Abstract

The “pick-up ball service” program or commonly called mobile services is a form of developing services for the Population and Civil Registration Service (disdukcapil), especially Alor NTT Regency, which aims to reach people who have difficulty getting services due to various obstacles, including due to long distances and difficult access to service centers. Disdukcapil is an implementing agency in the district that is obliged to ensure that all residents, both Indonesians and foreigners, are recorded in the population database, have a NIK, and population documents. In its implementation, not all villages can be served due to insufficient time and funds, so it is necessary to select villages that are worthy of being served by “ball pick up service” or mobile service programs. So far, the determination of villages that are worthy of the program is still determined manually so that it is inseparable from the element of subjectivity. In this study, a classification method was used in data mining using the naïve bayes algorithm. Naïve bayes is one of the algorithms that is able to predict well by calculating the probability of each class and comparing them, Naïve bayes is used to calculate probability values from training data so that it can predict which villages are feasible for the program. The study used 25 training data taken from previous dukcapil service data and data on the distance and difficulty of access to the village, which were tested and simulated using the naïve bayes algorithm of weka software. The purpose of this study was to obtain accurate information about the villages in Alor district that deserve the program. The results of the process using WEKA software found that from 25 tuples used as test data, it resulted in 100% accuracy .

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