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CLASSIFICATION OF ASSISTANCE RECIPIENTS USING THE ALGORITHM C4.5

Diana Santi(1), Siti Aisyah(2), Asep Afandi(3), Dwi Marisa(4),


(1) Information Systems Study Program, Institut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia Kotabumi
(2) Information Systems Study Program, Institut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia Kotabumi
(3) Information Systems Study Program, Institut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia Kotabumi
(4) Information Systems Study Program, Institut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia Kotabumi
Corresponding Author

Abstract


Poverty is a condition that results in an inability to meet basic needs such as housing, food, education, and health. Based on data from the Central Statistics Agency (BPS), the number of poor people in Indonesia in September 2019 was 24.79 million. To minimize social welfare problems, especially the problem of increasing poverty, the Government of Indonesia issued policies related to empowering poor families. The government policy is the Family Hope Program (PKH), but the Implementation of the Family Hope Program (PKH) has not been implemented on target. This has resulted in social jealousy between residents in the community [1], one of the villages where PKH assistance distribution is still not on target is Gilih Suka Negeri Village. Gilih Suka Negeri Village is one of the areas in Lampung Province, North Lampung Regency, South Abung District, which has a total of 7 RTs (RTs) with a population of approximately 1,776 people. The author chose algorithm method C4.5 (Decision Tree) because it can be used as a solution to determine the classification of beneficiaries. Algorithm C4.5 (Decision Tree) will classify beneficiaries of the Family Hope Program (PKH) based on how much they earn, where they live, and how many people they have in their household

Keywords


Algorithm C4.5, Data Mining, Python, Family Hope Program

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DOI: 10.56327/jurnaltam.v14i2.1527

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