Sistem Pendukung Keputusan Penerima Beasiswa Program Indonesia Pintar Menggunakan Metode Algoritma K-Means Clustering
DOI:
https://doi.org/10.30865/jurikom.v9i2.3971Keywords:
Poverty, Data Mining, Clustering, K-Means Algorithm, the Program Indonesia PintarAbstract
SDN 020 PPU is one of the elementary schools that receive scholarships from the Program Indonesia Pintar (PIP) every year. The Smart Indonesia Program is a collaboration of three ministries of Kementerian Pendidikan dan Kebudayaan (Kemendikbud), the Kementerian Sosial (Kemensos), and the Kementerian Agama (Kemenag). Program Indonesia Pintar is designed to help school-age children from poor/vulnerable/poor priority families continue to receive education services until they finish secondary education, either through formal education (starting from SD/MI to graduating from SMA/SMK/MA) through this program the government seeks to prevent students from the possibility of dropping out of school, and is expected to attract dropouts to return to continue their education. Based on the results of the evaluation of the implementation of data processing, there are problems in distributing scholarships because there are often complications in proposing the eligibility of scholarship recipients. With these problems, a decision support system is needed to assist the school in determining scholarship recipients using the k-Means clustering algorithm method using Rapidminer studio version 9.10. This study uses 236 student data at SDN 020 PPU which consists of 5 research variables, namely Name, Number of Dependent Parents, Report Value, Occupation and Total Income of Parents. Based on the results of data processing, there are 70 data including cluster 1 with scholarship recipient status right on target, then 118 data including cluster 1 with scholarship recipient status not being targeted. and 48 data belonging to cluster 2 with scholarship recipient status not on targetReferences
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