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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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Pengembangan Sistem Informasi Penyewaan Alat Berat Berbasis Web dengan Metode Extreme Programming yuan Ramatullah; Lisa Amelia Frasen
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: 10.36050/7cpt4q36

Abstract

PT Rachmat Kelantan Sakti is a company engaged in heavy equipment rental services to support construction and infrastructure development activities. The data management process for equipment rental is still carried out manually using notebooks and Microsoft Excel, causing delays in data retrieval, transaction recording errors, difficulties in monitoring heavy equipment, and unintegrated operational reporting. This research aims to design and develop a web-based Heavy Equipment Rental Management Information System using the Extreme Programming (XP) method. The XP method was chosen because it supports fast, flexible, and user-oriented software development. The system was developed using the Laravel framework and MySQL database. The system features include customer management, heavy equipment data, rental transactions, maintenance, operational monitoring, vendors, invoices, and company reports. The results show that the developed system can improve data management effectiveness, accelerate information retrieval, simplify operational monitoring, and reduce transaction recording errors. Based on Black Box Testing, all system features function properly according to user requirements.
Komparasi Arsitektur Densenet121, MobilenetV2, dan Resnet50 Untuk Klasifikasi Awan Menggunakan Transfer Learning Yashin Al Fauzy Sabara; Carissa Fathinah Balti; Ahmad Hasan Faqih Aulia; Dodik Ariyanto; Faldiena Marcelita; Mayanda Mega Santoni
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: 10.36050/6hwf0s96

Abstract

Cloud image classification plays an important role in supporting atmospheric analysis and the development of artificial intelligence-based weather prediction systems. However, visual similarities among cloud types and variations in lighting conditions remain major challenges in automatic classification tasks. This study aims to compare the performance of three Convolutional Neural Network (CNN) architectures, namely DenseNet121, MobileNetV2, and ResNet50, for cloud image classification using a transfer learning approach. The dataset used in this study was the TJNU Ground-based Cloud Dataset, consisting of seven cloud classes with a total of 19.000 images; after removing the Mixed Clouds category with the total of 18.047 images; after removing. The research stages included pre-processing, data augmentation using the Color Jitter technique, model training through feature extraction and fine-tuning, and evaluation using Accuracy, Precision, Recall, and F1-Score metrics. Experimental results showed that ResNet50 achieved the best performance with an accuracy of 90,58% and an F1-score of 91,38%, followed by DenseNet121 with 89,53% accuracy and MobileNetV2 with 85,10% accuracy. In addition to obtaining the highest classification performance, ResNet50 also demonstrated good computational efficiency with the fastest training time of 20.9 minutes. These findings indicate that architectures based on residual learning are more effective in capturing the visual characteristics of cloud images compared to the other architectures evaluated in this study.
Perancangan sistem absensi online berbasis qr-code studi kasus: dosen dan mahasiswa program studi sistem informasi universitas pgri silampari menggunakan metode prototipe Neni mawar sari Mawar; Siti Aminah; Dina Dalilah
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: 10.36050/279d0c74

Abstract

This research aims to design and develop a QR Code-based attendance information system for lecturers and students in the Information Systems Study Program at Universitas PGRI Silampari using PHP and MySQL. The system was developed to overcome problems associated with the existing manual attendance process, including recording errors, delays in data processing, and the potential for attendance data manipulation. The system was developed using the Prototype development method, which consists of requirements analysis, prototype design, evaluation, refinement, implementation, and system testing. System testing was conducted using the Black Box Testing method to ensure that all system functions operated according to user requirements. The test results indicated that all system features, including user login, lecturer and student data management, QR Code generation, attendance recording, and attendance report generation, functioned successfully with a 100% success rate. Therefore, the developed system is considered valid and capable of improving the efficiency and accuracy of attendance management, simplifying attendance monitoring, and supporting faster, more accurate, and well-structured report generation.
Redesign Antarmuka Open Library Telkom University Berbasis User-Centered Design Ihsan Putra; Rizky Febriyanto; Fadhil Rahman Yuriana; Muhammad Naufal Fadhillah; Irfan Walhidayah
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/yyta7f66

