Pemanfaatan Algoritma K-Means untuk Pengelompokkan Angka Partisipasi Sekolah di Jawa Tengah

Authors

  • Jati Sumarah Politeknik Dharma Patria, Kebumen, Jawa Tengah
  • Ajeng Tiara Wulandari Politeknik Dharma Patria, Kebumen, Jawa Tengah

DOI:

https://doi.org/10.30865/mib.v5i4.3277

Keywords:

APS, Central Java, Data Mining, K-Means, Clustering

Abstract

In Indonesia, the School Participation Rate (APS) is recognized as one of the indicators of the success of developing education services in regions, whether Province, Regency, or City. The higher the rate of school enrollment, the more successful an area is at providing access to educational services. The dataset was obtained from the Central Statistics Agency (BPS) of Central Java Province's website. The object studied is the percentage of APS in the Central Java region from 2017 to 2019 for ages 7 to 12, 13 to 15, and 16 to 18. The study's goal was to conduct an analysis in the form of mapping the School Participation Rate in the districts and cities of Central Java, the third most populous province after West and East Java. RapidMiner software is used in the analysis process. The research output is a map of clusters of areas in the Regency and City areas. The k-means method, which is part of clustering data mining, is the solution method offered. The number of mapping clusters in this study was divided into two categories: high (C1) and low (C2) clusters. According to the study's findings, the mapping of the 7-12 year old cluster was 24 provinces in the high cluster (cluster 0) and 11 provinces in the low cluster (cluster 1); the mapping of the 13-15 year old cluster is 23 provinces in the high cluster (cluster 0) and 12 provinces in the low cluster (cluster 1); and the mapping of the 16-18 year old cluster is 15 provinces in the low cluster (cluster 1). Cluster determination is based on the final centroid value, with the final centroid value of the 7-12 year old cluster being high (cluster 0) 99.81, 99.87, 99.75; low (cluster 1) 99.73, 99.43, 99.25; and the centroid value of the 13-15 year old cluster being high (cluster 0) 97.52, 97.12, 96.93; low (cluster 1) 93.78, 93.58 Overall, the mapping results show a high percentage for all age groups, which is greater than 50% in the high cluster. In detail, 24 provinces (57 percent) are in the low cluster for the 16-18 year age group. The research findings can provide a macro picture of the level of development of the School Enrollment Rate over the last few years

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Published

2021-10-26

Issue

Vol. 5 No. 4 (2021): Oktober 2021

Section

Articles

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