluate service quality is user reviews available on digital platforms. This study aims to analyze the sentiment of Grab Motor user reviews as a basis for developing service improvement recommendations. The data used are 200 user reviews obtained from the Google Play Store. The applied method is Lexicon-Based because it is able to identify sentiment polarity without requiring training data. The research stages include data collection, preprocessing consisting of cleansing, case folding, tokenization, normalization, and stopword removal, then continued with the assignment of sentiment scores based on the lexicon dictionary to classify reviews into positive, negative, and neutral categories. The results show that 120 reviews (60%) include positive sentiment, 50 reviews (25%) negative sentiment, and 30 reviews (15%) neutral sentiment. Model evaluation using a confusion matrix yielded an Accuracy of 89%, a Precision of 89%, a Recall of 91%, and an F1-score of 90%. The research findings indicate that the majority of users responded positively to Grab Motor's services, particularly regarding the app's ease of use and speed of service. Meanwhile, negative sentiment was still found regarding fares, pickup delays, order cancellations, and app technical issues. The results of this study are expected to serve as evaluation material and a basis for decision-making in efforts to improve service quality and Grab Motor user satisfaction.
Sentiment Analysis, Grab Motor, Service Quality, Lexicon-Based, User Reviews
Copyright (c) 2026 Mario Benediktus Weruin, Ita Arfyanti, Wahyuni http://creativecommons.org/licenses/by/4.0
The Effect of Compensation and Work Motivation on Teacher Job Satisfaction at Elementary Schools in Kahala Village, Kutai Kartanegara Regency
Teacher job satisfaction is an important factor that influences the quality of learning and the achievement of educational goals. Compensation and work motivation are factors that can affect teachers’ perceptions and attitudes toward their jobs. Appropriate compensation and high work motivation are expected to encourage teachers to perform their duties optimally and enhance their level of job satisfaction. This study aims to analyze the effect of compensation and work motivation on teacher job satisfaction at elementary schools in Kahala Village, Kutai Kartanegara Regency. This study employed a quantitative approach. Data were collected through questionnaires distributed to all 36 teachers using a saturated sampling technique. The data were analyzed using multiple linear regression with the assistance of Statistical Product and Service Solutions (SPSS). The results indicate that compensation does not have a significant effect on teacher job satisfaction. In contrast, work motivation has a positive and significant effect on teacher job satisfaction. Simultaneously, compensation and work motivation have a significant effect on teacher job satisfaction. The findings reveal that teacher job satisfaction is influenced not only by financial rewards but also by motivational factors that enhance enthusiasm, commitment, responsibility, and dedication in carrying out teaching duties. These findings highlight the important role of work motivation in creating a supportive work environment that contributes to improved teacher performance and job satisfaction. Therefore, schools and relevant stakeholders should strengthen teachers’ work motivation through recognition, supportive working conditions, and professional development opportunities to improve job satisfaction and enhance the quality of education.
Compensation, Work Motivation, Job Satisfaction, Elementary Teachers, Basic Education
Copyright (c) 2026 Muhammad Yassir Arafat, Catur Kumala Dewi, Sukirman http://creativecommons.org/licenses/by/4.0
The Effect of Time Management and Self-Leadership on the Work Productivity of Generation Z among Freelance Student Workers at Universitas 17 Agustus 1945 Samarinda
The development of the digital economy has encouraged an increasing number of Generation Z students to engage in freelance work. This condition requires students to balance academic activities and work responsibilities in order to maintain productivity. The work productivity of freelance student workers is influenced by various factors, including time management and self-leadership. This study aims to analyze the effect of time management and self-leadership on the work productivity of Generation Z freelance student workers at Universitas 17 Agustus 1945 Samarinda. This research employed a quantitative approach using primary data collected through questionnaires and interviews. The population consisted of 1,484 students from the 2022 and 2023 cohorts, with a sample of 94 respondents selected through a purposive sampling technique. Data were analyzed using multiple linear regression with the assistance of Statistical Product and Service Solutions (SPSS). The results indicate that time management and self-leadership partially have a positive and significant effect on work productivity. Simultaneously, both variables also have a positive and significant effect on the work productivity of freelance student workers at Universitas 17 Agustus 1945 Samarinda. These findings suggest that the ability to manage time and lead oneself plays an important role in improving work productivity and supporting a balance between academic and work activities, enabling students to achieve work targets effectively and efficiently without neglecting their academic responsibilities.
Time Management, Self-Leadership, Work Productivity, Generation Z, Freelance Workers
Copyright (c) 2026 Aulia Asyifa, Catur Kumala Dewi, Sukirman http://creativecommons.org/licenses/by/4.0
Android-Based Ramli Waste Bank Application in Samarinda City
Household and plastic waste remain major challenges in environmental management in Indonesia, including in Samarinda City. One of the efforts to reduce waste volume while providing economic benefits to the community is through the RAMLI Sidodadi Waste Bank. However, data management and transaction recording at the waste bank are still carried out manually using passbooks, which may lead to recording errors, data loss, and inefficient customer services. Therefore, a technology-based solution is needed to improve the effectiveness and transparency of waste bank management. This study aims to develop an Android-based RAMLI Waste Bank application for Samarinda City that can facilitate data management and information access for both customers and administrators. The research employed a descriptive approach, with data collection techniques including literature studies, interviews, and observations. The system was developed using the Waterfall method, which consists of requirements analysis, system design, implementation, testing, and maintenance stages. The application was built using the Flutter framework, Dart programming language, and Firebase Realtime Database as the data storage platform. The application provides several features, including user login and registration, waste type information, waste bank location services, waste management educational content, point balance checking, transaction history, and user profile management. The development results indicate that the application improves transaction recording efficiency, facilitates real-time access to information, enhances data transparency, and reduces the risk of data loss. Therefore, the Android-based RAMLI Waste Bank application can serve as a digital solution that supports sustainable waste management while increasing community participation in environmental conservation and generating economic benefits through waste management activities.
