Data Mapping using Combining Clustering Methods and C.45 Classification

Robbi Rahim, Robbi and Unik Hanifah Salsabila, Salsabila and Akhmad Anwar Dani, Anwar Dani and Eka Maya S.S. Ciptaningsih, Maya and M. Mohzana, Mohzana (2023) Data Mapping using Combining Clustering Methods and C.45 Classification. International Journal of Electronics and Communication Engineering, 10. pp. 96-104. ISSN 2348-8549

Text (Jurnal (Turnitin)) 45. Scopus Q4-Turnitin-Data Mapping using Combining Clustering Method-SUDAH PUBLISH.pdf - Submitted Version Download (1MB)

Abstract

School participation is measured by the Pure Participation Rate (APM). This study examines whether data mining can generate new knowledge. The Central Sumatra Statistic Central Agency (BPS-North Sumatra) provided secondary statistics on APM by city/district (2011–2019) for elementary, junior high, high school, and PT. Data mining uses clustering (k-means) and classification (Decision tree). This cluster maps the APM. Mapping clusters are utilized again for categorization. Cluster value ranges indicate classification. C1 was the high APM cluster, and C2 was the low APM cluster. RapidMiner aids processing. The study found 18 high-cluster (C1) cities and 15 low-cluster cities (C2). Based on the clustering results obtained, classification results show that SMA and PT become influential attributes in mapping the area based on the Decision tree method, resulting in 3 rules: if SMA has a percentage <68,085% (high cluster); if SMA has a percentage> 68,085% and PT has a presentation <18,730% (low cluster); and if SMA and PT have a presentation> 18,730%. (high cluster). Classification and clustering have yielded new data. Keywords - Classification, Data mining, North sumatra, Pure participation.

Item Type:	Article
Subjects:	Pendidikan dan Pembelajaran > Evaluasi Pembelajaran Pendidikan dan Pembelajaran > Media Pembelajaran
Divisions:	Fakultas Bahasa, Seni, dan Humaniora > Pendidikan Bahasa dan Sastra Indonesia
Depositing User:	Mohzana Drs.Mohzana
Date Deposited:	03 Feb 2025 17:08
Last Modified:	03 Feb 2025 17:08
URI:	http://eprints.hamzanwadi.ac.id/id/eprint/5896

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