Abstract

Open Library Telkom University is a knowledge management center, both digitally and physically, that plays an essential role for the academic community. However, evaluation results showed that the Open Library system interface, particularly the digital platform, obtained a System Usability Scale (SUS) score of 47.5, which falls into the Poor category. Users frequently encountered difficulties due to an unintuitive interface, confusing navigation, and unclear system messages. This study aims to evaluate and redesign the user interface and user experience of the Open Library website using a user-centered Human-Computer Interaction approach, namely User-Centered Design (UCD). The methods applied include Hierarchical Task Analysis (HTA) to simplify workflows, conceptual modeling, improvement of instructional texts, and the implementation of feedback and assistance mechanisms. In addition, the design was optimized through internationalization, localization, and accessibility processes to support users with various limitations, such as color blindness, hearing impairments, and other accessibility needs. The result of this study is an interactive interface prototype featuring a more structured layout and a system that complies with visual accessibility standards. Based on the evaluation results using the System Usability Scale after the redesign of the Open Library website interface, a score of 79.5 was achieved, which is categorized as Good. The proposed design has been proven to minimize users’ cognitive load and effectively address usability issues.
Rancang Bangun Aplikasi E-Commerce Produk Kecantikan Dengan Sistem Rekomendasi Personal Berbasis Jenis Kulit Dan Undertone Dinda Syafitri; Sahara Lani Lestari; Kayla Amelia Putri; Deby Yandra Niska
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/yyg9jb02

Abstract

The rapid growth of digital technology has encouraged small beauty businesses to shift toward digital platforms, yet many consumers still struggle to find products that match their skin condition. This study aims to develop a web-based e-commerce application called BeautyMatch, equipped with a Beauty Quiz feature using the Content-Based Filtering (CBF) method to provide personalized skincare product recommendations based on skin type and makeup recommendations based on undertone. The system was built using Node.js and Express.js for the backend, HTML5, CSS3, and JavaScript for the frontend, and MySQL as the database, with an Agile development approach. Functional testing using Black-Box Testing across 12 scenarios yielded a 100% success rate, while User Acceptance Testing (UAT) conducted on 50 respondents produced an average score of 4.48 out of 5. The results demonstrate that integrating the Beauty Quiz feature with the CBF algorithm effectively helps users find beauty products that best match their skin profile.
Pemilihan Artificial Intelligence Tools Menggunakan Metode SAW Berbasis Web Pada Mahasiswa UNBARA Riya Majalista; Yuli Ermawati; Zulkarnaini
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/pbye3f21

Abstract

The rapid development of artificial intelligence (AI) tools presents a challenge for students in selecting the tools best suited to their academic needs. This study aims to recommend the best AI tools for students at Universitas Baturaja using the Simple Additive Weighting (SAW) method. Data were collected through questionnaires distributed to 150 students at Universitas Baturaja, selected using a purposive sampling technique, namely students who had used at least two of the four evaluated AI tools in their academic activities over a certain period of time. The    assessment was carried out on four alternatives Meta AI (A3), and Claude AI (A4), based on five criteria: ease of use (K1, weight 0.20), response speed (K2, weight 0.20), feature completeness (K3, weight 0.20), answer accuracy (K4, weight 0.25), and cost (K5, weight 0.15). Criteria weights were determined through expert discussion, taking into account the relative importance of each criterion to students' academic needs, while the score of each alternative on each criterion was obtained from the average rating given by 150 respondents on a 1–5 Likert scale. The SAW calculation results show that ChatGPT obtained the highest preference value of 0.9519, followed by Google Gemini at 0.8774, Claude AI at 0.8533, and Meta AI at 0.7319. ChatGPT performed best because it received the highest scores on the feature completeness and answer accuracy criteria, and achieved a perfect normalized value (1.000) on the cost criterion, since ChatGPT had the lowest cost score among the alternatives, making it the minimum reference value in the cost normalization calculation; meanwhile, Google Gemini performed better on ease of use and response speed. The SAW method in this study was able to produce a ranking that is structured, consistent, and mathematically traceable based on user perception, making it suitable as one of the institutional references for supporting AI tool selection, with the caveat that the results still reflect the subjective perceptions of respondents during the particular data collection period.
Prototipe Sistem Monitoring Jaringan Dan Otomasi Bandwidth Manager Dengan Visualisasi Grafana Pada Lingkungan Virtual Ridho Affandi; Dedy Kiswanto; Syti Salwaa Nafiisah; Shaqila Rahmayani
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/vme53t62

Abstract

The increasing complexity of information technology–based services has led to a growing demand for reliable and efficient network management. Network performance monitoring and bandwidth allocation control are critical aspects in maintaining network stability, availability, and quality of service. This paper presents the development of a network monitoring system prototype integrated with an automated bandwidth management mechanism in a virtualized environment. The system is designed to collect network performance data in real time, automatically manage traffic priorities, and present network information through clear and informative visualizations. A virtual environment is utilized to provide flexibility, resource efficiency, and ease of system testing. The prototype results indicate that the system enhances network visibility, supports more effective bandwidth management, and enables structured traffic control. This prototype is expected to serve as an initial solution for network management and as a foundation for further development of network monitoring and automation systems.
Sentralisasi Manajemen Multi-Router MikroTik Berbasis Web Melalui REST API pada Lingkungan Virtualisasi Azril Arfansyah; Dedy Kiswanto; Muhammad Iqbal Fahrezzi; Arion Pardede
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/z6vfkq27

