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INDONESIA
Journal of Applied Computer Science and Technology (JACOST)
Published by Indonesian Society of Applied Science
ISSN : -     EISSN : 27231453     DOI : https://doi.org/10.52158/jacost
Core Subject : Science,
Computer Science & IT
Fokus dan Ruang Lingkup Journal of Applied Computer Science and Technology (JACOST) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian bidang ilmu komputer dan teknologi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Ilmu Komputer dan Teknologi. Journal of Applied Computer Science and Technology (JACOST) menerima artikel ilmiah dengan lingkup penelitian pada: Rekayasa Perangkat Lunak Rekayasa Perangkat Keras Keamanan Informasi Rekayasa Sistem Sistem Pakar Sistem Penunjang Keputusan Data Mining Sistem Kecerdasan Buatan Jaringan Komputer Teknik Komputer Pengolahan Citra Algoritma Genetik Sistem Informasi Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Topik kajian lainnya yang relevan
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 11 Documents
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Search results for , issue "Vol. 6 No. 2 (2025): Desember 2025" : 11 Documents clear
A Systematic Literature Review of Retrieval-Augmented Generation: Methods, Applications, and Future Research Directions Hajar, Muhammad Rizky; Utami, Ema; Hendi Muhammad, Alva
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jacost.v6i2.1170

Abstract

Retrieval-Augmented Generation (RAG) represents a growing research direction in the advancement of large language models (LLMs) by incorporating external information sources into the response generation process. As LLM-based systems are increasingly deployed in information-sensitive domains such as healthcare, education, and law, the demand for responses that are not only fluent but also verifiable and context-aware has become more pronounced. This study conducts a systematic literature review (SLR) of 100 recent publications to examine methodological approaches, application domains, technical challenges, and research contributions related to RAG. The review draws on studies indexed in major academic databases, including IEEE, ACM, and Springer, and applies structured inclusion and exclusion criteria to ensure analytical rigor. The findings reveal a strong emphasis on architectural optimization, particularly in the interaction between retrieval and generation components, alongside widespread adoption in domain-specific contexts. Persistent challenges identified across the literature include limitations in retriever effectiveness, system integration complexity, and the absence of standardized evaluation benchmarks. Overall, this review provides a structured synthesis of current RAG research and highlights directions for future investigation and practical deployment..
Implementasi UAV dan ArcGIS untuk Pemetaan 3D Kawasan Hutan Konservasi Ubadari Rumui, Nelson; Al Hamid, Deisya Maulida; Anas, Syukron
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/j6kwy595

Abstract

This study aims to produce a three-dimensional (3D) visualisation model of the Ubadari Conservation Forest Area in Fakfak Regency, West Papua, using Unmanned Aerial Vehicle (UAV) technology and ArcGIS Pro software. Aerial imagery data was collected through photogrammetric missions with calibrated parameters. This elevation model has high accuracy with a Root Mean Square Error (RMSE) value of 0.35 metres, indicating an average vertical deviation of only about 35 cm from the actual elevation value—accurate enough for conservation and advanced mapping applications. Spatial analysis was conducted to map topography, vegetation index (NDVI), land cover classification using the k-means clustering algorithm, as well as zones prone to degradation and potential fires. The results show that more than 15% of the area has a slope of >30%, and around 22.3% of the area is classified as having poor vegetation health. Meanwhile, 23.7% of the area was classified as low vegetation cover. Degradation and fire-prone zones covered 18.5% of the study area, mainly around road access and the edges of the area. These findings contribute to data-based monitoring systems and form an important basis for risk mitigation planning and conservation forest ecosystem preservation.
Sistem Pendukung Keputusan Pemilihan Mobil Bekas Berbasis Web Menggunakan Metode Weighted Product Prayogi, Nandang; Sudarmaningtyas, Pantjawati; Arrosyidi, Achmad
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jacost.v6i2.1224

Abstract

Limited information about vehicle conditions and manual selection methods often leaves prospective used car buyers uncertain. This problem occurs at the Sumber Rejeki Showroom, which has not yet adopted a decision support system to assist buyers in selecting used cars. This study aims to develop a web-based decision support system for used car selection using the Weighted Product (WP) method. Using a quantitative approach, the study involves collecting car attribute data, assigning criterion weights, and testing the system. Validation is conducted by comparing system-generated rankings with manual WP calculations and by performing white box testing to verify the correctness of the system logic. The system development follows the intelligence, design, choice, and implementation stages. The results show that the system’s ranking aligns exactly with manual calculations, confirming the proper application of the WP method. White box testing indicates error-free WP computations, and a Cyclomatic Complexity score of 10 suggests that the code is maintainable. Overall, the study demonstrates that the developed web-based decision support system can effectively support used car selection, enhance decision-making efficiency, and increase user confidence.
Penerapan REST API pada Aplikasi Antarmuka Alat Pemantauan Tambak Udang Abdul Aziz, Fiqri; Subandri, M. Asep; Armada
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/19qkf837

