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ANALISA ALGORITMA NAÏVE BAYES, J48, DAN KSTAR UNTUK KLASIFIKASI WARNA

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ABSTRACT ANALYSYS NAÏVE BAYES, J48, AND KSTAR ALGORITHM FOR COLOUR CLASSFICATION FRITZ MERCYANO FANIEL NIM : 1181002 Data mining techniques (Data Mining) is a mining or the new techniques discovery of information to look for patterns or particular rules of a number of large amounts of data. The mining data can be used to search for data in columns RGB (Red Green Blue) to classify the colors. RGB (Red Green Blue) is a color model that consists of three colors such as red, Green, and Blue. RGB is a model color that relies on the appliance. There are three algorithms used to classify color, that naïve Bayes, J48, and Kstar. The three algorithms will predict the value of truth in the form of a percentage of an RGB data. The predictive value must be fullfill the requirements numbers that has been specified. The purpose of this analysis is to determine which of the three algorithms have the most optimal predictive value (accurate) to be able to classify the color well. The results obtained after the analysis was the algorithm Kstar has very accurate prediction results compared with naïve Bayes algorithm and J48. The prediction results of Kstar value algorithm was very accurate, so the algorithm highly optimized to clasify Kstar color. Then to conduct further research is recommended to use the kstar algorithm . Key Words: Data mining, RGB, Naïve Bayes, J48, KStar