IMPLEMENTASI RAPIDMINER DENGAN METODE K-MEANS (STUDY KASUS: IMUNISASI CAMPAK PADA BALITA BERDASARKAN PROVINSI)

 (*)Riyani Wulan Sari Mail (STIKOM Tunas Bangsa, Pematangsiantar, —)
 Anjar Wanto (STIKOM Tunas Bangsa, Pematangsiantar, —)
 Agus Perdana Windarto (STIKOM Tunas Bangsa, Pematangsiantar, —)

(*) Corresponding Author

Abstract

Measles is one of the causes of death in children around the world which always increases every year. Although measles immunization programs have been implemented, the incidence of measles in children is still quite high. This study discusses the Implementation of Rapidminer with the K-Means Method (Case Study: Measles Immunization in Toddlers by Province). The increase in cases of measles in toddlers in Indonesia is a case that has never been separated from the government's attention. Data sources and research were obtained from the Central Statistics Agency (BPS). The data used in this study are data from 2004-2017 which consists of 34 provinces. The cluster process is divided into 3 (three) clusters, namely high cluster level (C1), medium cluster level (C2) and low cluster level (C3). So that the assessment for cases of immunization against measles based on high cluster province (C1) is 21 provinces for medium cluster (C2) of 12 provinces and for low cluster (C3) of 1 province. The results of the cluster can be used as input for the government, especially the provinces, so that provinces that enter the high cluster receive more attention and increase the socialization of measles immunization against children under five.

 Keywords: Data Mining, Measles, Clustering, K-means

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References

K. P. Juanda, “EFEKTIVITAS PELAKSANAAN PROGRAM IMUNISASI CAMPAK Kata Kunci : Efektivitas Program , Program Imunisasi Campak,” vol. 5, pp. 6409–6420, 2017.

H. N. Rosalina, D. E. Wijayanti, and R. Caturiningsih, “Jurnal Kesehatan Dan Kebidanan ( Journal of Midwifery and Health ),” J. Kesehat. dan kebidanan, pp. 64–70, 2015.

L. Mafulla Rahmayanti, “Hubungan Status Imunisasi Campak Dan Perilaku Pencegahan Penyakit Campak Dengan Kejadian Campak Pada Bayi Dan Balita Di Puskesmas Kabupaten Bantul Tahun 2013-2014,” 2015.

A. P. Windarto, “Penerapan Data Mining Pada Ekspor Buah-Buahan Menurut Negara Tujuan Menggunakan K-Means Clustering,” Techno.COM, vol. 16, no. 4, pp. 348–357, 2017.

M. G. Sadewo, A. P. Windarto, and D. Hartama, “PENERAPAN DATAMINING PADA POPULASI DAGING AYAM RAS PEDAGING DI INDONESIA BERDASARKAN PROVINSI MENGGUNAKAN K-MEANS CLUSTERING,” InfoTekJar (Jurnal Nas. Inform. dan Teknol. Jaringan), vol. 2, no. 1, pp. 60–67, 2017.

A. P. Windarto, “Implementation of Data Mining on Rice Imports by Major Country of Origin Using Algorithm Using K-Means Clustering Method,” Int. J. Artif. Intell. Res., vol. 1, no. 2, pp. 26–33, 2017.

Sumijan, A. P. Windarto, A. Muhammad, and Budiharjo, “Implementation of Neural Networks in Predicting the Understanding Level of Students Subject,” Int. J. Softw. Eng. Its Appl., vol. 10, no. 10, pp. 189–204, 2016.

M. N. H. Siregar, “Neural Network Analysis With Backpropogation In Predicting Human Development Index ( HDI ) Component by Regency / City In North Sumatera,” I n t e r n a t i o n a l Jo u r n a l O f I n f o r m a t i o n S yst e m T e c h n o l ogy, vol. 1, no. 1, pp. 22–33, 2017.

Solikhun, A. P. Windarto, Handrizal, and M.Fauzan, “Jaringan Saraf Tiruan Dalam Memprediksi Sukuk Negara Ritel Berdasarkan Kelompok Profesi Dengan Backpropogation Dalam Mendorong Laju Pertumbuhan Ekonomi,” Kumpul. J. Ilmu Komput., vol. 4, no. 2, pp. 184–197, 2017.

A. P. Windarto, L. S. Dewi, and D. Hartama, “Implementation of Artificial Intelligence in Predicting the Value of Indonesian Oil and Gas Exports With BP Algorithm,” Int. J. Recent Trends Eng. Res., vol. 3, no. 10, pp. 1–12, 2017.