Abstract

Increasing shrimp pond productivity is a top priority in fisheries cultivation, especially with the challenge of maintaining water quality as a determining factor for success. The use of modern technology such as the Internet of Things (IoT) allows the integration of monitoring tools with software-based interface applications. This study aims to develop a shrimp pond monitoring tool interface application that uses REST API to connect IoT devices with a Flutter-based application system. The methods used include software development using prototyping with a system design approach based on evaluations received from users to obtain results that meet user needs. The data obtained is sent to Firebase via REST API and displayed in real-time on a Flutter-based application. The results of the study show that the application of REST API allows faster and reliable data transmission between IoT devices and interface applications. The REST API achieved an average response time between 70–87 ms with 0% packet loss during 10-minute testing using Apache JMeter. The monitoring sensors reached accuracy levels of 93.3–96.0% for temperature and 93.7–96.4% for pH measurements. The resulting application makes it easy for users to monitor pond conditions in real-time via mobile devices. This technology supports faster pond management by delivering accurate information. This research is expected to be the basis for further development of IoT-based pond monitoring systems, focusing on improving system features and reliability to support the sustainability of shrimp pond cultivation.
Application of Bagging and Boosting Methods for Heart Disease Classification Parapak, Yehezkiel E.A; Robet, Robet; Hendrik, Jackri
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/we9asn06

Abstract

Cardiovascular disease remains a primary contributor to global mortality, underscoring the urgent need for accurate and early diagnostic tools. This study aims to develop a robust classification model for heart disease by conducting a comparative analysis of six ensemble machine learning algorithms, comprising three from the Bagging family (Random Forest, Bagged Decision Tree, Extra Trees) and three from the Boosting family (AdaBoost, Gradient Boosting, XGBoost). The research utilizes the publicly available UCI Cleveland Heart Disease dataset, which exhibits a mild class imbalance. To address this, the Synthetic Minority Over-sampling Technique (SMOTE) was strategically applied to the training data. The performance of each model was rigorously evaluated using accuracy, precision, recall, and F1-score. Experimental results revealed that the Extra Trees algorithm, when combined with SMOTE, achieved the highest overall performance with 90% accuracy, 96% precision, 82% recall, and an 88% F1-score. The primary contribution of this work lies in its comprehensive analysis demonstrating that the randomization strategy of Extra Trees provides a superior and more reliable framework for this classification task compared to other common ensemble techniques, particularly after data balancing. These findings confirm that an integrated approach of ensemble learning and proper data balancing can significantly enhance the development of fair and effective diagnostic tools to support medical professionals.
Systematic Literature Review: Tren dan Tantangan Machine Learning pada Sistem Rekomendasi Kursus Daring Habibi, Roni; Ramadhan, Ryaas Ishlah
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/ct1kr873

Abstract

This study presents a Systematic Literature Review (SLR) on the application of machine learning in online course recommendation systems. The aim is to map research trends, methodological approaches, and challenges in developing AI-based recommendation systems for online education. A total of 40 Scopus-indexed articles published between 2020 and 2025 were analyzed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, using the Watase UAKE tool for literature selection. The findings reveal that deep learning and hybrid models are the most dominant approaches, with a significant increase observed during 2022–2024. China contributes 57.5% of the studies, followed by India and Taiwan, indicating a strong research concentration in Asia. Combined architectures such as CNN–LSTM–ResNet achieved the highest accuracy (99.2%), while Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL) are emerging as adaptive approaches for course recommendation. The main challenges identified include real-time adaptability, computational efficiency, and model transparency. The main contribution of this paper is to provide a comprehensive map of current research and outline future directions toward adaptive, efficient, and explainable online course recommendation systems.T
Evaluasi Pengaruh Kualitas Website Kampung Kopo terhadap Kepuasan Pengguna Menggunakan Model WebQual 4.0 Ahoren, Anan Ansi; Suhendra, Christian Dwi; Baisa, Lorna Yertas
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/tftzct83

