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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.
Assessing Language Reasoning Skills of Indonesian Students Using Computerized Adaptive Testing Sudaryanto, Memet; Utomo, Muhammad Nur Yasir
International Journal of Pedagogy and Teacher Education Vol 8, No 1 (2024): International Journal of Pedagogy and Teacher Education - April
Publisher : The Faculty of Teacher Training and Education (FKIP), Universitas Sebelas Maret, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijpte.v8i1.89913

Abstract

Language, as the fundamental means of communication, represents the symbolization of thoughts conveyed to others. Human understanding of the structure of messages relies on the speaker's language reasoning ability. This ability can be measured from the simplest to the most complex stimuli. Traditionally, assessing language reasoning has been done through written tests, which require extensive preparation and are time-consuming. This study proposes a model for measuring language reasoning ability using a Computerized Adaptive Test (CAT). The CAT adjusts the difficulty of questions in real time based on the participant's responses. If a participant answers correctly, the system presents a more challenging question. Conversely, the system selects an easier question if the participant answers incorrectly. This adaptive approach ensures a tailored and efficient assessment experience, accurately measuring the participant's abilities. The research began by developing a valid and reliable language reasoning test instrument and its quadrant class. This included determining the starting, jumping, and stopping points, culminating in the CAT design. The results of the CAT proposed in this study can map basic language reasoning skills, starting from understanding the concept of facts, applying linguistic rules according to the agreement formed in the read clauses, breaking down information into more specific forms, judging the values of ideas, combining word selection, ideas formation, and context, analogy thinking, and comparative thinking. The analysis revealed that the participants' dominant ability was in comparative thinking, which involves comparing language forms, conditions, settings, and messages in written discourse. Moreover, the CAT system proposed in this study was proven to speed up the testing process while enabling students to complete the tests according to their abilities.