Waste Bank, Waste Management, Android, Flutter, Firebase
Copyright (c) 2026 Jainal Rahman, Muhammad Fahmi, Rizky Zakariyya Rasyad http://creativecommons.org/licenses/by/4.0
Effectiveness Analysis of DHCP Snooping and Port Security Against DHCP Starvation Attacks on Cisco-based VLAN Networks
Traditional Dynamic Host Configuration Protocol (DHCP) protocols implemented on Virtual Local Area Network (VLAN) networks are highly vulnerable to DHCP Starvation attacks due to the absence of device authentication mechanisms. This research aims to comparatively analyze the effectiveness level of DHCP Snooping and Port Security features on Cisco switches in maintaining the availability of IP Address allocation services. The research method was conducted experimentally through a multi-tiered network infrastructure simulation using Cisco Packet Tracer simulator. The testing evaluated two main scenarios: operational conditions without security and conditions with an active protection system. The measured testing parameters included the IP request packet rate (configured at a DHCP Snooping Limit Rate of 2 packets per second), the maximum number of MAC Addresses per physical port (configured for 1 address via Port Security), and the network disruption response time. The testing results indicated that in the unsecured scenario, the attack successfully exhausted 100% of the address pool allocation (254 IP Addresses) within 3 to 5 seconds, causing total service downtime for all legitimate users. Conversely, when the active protection system with a shutdown violation parameter was applied, the switch instantly isolated the attacker's physical port into an err-disable status in less than 1 second after detecting a violation. The research conclusion proves that the combination of these two features has a 100% effectiveness rate in maintaining addressing stability and protecting the integrity of VLAN network infrastructure from disruption.
DHCP Starvation, DHCP Snooping, Port Security, VLAN, Cisco Packet Tracer.
Copyright (c) 2026 Rendy Adi Tama, Muhammad Fahmi, Ahmad Fahrijal Pukeng http://creativecommons.org/licenses/by/4.0
Evaluation of Konselopoly Quest as Educational Media in Riverside Schools Through the CIPP Model
This study purpose to evaluate the implementation of Konselopoly Quest as an educational medium in riverside schools using the Context, Input, Process, and Product (CIPP) evaluation model. A qualitative approach was employed involving students from SMA Negeri 12 Banjarmasin selected through purposive sampling. Data were collected through in-depth interviews, observations, and documentation and analyzed using the Miles and Huberman interactive model, which includes data reduction, data display, and conclusion drawing. The findings indicate that, in the context dimension, the game successfully created a more engaging and interactive learning environment, although the content was not fully aligned with students’ academic needs. In the input dimension, the visual design and overall appearance were perceived positively, while the use of foreign terms and game mechanics required further simplification. In the process dimension, the game enhanced students’ social interaction, teamwork, participation, and critical thinking skills, despite uneven levels of involvement influenced by group dynamics. In the product dimension, the game contributed positively to students’ understanding of Pancasila Student Profile values, social skills, and self-confidence. However, its impact on long-term learning motivation and comprehensive understanding of wetland environments remained limited. Overall, Konselopoly Quest was found to be a reasonably effective educational medium that promotes active, communicative, and enjoyable learning experiences, although improvements are still needed in terms of content, language, game mechanics, and implementation strategies.
Konselopoly Quest, educational media, CIPP evaluation, Wetlands
Copyright (c) 2026 Muhammad Syauqie Rizaldin, Hendro Yulius Suryo Putro, Muhammad Arsyad http://creativecommons.org/licenses/by/4.0
Analysis Of The Effectiveness Of Using Tiktok Social Media As A Promotional Medium Using The EPIC Model At Alesha Shop Bara
Social media promotional activities currently play a truly crucial role in significantly increasing brand awareness and public interest in Alesha Shop Bara. For this precise reason, conducting a comprehensive analysis of the effectiveness of utilizing this digital media is highly necessary for management to design and develop more optimal sales strategies in the future. In conducting this evaluation process, a highly applicable instrument or method is the EPIC Model, which was initially developed by the global market research firm, AC Nielsen. This particular evaluation model is specifically designed to comprehensively measure promotional effectiveness based on four main dimensions, which consist of empathy, persuasion, impact, and communication. To test and determine definitely whether the specific marketing strategy executed through the TikTok platform by Alesha Shop Bara has been completely effective, an objective measurement of the shop's TikTok performance itself is required. Based on the final results of the data analysis, it can be concluded that Alesha Shop Bara's TikTok is proven to be a highly effective promotional medium. This positive result is strongly evident from the excellent scores achieved in the empathy, persuasion, impact, and communication dimensions. Overall, the average score of the EPIC rate obtained is 4.42, with the empathy dimension successfully achieving the highest score compared to the other dimensions, reaching 4.49.
