ALGORITMA ITERATIVE DICHOTOMISER 3 (ID3) UNTUK MENGIDENTIFIKASI DATA REKAM MEDIS (Studi Kasus Penyakit Diabetes Mellitus Di Balai Kesehatan Kementerian Perindustrian, Jakarta)

Avia Enggar Tyasti, Dwi Ispriyanti, Abdul Hoyyi

Abstract


Iterative Dichotomiser 3 (ID3) Algorithm is a basic decision tree learning algorithm. These algorithms perform a thorough search (greedy) in all possible decision tree. ID3 algorithm can be implemented using a recursive function, (function that calls itself). One of the problems that can be solved using the ID3 algorithm is a classification of diabetic patients. Diabetic is a disease because of the body is not able to control the amount of sugar or glucose in the bloodstream. Classification using ID3 in the case of diabetics produce trees with many vertices to 32 knot where 21 of them is a leaf node and attribute two-hour postprandial glucose fasting elected as the root node in the decision-making tree. Based on the classification performance measurements show that the classification accuracy or measurement accuracy reaches 89,75%. While the measurement accuracy of the classification algorithm ID3 using test samples totaling 84 samples showed an accuracy of 72,619%.

 

Keywords: ID3 Algortihm, Decision Tree, Diabetes

ALGORITMA ITERATIVE DICHOTOMISER 3 (ID3) UNTUK MENGIDENTIFIKASI DATA REKAM MEDIS

(Studi Kasus Penyakit Diabetes Mellitus Di Balai Kesehatan Kementerian Perindustrian, Jakarta)

Keywords


ID3 Algortihm, Decision Tree, Diabetes

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