Abstract

Conventional management of MikroTik-based network infrastructure still relies on desktop-bound applications such as Winbox and Command Line Interface (CLI) that require per-device manual configuration, causing operational inefficiencies and the inability to provide centralized real-time visibility. This study develops a web-based Network Management System (NMS) leveraging the built-in REST API of MikroTik RouterOS version 7 to automate and centralize the configuration and monitoring of multiple routers within a single dashboard. The system is built on a three-tier architecture: a React 19-based frontend with Vite bundler, a Node.js and Express.js-based backend proxy, and an SQLite database layer. Evaluation was conducted in two stages: Black Box Testing for module functionality validation, and quantitative performance testing covering API endpoint response times, concurrent throughput, and multi-router scalability simulation. Results indicate that all 17 main API endpoints respond with an average time of 18.69 ms and a request success rate of 100% out of 1,404 total requests, with a communication failure rate of 0.00%. Scalability tests with 1 to 30 routers demonstrate sub-linear time growth through parallel and asynchronous execution mechanisms, with a total processing time of 185.98 ms for 30 simultaneous routers and a parallelization efficiency of 2.92x. The primary contribution of this study is the empirical demonstration that a Node.js proxy architecture exploiting RouterOS v7 REST API effectively scales multi-router configuration operations with measurable efficiency, while simultaneously integrating WireGuard VPN automation with server-side cryptographic management in a single platform.
Perancangan Sistem Informasi Pemasaran Perumahan Berbasis Web Julia Dwi Saputri; Ariansyah; Fajriyah
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/bqdm7711

Abstract

Muara  Cipta  Baru  Housing  is  currently  still  conducting  marketing  manually  through  the  distribution  of  brochures  and  word-of-mouth,  resulting  in  limited  marketing  reach  and  less  effective  information  delivery.  To  improve  information  dissemination  and  make  things  simpler  for  prospective  buyers  to  acquire  data  regarding  house  types,  prices,  and  locations,  a  marketing  system  of  information  that  is  accesible  widely  and  quickly  is  required.  This  study  attempts  for  create  a  web-based  on  housing  advertising  system of information  utilizing  the  prototype  technique,  which  allows  the  system  development  process  to  be  carried  out  interactively  through  stages  of  requirement  communication,  rapid  design,  user  evaluation,  and  iterative  improvements  until  a  system  that  meets  needs  is  prodused.
Klasifikasi Dinasti Artefak Keramik Cina Berbasis Citra Fotografi Menggunakan Pendekatan Teachable Machine Yogi Piskonata; Agung Pambudi; Rum Muhammad Andri K Rasid; Yoga Sahria
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/qk5d4q30

Abstract

Chinese Ceramics constitute one of the most frequently encountered archaeological artifacts in Indonesia and play a pivotal role in chronological studies and the reconstruction of historical maritime trade networks. Their presence is commonly employed as a relative dating indicator for archaeological sites and as evidence of interregional cultural interactions. Consequently, identifying the dynasty of origin of Chinese ceramics represents a critical aspect of archaeological and maritime historical research in Asia Conventionally, such identification relies on visual analysis conducted by experts, based on morphological and decorative characteristics including glaze color, decorative motifs, vessel shape, and surface texture. However, this approach is inherently subjective, time-consuming, and prone to inconsistencies particularly when applied to large assemblages of ceramic finds. This study aims to implement a machine learning (ML) approach to classify Chinese ceramic dynasties using photographic images. The research dataset comprises labeled photographs of ceramics from various dynastic periods, annotated according to their distinctive visual features. The methodological framework encompasses data collection and image preprocessing, dynasty labeling, model training via the Teachable Machine platform, and performance evaluation through classification accuracy assessment. The results demonstrate that the machine learning model developed using Teachable Machine effectively recognizes the characteristic visual patterns associated with each dynasty, achieving a satisfactory level of classification accuracy. The results demonstrate that Teachable Machine can identify the unique visual patterns of each dynasty with high precision, achieving an overall accuracy of 91%. High classification stability and performance were observed for the Qing Dynasty, with Precision of 0.95, Recall of 0.95, F1-Score of 0.95, and a matrix value of 0.94. Conversely, the lowest classification performance was recorded for the Yuan Dynasty, with Precision of 0.90, Recall of 0.84, and an F1-Score of 0.86. These findings indicate that image-based machine learning holds significant potential as a supportive analytical tool in digital archaeology particularly in enhancing the objectivity, consistency, and efficiency of Chinese ceramic identification, documentation, and data management processes.

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