Pemanfaatan Algoritma K-Means untuk Pengelompokkan Pasien Penyakit Infeksi Saluran Pernafasan Akut (ISPA)
DOI:
https://doi.org/10.54259/satesi.v2i1.804Kata Kunci:
Data Mining, ISPA, Bah Biak, Pengelompokkan, PuskesmasAbstrak
Penelitian ini membahas tentang Penyakit Infeksi Saluran Pernafasan Akut (ISPA) pada Puskesamas Bah Biak. Puskesmas Bah Biak merupakan salah satu puskesmas yang ada di Marihat di kota Pematangsiantar. Setiap harinya jumlah pasien yang datang dan melakukan perawatan medis di puskesmas ini cukup banyak. Tingginya jumlah kunjungan pasien pada puskesmas ini menyebabkan jumlah data rekam medis menjadi sangat banyak pula. Selama ini data yang berisi informasi mengenai pasien di puskesmas belum dimanfaatkan dengan baik. Informasi tersebut sebenarnya dapat dijadikan suatu pengetahuan bagi puskesmas, khususnya bagi pasien yang memiliki riwayat penyakit ISPA. Oleh sebab itu tujuan penelitian ini untuk mengelompokkan pasien penyakit ISPA pada Puskesmas tersebut. Metode yang digunakan adalah K-Means klustering. Hasil penelitian ini mampu mengelompokkan pasien penyakit ISPA ke dalam 2 kluster, kluster 1 memberikan rekomendasi tinggi berjumlah 72 Pasien, dan kluster 2 memberikan rekomendasi rendah berjumlah 70 Pasien. Proses kluster berhenti pada data iterasi ke 5. Berdasarkan proses perhitungan manual dengan menggunakan Ms. Excel dan pengujian dengan menggunakan Rapidminer 5.3, menghasilkan nilai yang sama. Dapat disimpulkan bahwa untuk kasus ini, algoritma K-Means dapat pengelompokkan pasien penyakit ISPA yang ada di puskesmas Bah Biak dengan baik
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