IMPLEMENTATION OF DATA MINING CLASSIFICATION FOR DETERMINING THE TYPE OF SOCIAL ASSISTANCE USING THE NAÏVE BAYES CLASSIFIER METHOD
DOI:
https://doi.org/10.22303/csrid-.16.1.2024.13-24Keywords:
Data Mining, Classification, Naïve BayesAbstract
The social assistance program is a program held by the government as an effort to overcome poverty. Mekarjaya Village is one of the villages running the program. In carrying out this social assistance process, there are obstacles in terms of collecting data on its citizens because there are often discrepancies in the recipient data collected by the community with the type of assistance. To make it easier to determine the appropriate type of social assistance, an analysis of the data on the recipients of the social assistance is needed. The data analysis method in this research uses Data Mining including Data Selection and Preprocessing, while the classification method uses the Naïve Bayes Classifier. Testing using the Confusion Matrix produces an accuracy of 94.53% with a comparison of training data and testing 80:20. With this model, it is hoped that village officials can determine the type of social assistance that is appropriate for the community.
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