Analysis, TikTok Advertising Effectiveness, EPIC Model, Alesha Shop Bara, SPSS
Copyright (c) 2026 Ammar Ibnu Arif, Ita Arfyanti, Bartolomius Harpad http://creativecommons.org/licenses/by/4.0
Design Of a Public Reporting Application For Traffic Violations: A Case Study Of The Samarinda City Transportation Department
This study aims to design a public reporting application for Traffic violations to assist the Samarinda City Transportation Department in improving the effectiveness of Traffic monitoring and law enforcement. The current problem lies in the reporting process, which is still conducted manually, resulting in delays in handling reports and limiting public participation in reporting Traffic violations. This study employed the Waterfall system development method, consisting of Requirement analysis, system design, implementation, testing, and maintenance stages. Research data were collected through observation, literature review, and field studies at the Samarinda City Transportation Department to comprehensively identify system Requirements. The results indicate that the implementation of the public reporting application for Traffic violations significantly increases the number of public reports, accelerates the response time for handling violations, and improves transparency and accountability in report management. The designed application also facilitates the public in submitting reports in real time through location data and violation documentation uploads. Furthermore, the application is expected to become an innovative solution in supporting Traffic law enforcement and improving the quality of public services in the transportation sector in Samarinda City. The system was developed using PHP (Hypertext Preprocessor) as the programming language and MySQL (My Structured Query Language) as the database management system managed through PhpMyAdmin. The system is also designed to provide easier access, improve report management efficiency, and support more responsive and sustainable Traffic monitoring.
Traffic Violation, Public Reporting, Waterfall Method, Transportation Agency, Web System
Copyright (c) 2026 Yusva Awabil Chair, Muhammad Fahmi, Azahari http://creativecommons.org/licenses/by/4.0
Ethical Violations and Their Effects on Public Accounting Firms:A Case Study of KAP XYZ
Ethical violations by external auditors may reduce audit quality and create risks of inappropriate audit opinions, particularly when audited financial statements are used by external parties such as creditors. This study was to analyze the process, causes, and effects of ethical violations in an anonymized audit engagement at KAP XYZ involving Bank X. The study used a qualitative retrospective case study approach. Data were collected through semi-structured interviews with two actual informants, namely a partner familiar with the accountability process and a junior auditor who participated in fieldwork, supported by document review, member checking, and source triangulation. The data were analyzed thematically by comparing interview codes with the Indonesian Public Accountant Professional Code of Ethics and relevant Standards on Auditing. The findings indicate violations of professional competence and due care in audit planning, fieldwork, and reporting. Inventory and receivables testing relied excessively on analytical procedures without sufficient alternative procedures. Time pressure, weak supervision, and limited audit evidence contributed to an inappropriate unmodified opinion. The case resulted in contract termination by Bank X, reputational damage, and restrictions on the responsible auditors.
Audit Evidence, Audit Opinion, Audit Quality, Ethical Violation, External Auditor, Time Pressure
Copyright (c) 2026 Deli Yansyah, Khairunnisa Rahmah, Agung Prabowo http://creativecommons.org/licenses/by/4.0
Analysis of Food Security Index in East Kalimantan Using Panel Regression and K-Means Clustering
This study aims to identify indicators that significantly influence the Food Security Index (IKP) of districts/cities in East Kalimantan Province and to group regions based on their food security characteristics. Food security is a crucial issue because it relates to the availability, accessibility, and utilization of food, which are influenced by socioeconomic conditions, education, health, and basic infrastructure. Differences in characteristics between regions in East Kalimantan encourage the need for analysis that can explain the influence of variables both spatially and temporally. The methods used in this study are panel data regression and K-Means Clustering. Panel data regression is applied to analyze variables that significantly influence the IKP, while the selection of the best model is carried out through the Chow Test, Hausman Test, and Lagrange Multiplier Test. Furthermore, the K-Means Clustering method is used to group districts/cities based on food security indicators. The results show that the best model is the Common Effect Model (CEM) with a coefficient of determination of 91.7%. Variables proven to significantly influence the IKP include rice production, poverty rate, per capita expenditure, electricity access, average length of schooling, life expectancy, and access to safe drinking water. Furthermore, the results of the K-Means Clustering analysis yielded three regional groups with distinct food security characteristics, which can serve as a basis for formulating more targeted food security policies in East Kalimantan.
Clustering, Food Security Index, East Kalimantan, Panel Regression
Copyright (c) 2026 Diana Nurlaily, Nabila Putri Bareng, Milka Yosep, Revalina Putria Hidayat http://creativecommons.org/licenses/by/4.0
IoT-Based Household Electricity Usage Monitoring System Using Android
In daily life, uncontrolled electricity consumption can lead to the waste of electronic devices in households. Therefore, a system that is able to accurately monitor electricity use is needed. This study aims to find out how much electrical energy is used in households based on the Internet of Things (IoT) that can be accessed through android devices. The method used in this study is the prototype method. The system is built using a ESP8266 NodeMCU microcontroller connected to the internet network and a PZEM-004T sensor to measure the voltage, current, power, and electrical energy used. The result of this research is in the form of a monitoring tool that is able to display the use of electrical energy directly and can be monitored from anywhere through an android device. This system is expected to help the community in controlling electricity use to be more efficient.
