Implementasi Algoritma K-Means untuk Pengelompokan Penyakit Pasien Pada Puskesmas Warujayeng

Authors

  • Ulil Ma’rifatin Univ. Nusantara PGRI Kediri Indonesia

DOI:

https://doi.org/10.29407/inotek.v4i1.211

Abstract

Dalam menentukan konsistensi data kesehatan, dapat menggunakan teknik penambangan data yang dapat menggali informasi tersembunyi dart data set yang telah diperoleh. Selain itu, data yang terhubung dengan data lain juga dapat dilakukan dengan teknik penambangan data ini. Salah satu teknik penambangan data yang cukup terkenal yaitu clustering. Metode ini cukup populer dalam teknik penambangan data yang disebut metode k-means. Ini digunakan untuk memfasilitasi perekam medis untuk menganalisis situasi kesehatan umum kelompok populasi dalam pengarsipan data perawatan kesehatan. Hasil analisis ini, pengelompokan penyakit berdasarkan usia, jenis kelamin, durasi penyakit dan diagnosis penyakit. Penelitian ini menggunakan alat Rapid Miner 5.3. Berdasarkan data dari puskesmas Warujayeng, hasil pengelompokan ini adalah 376 item akut. dan 624 penyakit tidak akut dari 1000 total data.

Keywords:

Clustering, Data Mining, K-Means

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References

Wallace, V. P., Bamber,J. C. dan Crawford, D. C. 2000. Classification of reflectance spectra from pigmented skin lesions, a comparison of multivariate discriminate analysis and artificial neural network. Journal Physical Medical Biology. No.45. Vol.3. 2859-2871.

Yusoff, M. Rahman, S.,A., Mutalib, S., and Mohammed, A. 2006 Diagnosing Application Development for Skin Disease Using Backpropagation Neural Network Technique. Journal of Information Technology. vol 18. hal 152-159.

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Published

2020-12-17

Issue

Vol. 4 No. 1 (2020): PROSIDING SEMNAS INOTEK Ke-IV Tahun 2020

Section

Articles

License

Copyright (c) 2020 Ulil Ma’rifatin

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How to Cite

Implementasi Algoritma K-Means untuk Pengelompokan Penyakit Pasien Pada Puskesmas Warujayeng. (2020). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 4(1), 285-291. https://doi.org/10.29407/inotek.v4i1.211