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Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Published by Institut Teknologi Pagar Alam
ISSN : 23391871     EISSN : 27157369     DOI : https://doi.org/10.36050/betrik.v10i03
Core Subject : Science,
Computer Science & IT
Besemah Teknologi Informasi dan Komputer (BETRIK) is a national journal published by Pusat Penelitian dan Pengabdian kepada Masyarakat (P3M), Institut Teknologi Pagar Alam (ITPA). This scientific work was published in 3 editions, with topics related to Computers, Technology, and Science. Topics related to this field can be information systems, informatics, computer science, IT business, IT Governance, enterprise architecture planning, software engineering, modeling and simulation, Data Mining, Artificial Neural Network, Digital Image Processing, Algorithm and Programming, Internet of Things (IoT), artificial intelligence, information security, social networking, cloud computing, science, engineering and related topics. The Scientific Journal BETRIK is a peer journal -National review dedicated to the exchange of high-quality research results in all aspects of education and teaching. This journal publishes the latest works in basic theory, experiments and simulations, as well as applications, with systematically proposed methods, adequate reviews of previous works, extended discussions and conclusions. As our commitment to the advancement of education and teaching, the BETRIK Journal follows an open access policy that allows published articles to be available online for free without subscribing.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 277 Documents
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Deteksi Cyberbullying Pada Teks Bilingual Menggunakan Bidirectional Long Short-Term Memory Mochammad Daffa Faiq Husin Syahputra; Anggraini Puspita Sari; Yisti Vita Via
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/2r7vry78

Abstract

The increasing use of social media not only provides various benefits but also contributes to the spread of cyberbullying. Detecting cyberbullying on social media is challenging because users frequently communicate in Indonesian, English, or a combination of both languages. In addition, previous studies have generally focused on detecting cyberbullying in a single language, limiting their ability to accommodate the characteristics of bilingual text. This limitation may lead to failures in detecting cyberbullying comments accurately and promptly, potentially causing psychological harm to victims. Therefore, an automated detection system capable of understanding the characteristics of bilingual text is needed. This study aims to develop a BiLSTM model for detecting cyberbullying in Indonesian and English texts. A bilingual dataset consisting of 21,308 Indonesian and English text samples was used to train the BiLSTM model. The experimental results show that the choice of optimizer affects model performance, with RMSProp outperforming Adam and SGD, achieving an accuracy of 96.01%, a precision of 96.03%, a recall of 96.01%, and an F1-score of 96.01%. These results demonstrate that the BiLSTM model with the RMSProp optimizer is effective for detecting cyberbullying in bilingual Indonesian and English texts.
Pengembangan Sistem Informasi Pelaporan Perjalanan Dinas Menggunakan Metode Rapid Application Development (RAD) Nolly Pialewi; Rudy Hartono
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/3xg6j086

Abstract

Microsoft Excel is still utilized by the Department of Cooperatives, Small and Medium Enterprises, and Trade (DISKUMDAG) of Landak Regency as the primary tool for data management and official travel reporting. This condition leads to difficulties in data retrieval and updating, risks of errors in cost calculation and data duplication, as well as an unintegrated process of report preparation and budget usage monitoring. As a resolution, a web-based official travel reporting information system was developed to facilitate the tasks of the Secretariat Division admin in managing official travel reporting data, while also providing information that supports the decision-making process for the Head of the Department. The Research and Development (R&D) approach was employed in this study, with the Rapid Application Development (RAD) method encompassing three stages, namely requirement planning, design workshop, and implementation. The Laravel framework with MySQL database was used as the foundation for system development. System testing was conducted through Black Box Testing and User Acceptance Testing (UAT) involving 20 individuals, consisting of 10 individuals with competence in the IT field and 10 employees of DISKUMDAG Landak Regency. The results of the Black Box Testing indicated that all system features functioned properly, while through UAT, a user acceptance rate of 90.92% was obtained. Based on the overall testing results, it can be concluded that the system has been well accepted by users and is considered to have met the requirements in the process of managing and reporting official travel
Sistem Pendukung Keputusan Pemilihan Minat Skripsi Berbasis Kesiapan AI Menggunakan Metode SAW Reza Ilham Ananditya; Arief Jananto
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/r91aev96

