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All Journal Jurnal Ilmiah Ecosystem INTEK: Jurnal Penelitian Journal of Information Systems and Informatics Jurnal Teknologi Elekterika EJOIN : Jurnal Pengabdian Masyarakat Journal of Embedded Systems, Security and Intelligent Systems Journal of Informatics and Computer Engineering Research
Utomo, Muhammad Nur Yasir
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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WEB-BASED PUBLIC RELATIONS CHATBOT USING LARGE LANGUAGE MODELS AND THE RETRIEVAL-AUGMENTED GENERATION Nuzul1, Andi Muhammad; Utomo, Muhammad Nur Yasir; Indrabulan, Tantri
Journal of Informatics and Computer Engineering Research Vol. 2 No. 2 (2025)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v2i2.6014

Abstract

The Public Relations and Protocol Working Group (Pokja Humas) of Politeknik Negeri Ujung Pandang (PNUP) faces challenges in providing interactive and responsive information services. The official website functions only as a one-way medium, and the high volume of repeated questions causes delays in response time. This study developed a public relations chatbot based on Large Language Model (LLM) using the Retrieval-Augmented Generation (RAG) method to improve information services. The chatbot data were obtained through web scraping of the PNUP official website and internal PDF documents, which were processed through preprocessing, text splitting, and embedding using Hugging Face and stored in a FAISS vectorstore. The system was built using FastAPI as the backend and web-based interfaces for admin and user interactions. The results show that User Acceptance Test (UAT) involving 35 respondents achieved 91.93% acceptance (very good). The Retrieval-Augmented Generation Assessment (RAGAS) evaluation achieved average scores of 0.89 for Faithfulness, 0.91 for Answer Relevancy, 0.89 for Context Precision, and 0.89 for Context Recall, indicating that the chatbot produced relevant and contextually accurate answers.
Comparative Performance Analysis of Web Caching and Load Balancing in Web-Based E-Learning Platforms Silamba, Yurico Ignasius May; Utomo, Muhammad Nur Yasir; Syamsuddin, Irfan
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 1 (2026): March 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v7i1.2602

Abstract

Purpose – The increasing adoption of web-based E-learning platforms has introduced significant performance challenges under high user load, including elevated latency, degraded response time, and service downtime. While web caching and load balancing are commonly employed as mitigation strategies, empirical guidance on which technique better suits E-learning traffic characteristics remains limited. This study aims to provide a direct, controlled comparison between the two approaches.Design/methods/approach – An experimental methodology was employed using a Moodle-based E-learning platform deployed in a controlled virtualized environment.  Web caching was implemented with Varnish Cache and load balancing with HAProxy, each deployed on separate virtual machines running Moodle as the E-learning platform. Apache JMeter was used to simulate concurrent workloads ranging from 50 to 250 users, measuring latency, throughput, server response time, and failure rate.Findings – The results show that web caching consistently outperformed load balancing across all metrics. At 250 concurrent users, web caching reduced latency by 9.9%, improved throughput by approximately 4.5 times, decreased server response time by 96.6%, and lowered failure rate by 80.2% compared to load balancing. These findings indicate that caching more effectively mitigates backend overload in E-learning systems dominated by repetitive content access.Research implications/limitations – The experiments were conducted in a virtualized environment and focused primarily on static and semi-static content. Hybrid architecture combining both techniques were not evaluated.Originality/value – This study provides a head-to-head empirical comparison between web caching and load balancing under identical conditions, offering practical architectural guidance for infrastructure planning in academic environments.
Co-Authors Abdul Rahman Al Imran, Andi Yusdar Anggun Winursito BASTIAN, ALVIAN Fansab, Nur Ayu Farahgta Indrabulan, Tantri Irfan Syamsuddin Khartika, Widya Mochammad Imron Awalludin Muh. Fajri Raharjo Nuzul1, Andi Muhammad Ramadhani, Ainun Zulkiah Rini Nur, Rini Silamba, Yurico Ignasius May Syam, Muh. Fadhil TUNGADI, EDDY Violita, Fajrin Yusri, Iin Karmila