Abstract

This study evaluates the quality of the Kampung Kopo website using the WebQual 4.0 model, which comprises three dimensions: usability, information quality, and interaction quality. A quantitative survey was conducted with 109 purposively selected respondents, and data were analyzed using multiple linear regression. Descriptive results showed that usability (4.03) and information quality (4.03) received high scores, while user satisfaction was moderate (3.41). Regression analysis revealed that all three dimensions significantly influenced satisfaction: interaction quality (β = 0.401; p < 0.001), information quality (β = 0.345; p < 0.001), and usability (β = 0.306; p < 0.001). The model was significant (F = 308.281; p < 0.001) and explained 89.8% of satisfaction variance (R² = 0.898). These findings confirm that while interaction quality has the strongest effect, all three dimensions play essential roles in determining user satisfaction. Village websites should adopt a comprehensive approach to improve usability, information quality, and interaction quality simultaneously to strengthen digital transformation at the village level.
Pengembangan Sistem Anti-Spoofing Berbasis Face Recognition Menggunakan Arsitektur YOLOv8n Tanujaya, Carmelita Angeline; Azhar, Nur Fajri; Nugroho, Bowo
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jacost.v6i2.1362

Abstract

Face spoofing poses a major threat to facial recognition–based authentication systems, especially in web-based environments that require lightweight and real-time verification. This study develops a real-time anti-spoofing system that integrates YOLOv8n for classifying four facial categories (real, printed, digital, and mask), combined with blink-based liveness verification using the Eye Aspect Ratio (EAR). Using 400,800 images and 18 videos, two training strategies—pretrained and from scratch—were evaluated. The pretrained model achieved a precision of 99.5%, recall of 98.6%, mAP50 of 99.4%, and mAP50–95 of 90.4%, slightly outperforming the from-scratch model. EAR threshold evaluation showed that a value of 0.17 yielded the best performance with 99.02% accuracy, 100% recall, a FAR of 16.11%, and an FRR of 0%. The proposed integration of YOLOv8n and EAR represents a practical novelty for lightweight, web-based anti-spoofing, providing fast inference and stable real-time performance suitable for modern facial authentication systems.
Rancang Bangun dan Evaluasi Sistem Smart-Ponik Untuk Monitoring dan Automatisasi Tanaman Hidroponik Berbasis IOT dengan Protokol MQTT QTT Rachmini, Siti Aulia; Rasyid, Muh. Rafli; Insani, Chairi Nur; Rabbani, Alim
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/tpd2rq94

Abstract

Hydroponic farming, a soil-free farming method that has grown in popularity due to its efficient land use and ability to deliver high-quality yields. However, when managed manually, it often encounters issues such as inaccurate watering, imprecise nutrient regulation, and delays in detecting environmental changes. These factors can lead to reduced productivity and lower crop quality. This research aims to address these issues by developing Smart-Ponik, an Internet of Things (IoT)-based monitoring and automation system for hydroponic cultivation utilizing the Message Queuing Telemetry Transport (MQTT) protocol. The system integrates DHT22, soil moisture, and pH sensors to monitor key environmental parameters and transmits data in real time to a server for visualization through a web-based dashboard and automated notifications. The study employs a Research and Development (R&D) method consisting of needs analysis, system design, implementation, and testing. Experimental results show that the system achieves a 100% data transmission rate without packet loss, with an average latency of 0.00 seconds, and occasional delays of 0.01–0.02 seconds due to network fluctuations. Automated control of pumps and fans records a 95% success rate, while black-box testing demonstrates a 100% functional pass rate. In conclusion, Smart-Ponik proves effective for real-time monitoring and automation of hydroponic environments. The system minimizes manual errors, enhances environmental stability, and supports more consistent crop yields. These findings highlight the potential of IoT-based automation to improve precision agriculture practices and increase the reliability of hydroponic production.
Pengembangan Website Harga Bapokting Real-time dengan Extreme Programming dan Integrasi API SILINDA Setiawan, Ridwan; Parlina, Rina; Gunadhi, Erwin
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/98c7mh73

Abstract

This study aims to implement the SILINDA API from the West Java Provincial Government on a prototype website to present real-time price data for Basic Necessities and Important Goods (Bapokting) in Garut Regency. This addresses the problem of reporting delays and potential data inaccuracies that arise from the manual process of reporting via WhatsApp and weekly recapitulation using Microsoft Excel. The system was developed using the Extreme Programming (XP) methodology, which includes the stages of planning, design, coding, and testing. System design utilizes Unified Modeling Language (UML), specifically use case and class diagrams. The implementation uses JavaScript with the React.js library for the frontend and Node.js with the Express.js framework for the backend. The result of this research is a website prototype that is synchronized with the SILINDA API to perform automatic price updates. System testing included unit testing with a black-box approach and acceptance testing using the System Usability Scale (SUS) method, which yielded an average score of 83, categorized as Grade A (Excellent) with an "Acceptable" level of acceptance. This research contributes a system that replaces the manual reporting process with a website synchronized with SILINDA, providing real-time data for the Disperindag ESDM, Garut Satu Data, and the general public. It also demonstrates the effectiveness of the XP method in building an adaptive system that is relevant to user needs.

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