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All Journal Journal of Information System and Computer Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Muhammad Roiful Anam
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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OPTIMALISASI PENJADWALAN KULIAH MENGGUNAKAN ALGORITMA GENETIKA UNTUK MENINGKATKAN EFISIENSI JADWAL PADA PROGRAM STUDI SISTEM INFORMASI UNISNU JEPARA Nuradira, Afrida Hilda; Muhammad Roiful Anam; Leni Amrita; Maulidya Zumrotul Izzati; Heru Saputro
Journal of Information System and Computer Vol. 4 No. 2 (2024): Desember 2024
Publisher : Universitas Islam Nahdlatul Ulama Jepara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34001/jister.v4i2.1220

Abstract

The scheduling process in higher education is a complex challenge because it involves time allocation, space management, and human resources. In the UNISNU Jepara Information Systems Study Program, problems such as schedule clashes, uneven distribution of lecturer workloads, and inefficient classroom utilization often occur due to the increasing number of students and variety of courses. This research proposes the application of genetic algorithm as an optimization solution due to its ability to handle problems with various constraints and produce near-optimal solutions through the process of selection, crossover, and mutation. This research includes three main stages: data collection, genetic algorithm implementation, and result evaluation. Data was obtained from academic administration documents, including class schedules, course instructors, and classroom capacity. The evaluation results show that the genetic algorithm is able to reduce schedule conflicts, improve lecturer time efficiency, and maximize the use of classrooms. In conclusion, the application of genetic algorithms not only solves technical problems in scheduling, but also contributes to the development of a modern and adaptive academic information system, supports more effective decision-making, and ensures a smoother teaching-learning process in a college environment.
QnA Chatbot with Mistral 7B and RAG method: Traffic Law Case Study Muhammad Roiful Anam; Agus Subhan Akbar; Heru Saputro
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 15 No. 03 (2024): Vol. 15, No. 03 December (2024)
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i03.p06

Abstract

Mistral 7B is a language model designed to achieve high efficiency and performance in handling Natural Language Processing (NLP). This research will evaluate the model's effectiveness in legal data processing using the Retrieval-Augmented Generation (RAG) method, focusing on road traffic and transportation law No 22/2009. The system was built using the LangChain framework, followed by fine-tuning the model and evaluated using BERTScore. Results showed that the fine-tuned Mistral 7B achieved an F1 score of 0.9151, higher than the version without fine-tuning (0.8804) and GPT-4 (0.8364). To improve accuracy, the model utilizes specific keywords that make it easier to find relevant data. Fine-tuning was shown to enhance precision, while the use of key elements in questions helped the model focus more on important information. The results are expected to support the development of artificial intelligence (AI) in Indonesia's legal system and provide practical guidance for applying AI technology in other areas of law.
Co-Authors Agus Subhan Akbar Heru Saputro Leni Amrita Maulidya Zumrotul Izzati Nuradira, Afrida Hilda