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All Journal JURNAL SISTEM INFORMASI BISNIS JOIV : International Journal on Informatics Visualization Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri Techno Nusa Mandiri : Journal of Computing and Information Technology Journal of Information Systems and Informatics Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Abditeknika - Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem Informasi Akuntansi SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Media Computer Science Paradigma Indonesian Journal Computer Science (ijcs) Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial
Galih Setiawan Nurohim
Universitas Bina Sarana Informatika
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health

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Journal : JOIV : International Journal on Informatics Visualization

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Knowledge-Based Intelligent System for Diagnosing Three-Wheeled Motorcycle Engine Faults Ary Setyadi, Heribertus; Supriyanta, Supriyanta; Nurohim, Galih Setiawan; Widodo, Pudji; Sutanto, Yusuf
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2487

Abstract

Three-wheeled motor engine damage is one of the most serious problems with all motorcycles. When problems appear, it becomes difficult for users to repair and diagnose faults because knowledge about machine breakdown symptoms is minimal. Most motorcycle repair shops don’t have mechanics who understand tricycle motorbike engines, so they are less accurate in diagnosing damage symptoms, only based on estimates. Three-wheeled motorbikes have several differences in structure and spare parts compared to motorcycles because tricycle motorbikes have an axle like a car. For this problem, an information system is needed with a method that combines an expert's experience, expertise, and knowledge to develop expert system applications based on several cases that have been experienced and are known as case-based reasoning. This research aims to produce a web-based expert system to diagnose and solve tricycle motorbike engine damage problems. The case-based reasoning method with the K-Nearest Neighbor algorithm is used to assist in analyzing engine damage and give solutions to the issues in three-wheeled motorbike engines. Using two methods is appropriate because of the answers found and the similarities calculated by the cosine similarity method, which experts then review to get the proper solution. From testing using 20 samples of diagnostic data, an accuracy percentage of 85% was obtained. The calculation result for precision is 85%, and recall is 85%.
Co-Authors Ahmad Fauzi Ahmad Fauzi Akbar, Muhammad Faitullah Al Amin, Budi Amin, Budi Al Budi Al Amin Candra Agustina Diah Pradiatiningtyas Doddy Satrya Perbawa eka rahmawati Fauzi Ahmad Muda Fauzi, Ahmad Heribertus Ary Setyadi Muhammad Faittullah Akbar Nugroho, Wawan Pudji Widodo Setyadi, Heribertus Ary Setyadi Siti Khotimah Sundari Sundari Supriyanta Supriyanta Sutanto Sutanto Wahyuningsih, Hartati Dyah Wati, Fanny Fatma Wawan Haryanto Wawan Nugroho Yusuf Sutanto