Abstract

Selecting a thesis interest area requires a structured assessment of student readiness, AI technology utilization, and personal interest. This study develops a web-based decision support system for Information Systems students at Universitas Stikubank. AI is measured as the C2 evaluation criterion rather than used as the computational algorithm, while the Simple Additive Weighting (SAW) method performs the entire ranking process. The researcher proposed the criterion weights and verified them through interviews with the thesis supervisor and Head of the Information Systems Study Program: student readiness 0.40, AI technology utilization 0.35, and student interest 0.25. The evaluation involved 40 students from the 2022 and 2023 cohorts. Validity testing retained six C1 items and seven C2 items, with Cronbach’s alpha values of 0.700 and 0.654. The recommendations were Artificial Intelligence & Machine Learning for 12 students (30.0%), Data Science & Analytics for 9 students (22.5%), Management Information Systems for 8 students (20.0%), Web Development for 6 students (15.0%), and Mobile Development for 5 students (12.5%). System outputs agreed 100% with manual calculations and all 18 functional scenarios worked properly. The system supports transparent academic guidance, while future work should develop readiness indicators that are specific to each alternative.
Analisis Performa Frontend Website Menggunakan Web Vitals Pada Halaman Community Yayasanmangroveindonesia.com najoan rizki; Reisa Permatasari; Abdul Rezha Efrat Najaf
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/q8mw3v50

Abstract

Frontend performance is a critical factor influencing website user experience, particularly in terms of page loading speed, visual stability, and rendering efficiency. This study aims to analyze the frontend performance of the community page on yayasanmangroveindonesia.com using the Core Web Vitals approach supported by two widely used automated testing tools, namely Google Lighthouse and GTmetrix. A descriptive quantitative method was employed by conducting performance testing three times on each tool, and the results were averaged to obtain more representative measurements. The evaluation focused on the metrics available in both tools, including Largest Contentful Paint (LCP) and Cumulative Layout Shift (CLS) as the primary metrics, supported by First Contentful Paint (FCP), Total Blocking Time (TBT), Speed Index, and Time to Interactive (TTI). The results show that Google Lighthouse achieved a Performance Score of  95, with an average LCP of 2.77 seconds, CLS of 0.03, FCP of 0.97 seconds, TBT of 56.67 ms, and Speed Index of 1.23 seconds. Meanwhile, GTmetrix obtained a Performance Score of 99 and a Structure Score of 100, with an average LCP of 0.48 seconds, CLS of 0.06, FCP of 0.48 seconds, TBT of 5.33 ms, and TTI of 0.66 seconds. Overall, the website demonstrates good frontend performance, although the LCP value measured by Google Lighthouse slightly exceeds the recommended Core Web Vitals threshold, indicating opportunities for further optimization. The findings suggest that combining Google Lighthouse and GTmetrix provides a more comprehensive performance evaluation and can serve as a reference for implementing frontend optimization strategies to improve user experience.
Implementasi WebGIS untuk Monitoring Infrastruktur Jaringan FTTH Saiful Adi Putra Adi; Agussalim; Nambi Sembilu
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/6xx7kb30

Abstract

The rapid expansion of Fiber to the Home (FTTH) infrastructure has increased the need for network monitoring systems capable of providing timely and accurate information about network conditions. At AFF NET, monitoring activities were previously conducted through manual inspections and customer reports, resulting in delays in fault identification. This study aims to implement a Web Geographic Information System (WebGIS) to provide interactive spatial visualization for monitoring FTTH network infrastructure. The system was developed using the Waterfall methodology with ReactJS as the frontend framework, Leaflet for interactive map visualization, Golang as the backend service, and Zabbix as the network monitoring platform. Monitoring data collected through the Zabbix API were integrated with geographic coordinates to display the location and operational status of network devices on a real-time digital map. Functional testing using the Black Box method achieved a 100% success rate, while User Acceptance Testing (UAT) obtained an average score of 87.50%, indicating excellent user acceptance. The results demonstrate that the proposed WebGIS improves the effectiveness of FTTH infrastructure monitoring by providing interactive spatial information, accelerating fault identification, and supporting more efficient network troubleshooting.
Evaluasi Kualitas Sistem Informasi Akademik SMK Negeri 1 Sukoharjo Menggunakan WebQual 4.0 dan (IPA) Muhammad Rifqi Anshory; Mulyadi S; Aji Supriyanto
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/1pn26718

