Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Alfan Nazala Putra
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Sistem Deteksi Kerusakan Mesin Pada Sepeda Motor Menggunakan Naive Bayes - Certainty Factor Alfan Nazala Putra; Nurul Hidayat; Suprapto Suprapto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1020.7 KB)

Abstract

Nowadays, motorcycle is no longer a luxury item for most people. Almost the whole community at least had motorcycle. Motorcycle became one of the main means of transportation which more dynamic and faster compared to other means of transport, and this is provable by the large number of motorcyclists compared to another user of transportation means on the road. Not surprising that motorcycle is the largest cause for accident in traffic. One of the causes of the accident on a motorcycle is from motorcycle engines. But as most motorcyclist are still much less savvy about the damage to their motorcycle engines because there are various kind of failure. A method of classification can be implemented into the software to know which part of motorcycle engines that get damaged or failure. One example is the Naive Bayes. Naive Bayes Classifier is a simple probability classification based on Bayes theorem which has Bayes inference in general, especially with a strong independence of assumptions. The theory of certainty using a value called the Certainty Factor (CF) to assume a degree of confidence to a data. The variable used in this study is a list of symptoms and damage to motorcycle engines. Highest accuracy resulting in this research is 90%.
Co-Authors Nurul Hidayat Supraptoa Supraptoa