Internet of Things (IoT), Monitoring Electrical Energy, Android, NodeMCU
Copyright (c) 2026 Yusuffi, Muhammad Fahmi, Ivan Haristyawan http://creativecommons.org/licenses/by/4.0
Analysis of Consumer Satisfaction Levels at Sakura Fashion Store Using the SERVQUAL Method
This research is motivated by the importance of understanding the level of customer satisfaction in the increasingly competitive retail fashion industry, particularly at Sakura Fashion Store. Customer satisfaction is a crucial factor in maintaining customer loyalty and enhancing business competitiveness. This study aims to analyze the level of customer satisfaction with service quality using the SERVQUAL method, which encompasses five dimensions: tangibles, reliability, responsiveness, assurance, and empathy. The research method used is a descriptive quantitative approach with data collection techniques through distributing questionnaires to 42 respondents who are consumers of Sakura Fashion Store. The data obtained were analyzed to determine the match between consumer expectations and perceptions of the services provided. The results showed that the overall level of customer satisfaction was in the category of quite satisfied to satisfied. The tangibles dimension received the highest score, while the reliability and responsiveness dimensions still require improvement. This study concludes that service quality has a significant influence on customer satisfaction. Therefore, Sakura Fashion Store is advised to improve service speed, product quality consistency, and employee ability to respond to consumer needs more effectively
Consumer Satisfaction; SERVQUAL Method; Fashion Store; SERVQUAL Analysis
Copyright (c) 2026 Laramitha, Pajar Pahrudin, Bartolomius Harpad http://creativecommons.org/licenses/by/4.0
Development of an Initial Risk Identification and Risk Validation Framework to Support Sustainable Geo-Ecotourism Infrastructure in Osing Kemiren Village
This study aims to identify, validate, and develop risk mitigation strategies for geo eco tourism infrastructure in Osing Kemiren Tourism Village, Banyuwangi Regency. The research methods include risk identification through field observations and recent literature review, risk classification based on environmental, socio-cultural, and operational categories, and risk validation through focused group discussions (FGDs) involving local communities and stakeholders. The results indicate that the main risks involve environmental degradation, socio-cultural changes, and operational constraints in tourism infrastructure. Based on the validation process, high-priority risks are addressed through mitigation strategies, including waste management, preservation of Osing cultural heritage, maintenance of tourist pathways, and active community participation in site management. The implementation of these strategies is expected to support the development of safe, environmentally friendly, and sustainable infrastructure, while enhancing local community engagement. This study provides a scientific basis for tourism managers and policymakers to design sustainable geo eco tourism development that aligns with local wisdom and community values
Geo Eco Tourism, Sustainable Infrastructure, Risk Mitigation, Osing Kemiren
Copyright (c) 2026 Fikca Ayuk Safitri, Yuni Ulfiyati, Enes Ariyanto Sandi http://creativecommons.org/licenses/by/4.0
Gandrung Sewu Festival as a Sustainable Tourism Attraction in Banyuwangi, East Java
Gandrung Sewu Festival has enriched the Banyuwangi Festival series and is recognized as part of the Karisma Event Nusantara (KEN). First held in 2012, this cultural event offers more than a traditional performance; it provides educational value for tourists through a unique and modern presentation. The festival also generates positive impacts on the local community, particularly through the active participation of Banyuwangi’s younger generation in its implementation. However, several aspects still require evaluation, both internally and externally. This study aims to formulate strategies to sustain the existence of the Gandrung Sewu Festival as a sustainable tourism attraction in Banyuwangi, East Java. The research applies a quantitative descriptive method using the Internal-External (IE) Matrix as the analytical tool. The results show that the festival’s strengths include the Gandrung dance as its core identity, strong community participation, creative annual themes, and the growth of Banyuwangi’s tourism sector. The main internal strength is its strategic location, while the key weakness is the inconsistent scheduling of the event. Externally, the greatest opportunity lies in tourism sector development, while the main threat comes from natural disasters and weather conditions. This study proposes three strategic recommendations to strengthen the festival’s sustainability. The findings are expected to serve as a reference for developing event-based sustainable tourism attractions in Indonesia.
festival, gandrung sewu, sustainable tourism attraction, Banyuwangi
Copyright (c) 2026 Kanom http://creativecommons.org/licenses/by/4.0
Prediction of the Number of New Students Using the Arima Time Series Model Case Study at Stmik Widya Cipta Dharma
Planning for new student admissions is an important aspect in university management because it is closely related to strategic decision-making and institutional resource allocation. This study aims to estimate the number of new students in the Informatics and Information Systems Engineering Study Program at STMIK Widya Cipta Dharma using the Autoregressive Integrated Moving Average (ARIMA) method. The data used is secondary data obtained from PDDIKTI with a period of 2015-2025. The analysis process was carried out through several stages, namely stationary testing using the Augmented Dickey-Fuller (ADF) method, model identification through Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF), parameter estimation, diagnostic tests, and forecasting processes. The results showed that the best model obtained was ARIMA (0,1,0) after first-order differentiation. The model produces residual that meets the assumption of white noise and is normally distributed. The forecast results show a tendency to decrease the number of new students in the 2026–2028 period. The model evaluation showed a very good level of accuracy in the Informatics Engineering Study Program with a Mean Absolute Percentage Error (MAPE) value of 9.64% and quite good in the Information Systems Study Program of 24.88%. Thus, the ARIMA model (0,1,0) is considered effective in supporting the planning of new student admissions in a more measurable and systematic manner.