Abstract

Educational administration in the digital era demands governance transformation through information technology; however, at State Vocational High School (Sekolah Menengah Kejuruan or SMK) Negeri 1 Sukoharjo, which possesses specific administrative complexities such as Field Work Practice (Praktik Kerja Lapangan or PKL) logbook management, comprehensive evaluation of service quality from the end-user perspective is still very minimal, potentially triggering inefficiencies in academic administration. This study aims to evaluate the quality level of the Academic Information System at SMK Negeri 1 Sukoharjo and to identify service attributes that are top priorities for improvement as well as those that need to be maintained. The research method used is descriptive quantitative by adopting the Website Quality 4.0 (WebQual 4.0) instrument, which includes Usability, Information Quality, and Service Interaction Quality dimensions, as well as the Importance Performance Analysis (IPA) method to visualize improvement priorities into a Cartesian quadrant matrix. Research data were gathered through online questionnaires and documentation studies involving stakeholders consisting of students, teachers, and administrative staff, where the minimum sample size determination was calculated using the Slovin formula through the Proportionate Stratified Random Sampling technique. The results of the conformity level analysis and attribute mapping on the Cartesian diagram show an overall level of conformity of 85.36%, with the Usability dimension achieving the best performance, while the Information Quality and Service Interaction Quality dimensions, particularly the PKL data update and helpdesk responsiveness attributes, were identified as top priorities for improvement in Quadrant I. The novelty of this research lies in its multi-stakeholder evaluation (students, teachers, administrative staff) of an Academic Information System at a vocational high school with the unique complexity of PKL logbook management, yielding a structured improvement priority map with concrete recommendations for the development team and school management in efficiently planning budget allocation and system enhancements to optimize overall user satisfaction.
Optimasi Manajemen Jaringan Menggunakan Segment Routing Traffic Engineering Pada SMKN 3 Buduran Azriel Dirga Efansyah; Agussalim; Nambi Sembilu
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/wv16bp68

Abstract

This research aims to optimize network management at SMKN 3 Buduran through the implementation of Open Shortest Path First (OSPF), Quality of Service (QoS) using the Queue Tree method, and TLS Host-based firewall filtering on MikroTik devices. The main problems identified in the school network include high delay and jitter values, uneven bandwidth distribution, and suboptimal network traffic management. This research applied the PPDIOO (Prepare, Plan, Design, Implement, Operate, Optimize) method with network simulation implemented using Cisco Packet Tracer and VirtualBox. The implementation stage involved configuring OSPF routing to support automatic rerouting processes, applying QoS for bandwidth management, and implementing firewall filtering to restrict access to certain websites. Network performance testing was conducted using Quality of Service (QoS) parameters, namely delay, jitter, and packet loss. The results showed that the implementation of OSPF and QoS significantly improved network performance. The average delay decreased from 78 ms to 59 ms, while the maximum delay decreased from 1193 ms to 117 ms. In addition, network connectivity remained stable during link failures through the automatic rerouting mechanism provided by OSPF. Furthermore, firewall filtering successfully restricted access to non-educational websites, resulting in more controlled network usage. Based on the testing results, the implementation of OSPF, Queue Tree QoS, and firewall filtering proved effective in improving the stability, efficiency, and quality of network services at SMKN 3 Buduran.
Perancangan Penentuan Dosen Terbaik Menggunaan Metode Weighted Product (WP) Prodi Sistem Informasi Christien Rozali; Mufidah Karimah; Ragil Nur Iman
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/ewvthq73

