Rancang Bangun Sistem Klasifikasi Frekuensi Penggunaan Minyak Goreng dengan Menggunakan Metode Bayes - M Nuzulul Marofi; Dahnial Syauqy; Hurriyatul Fitriyah (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2017)
The use of cooking oil repeatedly and beyond the normal limits (waste cooking oil) can cause variety of dangerous diseases to human health such as heart failure, high risk of diabetes, coronary heart disease, and others. However, the use of waste cooking oil is still high today. This is shown from the results of research in Makassar which is poor and rich people use the same cooking oil for frying as much as 61.2 percent use it twice, 19.6 percent use it three times, and 5.4 percent use it as four time. Based on the problem, it is necessary to have an automation system for classifying the frequency of the using cooking oil, so it can be used for the frequency classification of the use of cooking oil that has been used several times (waste cooking oil) accurately. In this study, the parameters used are the color and turbidity level of cooking oil. Determination of cooking oil classification is based on color and turbidity level of oil obtained from TCS3200 color sensor readings and sensor photodiode by Arduino Uno microcontroller by using Bayes methods. This method is chosen because it is one of the classification method that is quite simple, easy to understand, and has high computing speed. From the results of the tests performed, it is known the percentage error reading TCS3200 color sensor is 1.9% and photodiode sensor can work well. So, if the cooking oil is more turbid, the value of the photodiode sensor is smaller. Furthermore, the test system using Bayes methods with the amount of training data is 65 data and test data is 35 data obtained an accuracy of 71.42% with a system of computing time on average over 13.144 seconds.