ARIMA, Time Series, Forecasting, Freshmen, EViews
Copyright (c) 2026 Eko Jheremy Oktavianus, Pitrasacha Adytia, Muhammad Ibnu Sa’ad http://creativecommons.org/licenses/by/4.0
Cigarette Sales Forecasting at Bali Jaya Store Using the Single Method Exponential Smoothing
This study aims to forecast cigarette sales at Toko Bali Jaya using the Single Exponential Smoothing method as a quantitative approach to support more effective inventory management. The problems faced are the unstructured sales recording process and the manual determination of stock levels, which leads to inaccuracy in inventory control and potentially leads to overstocking or understocking. The Single Exponential Smoothing method was chosen because it is known to be effective in forecasting time series with fluctuating data patterns and no significant trends. The data used are cigarette sales data for 12 months which are processed to produce forecast values for the following period. The accuracy evaluation process is carried out using the Mean Absolute Percentage Error (MAPE) as an indicator of the level of forecast error. The results show that the best smoothing constant value is obtained at α = 0.3 with a MAPE value of 5.93%. This value indicates a low error rate, so the method used is able to produce forecasts that are close to the actual data. Thus, this method can be used as a basis for decision-making related to cigarette inventory management in a more systematic and measurable manner.
Forecasting, Cigarette Sales, Single Exponential Smoothing, MAPE
Copyright (c) 2026 I Ketut Andri Purna Wijaya, Andi Yusika Rangan, Muhammad Ibnu Saad http://creativecommons.org/licenses/by/4.0
Recruitment of Civil Servants Following The State of Emergency at The Sawang Subdisdrict Office, North Aceh Regency
This study aims to determine the recruitment process of civil servants and its impact on professionalism and transparency at the Sawang Sub-District Office in North Aceh Regency. The method used in this study is descriptive qualitative, with data collection techniques including interviews, observation, and documentation. The data obtained was then analyzed through data reduction, data presentation, and data verification. The results of the study show that the recruitment of civil servants after the military emergency at the Sawang Subdistrict Office was simple, quick, and tended to be closed because it was more influenced by the need to maintain socio-political stability, reconciliation, and the continuity of government in a post-conflict situation than by the strict application of merit principles, so that the process did not involve open selection or competency tests. This situation has impacted the professionalism of the State Civil Apparatus, which is not yet optimal, as well as low levels of transparency, because the recruitment process is based more on social and situational considerations during the transition period. When compared to the principle of meritocracy, this recruitment practice is not entirely appropriate because it does not place qualifications, competence, potential, performance, and integrity as the main criteria, even though it can be understood as an adaptive policy by local governments to maintain peace and ensure that public services continue to run.
Recruitment, Civil Servants, Post-Martial Law
Copyright (c) 2026 Ruwaida, Aiyub, Muryali, Cut Sukmawati, Ferizaldi http://creativecommons.org/licenses/by/4.0
Recommendation System for College Major Selection Based on Academic Analysis and Student Interests at SMAN 5 Berau Using Naïve Bayes
Choosing a college major is one of the most critical decisions faced by high school students before graduation, as it significantly influences their academic path and future career. However, many students experience difficulties in selecting a major that aligns with their academic abilities and personal interests, which often leads to mismatches during their university studies. This research aims to design and implement a recommendation system for college majors tailored to students of SMAN 5 Berau by applying the Naïve Bayes algorithm. The dataset used in this study consists of students’ academic records and interest survey results, which are processed to generate appropriate recommendations. The Naïve Bayes method is chosen due to its simplicity, efficiency, and effectiveness in handling probabilistic classification problems. The system is developed to provide objective and data-driven recommendations by integrating both academic performance and student interests. Based on the analysis, the system is able to produce relevant recommendations that assist students in making more informed and accurate decisions regarding their future majors. Furthermore, this system also supports guidance counselors in providing appropriate academic advice. Therefore, the implementation of this recommendation system is expected to improve decision-making quality and reduce the risk of mismatched major selection among students.
Recommendation System, College Major, Academic Data, Student Interests, Naïve Bayes
Copyright (c) 2026 Abil Firnanda, Salmon, Kusnandar http://creativecommons.org/licenses/by/4.0
The Effect of Effectiveness, Accessibility, and Ease of Service of Digitalized Sharia Banking Services from BSI Mobile to BYOND by BSI on CustomerSatisfaction at The Gandapura Branch Office
This study aims to determine how the effectiveness, accessibility, and ease of service affect customer satisfaction with the BYOND by BSI application at BSI KCP Gandapura. This study was motivated by the author's observation that the usage rate of the BYOND by BSI application among KCP Gandapura customers is still low, as reflected in the perception that BYOND is not yet able to provide a better service experience than BSI Mobile. Customers are also reluctant to switch because the BYOND application is considered ineffective, often experiences technical problems, is difficult to access at certain times, and has a display and features that are not yet fully user-friendly. This study used a quantitative method, where the data source used was primary data obtained by distributing questionnaires to Gandapura KCP customers who were BYOND by BSI users. The data analysis technique used was multiple linear regression analysis using SPSS software. The results showed that the effectiveness, accessibility, and ease of service partially had a positive and significant effect on customer satisfaction with the BYOND by BSI application at KCP Gandapura. Then, the simultaneous test results showed that effectiveness, accessibility, and ease of service also had a significant effect on customer satisfaction with the BYOND by BSI application at KCP Gandapura.
