Penerapan Algoritma K-Means Clustering Dalam Persentase Merokok Pada Penduduk Umur Di Atas 15 Tahun Menurut Provinsi
DOI:
https://doi.org/10.30865/json.v2i2.2770Keywords:
Data Mining, Clustering, K-means, Percentage of Smoking, RapidMinerAbstract
This research aims to determine the number of people who are smoking the age of 15 years by applying Data Mining. The application uses the K-means algorithm where the data entered is the percentage of smoking. Using this method the data obtained can be grouped into 2 klasters. This research uses secondary data that is obtained from intermediate media that is recorded on the site of the Central Statistics website with the URL address https://www.bps.go.id/. The results gained in this study are grouping the number of smoking percentages that are grouped by as many as 2 klasters is klaster 1 (highest klaster) to get results 22 provinces and klaster 2 (lowest klaster) get 12 provinces.References
S. R. Ningsih, I. S. Damanik, A. P. Windarto, H. S. Tambunan, J. Jalaluddin, and A. Wanto, “Analisis K-Medoids Dalam Pengelompokkan Penduduk Buta Huruf Menurut Provinsi,†Pros. Semin. Nas. Ris. Inf. Sci., vol. 1, no. September, p. 721, 2019.
E. Buulolo, Data Mining Untuk Perguruan Tinggi. Deepublish, 2020.
I. W. S. Wicaksana, D. Aprilia, D. A. Baskoro, and Liat Ambarwati, “Belajar Data Mining Dengan Rapid Minner,†p. 139, 2013.
K. U. Pengelompokkan, K. Kota, M. W. Talakua, Z. A. Leleury, and A. W. Talluta, “ANALISIS CLUSTER DENGAN MENGGUNAKAN METODE PROVINSI MALUKU BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA TAHUN 2014 CLUSTER ANALYSIS BY USING K-MEANS METHOD FOR GROUPING OF DISTRICT / CITY IN MALUKU PROVINCE INDUSTRIAL BASED ON INDICATORS OF MALUKU DEVELOPMENT INDEX IN 2014,†vol. 11, pp. 119–128, 2017.
R. A. Malik, S. Defit, and Y. Yuhandri, “Comparison of K-Means Clustering Algorithm with Fuzzy C-Means In Measuring Satisfaction Level Of Television Da’wah Surau TV,†Rabit, vol. 3, no. 1, pp. 10–21, 2018.
I. Parlina, A. P. Windarto, A. Wanto, and M. R. Lubis, “MEMANFAATKAN ALGORITMA K-MEANS DALAM MENENTUKAN PEGAWAI YANG LAYAK MENGIKUTI ASESSMENT CENTER UNTUK CLUSTERING PROGRAM SDP,†CESS (Journal Comput. Eng. Syst. Sci., vol. 3, no. 1, pp. 87–93, 2018.
G. Prasetya, “PENGARUH PENDIDIKAN, PELATIHAN, JENIS KELAMIN, UMUR, STATUS PERKAWINAN, DAN DERAH TEMPAT TINGGAL TERHADAP LAMA MENCARI KERJA TENAGA KERJA TERDIDIK DI INDONESIA,†vol. 10, no. 2, pp. 1–15, 2018.