A. P. Windarto, “IMPLEMENTASI JST DALAM MENENTUKAN KELAYAKAN NASABAH PINJAMAN KUR PADA BANK MANDIRI MIKRO SERBELAWAN DENGAN METODE BACKPROPOGATION,” J-SAKTI (Jurnal Sains Komput. dan Inform., vol. 1, no. 1, pp. 12–23, 2017.

A. Putrama and A. P. Windarto, “Analisis dalam menentukan produk bri syariah terbaik berdasarkan dana pihak ketiga menggunakan ahp,” CESS (Journal Comput. Eng. Syst. Sci., vol. 3, no. 1, pp. 60–64, 2018.

P. P. P. A. N. W. F. I. R. H. Zer and A. P. Windarto, “Analisis Pemilihan Rekomendasi Produk Terbaik Prudential Berdasarkan Jenis Asuransi Jiwa Berjangka Untuk Kecelakaan Menggunakan Metode Analytic Hierarchy Process ( Ahp ),” CESS (Journal Comput. Eng. Syst. Sci., vol. 3, no. 1, pp. 78–82, 2018.

D. R. Sari, A. P. Windarto, D. Hartama, and S. Solikhun, “Sistem Pendukung Keputusan untuk Rekomendasi Kelulusan Sidang Skripsi Menggunakan Metode AHP-TOPSIS,” J. Teknol. dan Sist. Komput., vol. 6, no. 1, p. 1, 2018.

A. P. Windarto, “Penilaian Prestasi Kerja Karyawan PTPN III Pematangsiantar Dengan Metode Simple Additive Weighting (SAW),” J. Ris. Sist. Inf. Dan Tek. Inform., vol. 2, no. ISSN 2527-5771, pp. 84–95, 2017.

T. Imandasari and A. P. Windarto, “Sistem Pendukung Keputusan dalam Merekomendasikan Unit Terbaik di PDAM Tirta Lihou Menggunakan Metode Promethee,” J. Teknol. dan Sist. Komput., vol. 5, no. 4, p. 159, 2017.

D. Hartama, “MODEL ATURAN KETERHUBUNGAN DATA MAHASISWA MENGGUNAKAN ALGORITMA C 4.5 UNTUK MENINGKATKAN INDEKS PRESTASI,” 2011.

M. Ridwan, H. Suyono, and M. Sarosa, “Penerapan Data Mining Untuk Evaluasi Kinerja Akademik Mahasiswa Menggunakan Algoritma Naive Bayes Classifier,” Eeccis, vol. 7, no. 1, pp. 59–64, 2013.

J. Informatika, W. Mega, and P. Dhuhita, “CLUSTERING MENGGUNAKAN METODE K-MEANS UNTUK,” vol. 15, no. 2, 2015.

A. K. Wardhani, “Implementasi Algoritma K-Means untuk Pengelompokkan Penyakit Pasien pada Puskesmas Kajen Pekalongan,” J. Transform., vol. 14, no. 1, pp. 30–37, 2016.

L. Teori, “( K-MEANS ALGORITHM IMPLEMENTATION FOR CLUSTERING OF PATIENTS DISEASE IN KAJEN CLINIC OF PEKALONGAN ) Anindya Khrisna Wardhani Magister Sistem Informasi Universitas Diponegoro,” vol. 14, pp. 30–37, 2016.

G. F. Mandias et al., “Penerapan Algoritma K-Means Untuk Analisis Prestasi Akademik Mahasiswa Fakultas Ilmu Komputer Universitas Klabat Application of K-Means Algorithm for Academic Achievement Analysis of Faculty of Computer Science Universitas Klabat,” pp. 230–239, 2017.

D. A. N. Prestasi and M. Lalu, “DATA MINING UNTUK MEMPREDIKSI PRESTASI SISWA DATA MINING TO PREDICT STUDENT ’ S ACHIEVEMENT BASED ON SOCIO-ECONOMIC , MOTIVATION , DISCIPLINE AND,” vol. 4, pp. 222–231.

P. Soepomo, “PENERAPAN DATA MINING UNTUK KLASIFIKASI PREDIKSI PENYAKIT ISPA ( Infeksi Saluran Pernapasan Akut ) DENGAN ALGORITMA DECISION TREE ( ID3 ),” vol. 2, 2014.

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