Effectiveness, Accessibility, Ease Service, Customer Satisfaction, BYOND
Copyright (c) 2026 Wardiyati, Maryam, Cut Sukmawati, Ferizaldi, Teuku Zulkarnaen http://creativecommons.org/licenses/by/4.0
Optimizing IT Service Performance Through COBIT 2019-Based Governance Design at Keling Kumang Institute of Technology
The Keling Kumang Institute of Technology (ITKK) is a new university in Sekadau Regency, West Kalimantan, which faces challenges in IT management to support academic and managerial operations, including delays in IS and IT infrastructure maintenance, power and internet disruptions, a lack of competent IT human resources , and limited budget and network infrastructure. The complexity of IT services such as SIAKAD, Server and Network Systems, and OJS, requires the implementation of structured IT governance so that IT services run optimally and in line with the institution's vision and mission . This study aims to find weaknesses in IT governance through an analysis of current IT capabilities (as-is) and expected conditions (to-be), as well as to develop recommendations to achieve good governance levels. This study was conducted using the COBIT 2019 framework with 4 process objective domains that have been identified through consultation with ITKK stakeholders and stakeholders, namely APO04, APO07, DSS05, and BAI06. Based on the gap analysis, APO04 has evidence work of product at the Largely Achieved level (50-84%), APO07 has significant challenges in IT HR management with a Not Achieved value (0-49%) at Level 1, DSS05 shows weaknesses in network and endpoint security aspects with a Partially Achieved value (15-49%) at Level 2, and BAI06 requires substantial improvements in IT change management with a Partially Achieved value (15-49%) at all levels. The recommendations provided include the preparation of IT governance policies that are integrated with the ITKK Strategic Plan and VMTS, improving IT HR competency through training and certification, strengthening network security infrastructure, and implementing documented IT change management procedures
COBIT 2019, IT Governance, IT Infrastructure, Capability Level, Gap Analysis
Copyright (c) 2026 Angela AL, Alva Hendi Muhammadi http://creativecommons.org/licenses/by/4.0
Classification of Avocado Ripeness Levels Using Transfer Learning Based on VGG16 and VGG19
The determination of avocado ripeness is still commonly performed manually, which is subjective and often inaccurate due to its reliance on human visual perception. Traditional methods, such as pressing the fruit surface, may damage avocado quality and are inefficient for large-scale distribution and marketing. This study aims to automatically classify avocado ripeness levels using a deep learning approach based on transfer learning. The proposed method employs transfer learning using Convolutional Neural Network architectures, namely VGG16 and VGG19, which have been pre-trained on the ImageNet dataset. The research stages include image pre-processing such as resizing, normalization, and data augmentation to enhance input quality. Subsequently, model training and testing are conducted by comparing the performance of both architectures using evaluation metrics. The dataset used in this study is obtained from the Kaggle platform and consists of avocado images with various ripeness levels. Experimental results indicate that both models are capable of classifying avocado ripeness with high accuracy, precision, recall, and F1-score, with the VGG19 model achieving the best performance. These findings demonstrate that the deep learning approach effectively addresses the subjectivity and inaccuracy associated with manual avocado ripeness determination. This study contributes to the development of an accurate, objective, and practical image-based avocado ripeness classification system with potential applications in agriculture and fruit distribution
Avocado Ripeness, Deep Learning, Transfer Learning, CNN, VGG
Copyright (c) 2026 Ibnu Luthfi, Yuhandri Yuhandri, Gunadi Widi Nurcahyo http://creativecommons.org/licenses/by/4.0
Sentiment Analysis of Public Comments on YouTube Content Using Principal Component Analysis and Naive Bayes
The rapid acceleration of digital media development compels public broadcasting institutions to adapt to shifting public information consumption patterns, which are now centered on online platforms. TVRI Sumatera Barat has responded to these dynamics by leveraging YouTube as a channel for content distribution and audience engagement. However, this interaction generates a massive volume of unstructured comment text, rendering manual sentiment analysis inefficient, time-consuming, and prone to subjectivity. This study aims to address these challenges by automatically and objectively classifying user sentiment using a machine learning approach. The applied methodology integrates Principal Component Analysis (PCA) and the Gaussian Naive Bayes algorithm. PCA serves as a dimensionality reduction technique to simplify TF-IDF weighted text features without losing vital information, while Gaussian Naive Bayes was selected for classification due to its efficiency in rapidly processing the continuous numerical data resulting from the PCA transformation. The research dataset comprises 10 comments from the TVRI Sumatera Barat YouTube channel in 2024, collected via the YouTube Data API, which underwent preprocessing and labeling for positive and negative sentiments. Model validation was conducted using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The test results demonstrate that the combination of PCA and Gaussian Naive Bayes effectively enhances computational efficiency and delivers precise classification performance. This research makes a significant contribution by providing a measurable method for public opinion analysis, which is essential as a basis for evaluating audience perception to improve the quality of digital broadcasting strategies in public institutions.
Sentiment Analysis, YouTube, TVRI, TF-IDF, Principal Component Analysis, Gaussian Naive Bayes
Copyright (c) 2026 Dede Pratama, Sumijan, Rini Sovia http://creativecommons.org/licenses/by/4.0
Model Interpretation for Student Major Selection Using Principal Component Analysis and Random Forest
The development of information technology has had a significant impact on the education sector by providing data-driven tools to support the process of major selection. This process often causes confusion among students due to its crucial role in determining their academic and career futures. This study aims to develop an accurate and transparent recommendation system for major selection through the integration of Principal Component Analysis (PCA), Random Forest (RF), and SHAP. The research follows a systematic framework that includes data processing and model evaluation stages. PCA is applied to reduce the dimensionality of complex student data in order to improve computational efficiency and minimize information redundancy. Furthermore, the Random Forest algorithm is employed as a classification model to predict major recommendations such as Science, Social Sciences, and Religious Studies. The SHAP method is integrated to provide both mathematical and visual interpretations of the contribution of each academic feature to the model’s prediction results. The research data are obtained from the internal records of MAN 1 Payakumbuh covering the last three academic years (2022/2023–2024/2025). The dataset consists of 571 eleventh-grade students with tenth-grade academic scores and non-academic skill variables. The implementation of this model is able to provide more objective recommendations compared to conventional subjective assessments, achieving an accuracy of 88.70%. Visualization of feature contributions using SHAP enhances transparency and facilitates stakeholders’ understanding of the basis for each model decision. This study contributes to improving the efficiency of the major selection process and supports more accurate academic decision-making for students and educators.
