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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Mustajib Furqon Haqiqi
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Sistem Pengecek Kelayakan Pakai Oli Motor Matic Berdasarkan Parameter Warna dan Viskositas Menggunakan Metode Bayes Mustajib Furqon Haqiqi; Dahnial Syauqy; Issa Arwani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Lubricating oil on engine motorcycle is an important component of a vehicle as a means of transport. When oil is replaced, then the late effect on performance and condition of the machine motor. And most of the community if you want to check the condition of his motorcycle oil has to come to the repair shop if you want to check or replace the oil in the motor. The use of oil lubrication parameters as objects of research,. study on the parameters used to perform the comparison level of lubricant lubricant oil is color and viscosity on the oil of motorcycle. The use of lubricating oil parameter as an object of research due to the condition of the lubricant oil is very influential on the condition of the machine that is on the motor. The process of determining eligibility levels oil through color and viscosity of the oil obtained from the reading of the result value of the color sensor TCS3200 sensor and Water Flow YF-S201 by microcontroller, Arduino Uno with Naive Bayes method. Naive Bayes method is selected as one of the techniques for decision making types of lubricating oil eligibility levels, because this method was one method of classification is good enough where classes classification of types of eligibility levels have been known from the beginning. From the results of some tests done known percentage error reading sensor TCS3200 is color of 2.22% and the value of the correlation of readings the sensors Water flow YF-S201 by function it works can differentiate liquid based on the kind of lumpy. Next on the testing system using Naive Bayes method with the amount of training data by as much as 35 data and test data as much as 18 data, obtained accuracy of 94.44% with average computing time over the 1.68 seconds.
Co-Authors Dahnial Syauqy Issa Arwani