Abstract

This study aims to implement the Weighted Product (WP) method in a Decision Support System (DSS) to evaluate and determine lecturer performance objectively, systematically, and measurably. Lecturer performance evaluation is an essential component of higher education quality assurance to maintain the quality of teaching, research, and lecturers' contributions to their institutions. The WP method was selected because it supports multi-criteria decision-making by assigning weights to each evaluation criterion according to its level of importance. This study employs five evaluation criteria: Functional Academic Credit Score (PAK), attendance, JAD, supervision assessment, and student evaluation. The implementation process includes collecting lecturer performance data, determining the weights of each criterion, and calculating the final scores using the WP method. The system was developed as a web-based application using HTML, CSS, JavaScript, Bootstrap, Chart.js, and MySQL. System testing was conducted to evaluate its ability to produce accurate, objective, consistent, and balanced assessment results. The findings indicate that the WP method provides measurable information regarding lecturer performance and effectively supports the decision-making process. Based on the evaluation of ten lecturers, Andri Fahmi achieved the highest V vector value of 0.102. This study is expected to serve as a reference for higher education institutions in developing transparent, fair, and effective Decision Support Systems to support lecturer performance evaluation and career development.
Platform E-Pangkal AI Berbasis Kearifan Lokal untuk Monitoring Harga dan Distribusi Pangan Strategis Kota Lubuklinggau Muhammad Irvai; Davit Irawan; Ade Famalika
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/yg8zpb45

Abstract

This study is motivated by the importance of controlling the stability of strategic food prices to support food security and economic stability in Lubuklinggau City. Price fluctuations are influenced by the complexity of the supply chain, while conventional price reporting and food distribution systems result in delays in information dissemination and less effective policy decision-making. This study aims to develop E-Pangkal AI, a digital platform that integrates real-time food price and distribution monitoring, Long Short-Term Memory (LSTM)-based price forecasting, and local wisdom-based analysis to support regional price stabilization and inflation control. The research employed the Research and Development (R&D) method using the Prototype development model, which includes system design, prototype development, user evaluation, and iterative system refinement. The commodities analyzed consisted of rice, shallots, red chili peppers, cooking oil, and chicken meat, with a total of 1,797 datasets. The results of the LSTM model evaluation demonstrated good forecasting accuracy based on the Mean Absolute Percentage Error (MAPE), with values of 1.96% for rice, 6.98% for shallots, 3.63% for red chili peppers, 2.80% for cooking oil, and 2.06% for chicken meat. The findings indicate that the E-Pangkal AI platform is capable of integrating food price monitoring, food distribution monitoring, and LSTM-based price forecasting, enabling it to serve as a decision support system for the Government of Lubuklinggau City
Explainable Predictive Analytics untuk Prediksi Pengunduran Diri Karyawan pada Data Human Resource Analytics Sri Hartati; Rusidi; Dodi Herryanto
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/gcx9tn49

Abstract

Digital transformation has encouraged organizations to adopt Human Resource Analytics and Artificial Intelligence to support data-driven decision-making, including employee attrition prediction. Although numerous predictive models have been developed, most of them still suffer from limited interpretability, making their predictions difficult for Human Resource practitioners to understand and utilize. This study aims to develop an Explainable Predictive Analytics model for employee attrition prediction by integrating Information Gain, Random Forest, RandomizedSearchCV, and SHapley Additive exPlanations (SHAP). The study employs the IBM HR Analytics Employee Attrition & Performance dataset consisting of 1,470 employee records. The research workflow includes data preprocessing, feature selection using Information Gain, Random Forest model development, hyperparameter optimization using RandomizedSearchCV, model evaluation using Accuracy, Precision, Recall, F1-Score, and ROC-AUC, followed by model interpretation through SHAP Summary Plot and SHAP Feature Importance. The experimental results indicate that the model achieved 82.54% Accuracy, 37.50% Precision, 12.68% Recall, 18.95% F1-Score, and a ROC-AUC of 0.7439. Feature selection results indicate that OverTime has the highest Information Gain value, while MonthlyIncome is identified as the most influential feature according to Random Forest Feature Importance. The main contribution of this study is the integration of Information Gain-based feature selection, Random Forest optimization, and SHAP-based Explainable Artificial Intelligence into a unified Explainable Predictive Analytics framework, providing a more transparent and interpretable predictive model to support decision-making in Human Resource Management

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