Major Selection, PCA, Random Forest, Recommendation, SHAP
Copyright (c) 2026 Antoni, Sarjon Defit, Yuhandri http://creativecommons.org/licenses/by/4.0
Intelligent System for Diagnosing Infectious Diseases in Children Using the Certainty Factor and Naive Bayes Methods Based on Android
Infectious diseases in children remain a serious health problem due to their high vulnerability resulting from an immune system that is not yet fully developed. Limited access to medical personnel and delays in early detection often result in ineffective treatment. Therefore, this study aims to design and implement an Android-based intelligent system application capable of detecting infectious diseases in children early on by utilizing the Certainty Factor and Naïve Bayes methods. This system is designed as an expert system that mimics the way pediatricians analyze symptoms and determine preliminary diagnoses. The research methods used include collecting disease and symptom data based on the knowledge of pediatric health experts, data analysis, rule base formation, and the design and implementation of an Android-based system. The Certainty Factor method is used to handle the uncertainty of the level of confidence in the symptoms selected by the user, while the Naïve Bayes method is used to calculate the probability of disease based on historical data. The combination of these two methods aims to improve the accuracy and reliability of diagnostic results. The results of the study show that the developed expert system application is capable of providing initial diagnostic information on infectious diseases in children quickly and easily accessible to parents and health workers. This system is expected to be an effective early detection tool, support initial medical decision-making, and contribute to the development of artificial intelligence-based health technology in Indonesia.
Health Expert System, Early Detection of Childhood Diseases, Certainty Factor, Naïve Bayes, Android
Copyright (c) 2026 Ahmad Khomsi, Syafri Arlis, Sumijan http://creativecommons.org/licenses/by/4.0
Teacher Performance Evaluation Analysis Using K-Means Clustering Algorithm and Random Forest Classification
Teacher performance assessment is a primary parameter in determining the quality of educational institutions. Evaluation systems in many elementary schools still rely on descriptive qualitative approaches. Abundant school administrative data often remain as unprocessed archival records without further analytical utilization. This condition results in school management decision-making that lacks a strong empirical foundation. This study applies data mining technology to transform administrative data into strategic information. The research focuses on SD Negeri 12 Padang Besi and involves all active teaching staff during the current academic year. The research dataset is entirely derived from internal school records. This study excludes the use of questionnaire instruments, and in-depth interview methods are not employed in the data collection process. The analysis is strictly limited to administrative aspects, without including assessments of in-class pedagogical competence. The technical implementation utilizes the K-Means Clustering algorithm to automatically identify patterns in teacher performance grouping. This process is followed by the application of the Random Forest algorithm to measure classification accuracy based on the available administrative features. The combination of these methods produces a performance mapping that is free from human subjectivity. The analytical results provide clear performance labels for each individual teacher. This study contributes to the development of a data-driven digital evaluation model. School management can use the outputs of this research as a basis for reward allocation or targeted professional development programs. This approach ensures transparency in human resource governance within the educational environment.
Teacher Performance, Data Mining, K-Means Clustering, Random Forest, School Administrative Data, Educational Evaluation
Copyright (c) 2026 Dito Jurinaldo, Musli Yanto, Syafri Arlis http://creativecommons.org/licenses/by/4.0
An Analysis of Public Satisfaction with Government Services: A Multi-Method Approach Using PCA, K-Means Clustering, and Linear Regression
Flawless performance evaluation results across all service dimensions may potentially obscure the identification of areas for improvement and diminish objectivity in decision-making. This study aims to identify the specific service attributes influencing public satisfaction and to segment respondents based on their satisfaction levels at the Office of the Ministry of Religious Affairs in Payakumbuh City. The research integrates Principal Component Analysis (PCA), K-means clustering, and linear regression. PCA was employed to reduce data dimensionality and establish principal components; K-means clustering was utilized to group respondents based on perceptual similarities regarding service quality; and linear regression was applied to identify the most significant factors influencing public satisfaction within each segment. The data were sourced from the Public Service Survey Information System (SISULAP) application of the Payakumbuh Ministry of Religious Affairs, spanning June 2024 to October 2025, with a total of 1,950 respondents. The findings reveal that service process and efficiency are the primary factors influencing all respondent segments, with the low-satisfaction segment identified as the top priority for service improvement. The regression models demonstrate robust performance across all segments. These findings provide an empirical foundation for data-driven policymaking to enhance public service quality.
Public Satisfaction, PCA, K-means Clustering, Linear Regression, CSI, Service Quality
Copyright (c) 2026 Abuzar Gafari, Sarjon Defit, Rini Sovia http://creativecommons.org/licenses/by/4.0
Deep Learning Analysis for Predicting the Approval Time of Clinical Practice Guidelines (CPG) Based on Historical Administrative Data
This study aims to predict the processing time of the approval of Clinical Practice Guidelines (CPG), which exhibits considerable variation in duration and is difficult to predict accurately. In addition, the utilization of historical hospital administrative data to build effective predictive models for estimating the duration of the CPG approval process has not yet been optimized. Therefore, this research seeks to develop a predictive model to estimate the processing time of the CPG approval process.The proposed approach employs deep learning techniques by leveraging historical administrative data as the basis for modeling. The methods applied include K-Means Clustering, Decision Tree, and Long Short-Term Memory (LSTM). K-Means Clustering is used to group CPG data based on similar administrative characteristics, enabling the identification of approval time patterns. Subsequently, the Decision Tree method is utilized to analyze the relationships among variables and to generate classification rules that explain the factors influencing the duration of the CPG approval process. Meanwhile, LSTM serves as the primary model for predicting the processing time of CPG approval.This study uses 487 CPG records collected over the period from 2020 to 2024. The evaluation results indicate that the K-Means Clustering method achieves an accuracy rate of 87,36%. This level of accuracy reflects strong clustering performance and a high degree of conformity with actual conditions, indicating that the results are suitable to be used as a foundation for further analysis in the classification and prediction stages of the CPG approval process.
LSTM, K-Means, Decission Tree, CPG, Time Prediction
Copyright (c) 2026 Yuliana Pertiwi, Musli Yanto, Billy Hendrik http://creativecommons.org/licenses/by/4.0
Implementation of the Design Thinking Method in the Design of Mobile-Based MSME Applications (Case Study of MSME Mooara Space in Muara Badak District)
This study aims to design a mobile-based application for Micro, Small, and Medium Enterprises (MSMEs) to support digital transformation and improve service efficiency. Mooara Space MSME in Muara Badak District currently experiences limitations in managing services and delivering product information due to the absence of an integrated digital system. This condition leads to inefficiencies in operations and limited accessibility for customers. To address this issue, this research applies the Design Thinking approach, which emphasizes User-centered problem solving based on real needs and experiences. The research process consists of five main stages: empathize, define, ideate, prototype, and test. Data collection was conducted through direct observation and interviews with business owners and customers to identify key challenges and expectations. The findings were then translated into system requirements and solution concepts, which were implemented into a mobile application prototype. The developed application includes features such as product catalog, order management, payment processing, and order tracking. The evaluation results indicate that the proposed solution is able to meet User needs and improve interaction efficiency between customers and the business. Therefore, the application design is expected to enhance service quality, increase customer engagement, and support sustainable digital adoption for MSMEs.
Design Thinking, Mobile application, MSMEs, User Experience, System Design
Copyright (c) 2026 Muhammad Risqi Zharfan, Azahari, Ahmad Abdul Khair http://creativecommons.org/licenses/by/4.0
COBIT as a Framework for Evaluating Strategic Business IT Alignment:Systematic Literature Review
Strategic business IT alignment is a critical factor in the success of organizational IT governance. Numerous studies have examined the use of COBIT in the context of IT governance and business IT alignment across various sectors. These studies are generally partial and limited to specific contexts or COBIT domains, resulting in a lack of a comprehensive understanding of cross sectoral patterns in the use of COBIT and the evaluation approaches applied. This literature review aims to map the use of COBIT as a framework for evaluating IT business alignment across different sectors, including the COBIT domains and evaluation approaches employed. This study adopts a Systematic Literature Review (SLR) approach following the PRISMA guidelines, which consist of identification, screening, and final selection stages. The review results indicate that COBIT implementation is distributed across four sectors, namely education (35,29%), industry (29,41%), government and healthcare (each 17,65%), with the education sector being dominant context. The APO domain is the frequently used domain, followed by EDM, DSS, BAI, and MEA. Collectively, these domains reflect an evaluation focus on strategic planning, resource management, risk management, IT service delivery, and monitoring and evaluation mechanisms. The evaluation approaches identified in the reviewed literature are predominantly assessment-based, followed by IT governance design approaches, while comparative and exploratory approaches are used in a limited number of studies. The results of this review contribute by providing a structured overview of the patterns of COBIT domain usage and evaluative approaches across sectors. These findings may serve as a reference for future research as well as for practical evaluations of business and IT strategic alignment.
Strategic Business–IT Alignment, COBIT, IT Governance, Systematic Literature Review, Strategic Alignment
Copyright (c) 2026 Abdul Muis, Mukhammad Andri Setiawan http://creativecommons.org/licenses/by/4.0
Analysis of Irrigation Water Quality in Batang Lampasi
Irrigation water quality plays a key role in determining soil conditions and crop productivity. This study assessed the irrigation water quality of the Batang Lampasi Irrigation Area by analyzing a composite sample and comparing the results with FAO quality standards. Laboratory analyses included physical parameters—electrical conductivity (EC), turbidity, temperature, and odor—and chemical parameters such as pH, salinity, total Fe, total Ca, total Mg, and Sodium Adsorption Ratio (SAR). The results indicated that all measured parameters, including EC (132 µS/cm), turbidity (6.78 FTU), pH (6.44), salinity (34.32 ppm), Fe (0.904 mg/L), Ca (1.891 mg/L), Mg (1.795 mg/L), and SAR (0.467 meq/L), fall within acceptable limits set by FAO. These findings confirm that Batang Lampasi irrigation water is suitable for agricultural applications and underline the need for consistent monitoring and the development of national irrigation water quality standards.
Irrigation water quality, Batang Lampasi, FAO standards, physical–chemical parameters, SAR, salinity, iron (Fe) content
Copyright (c) 2025 Nola Rahma Yuni, Reni Ekawaty http://creativecommons.org/licenses/by/4.0