PERBANDINGAN METODE K-MEANS EUCLIDEAN DISTANCE DAN MANHATTAN DISTANCE PADA PENENTUAN ZONASI COVID-19 DI KABUPATEN MALANG
نویسندگان
چکیده
Coronavirus (Corona Virus Desease) atau yang biasa disebut Covid-19 ini adalah sebuah penyakit sangat berbahaya. Banyaknya jumlah kasus tercatat di Kabupaten Malang membuat pemerintah dituntut untuk membagi Zonasi wilayah pada setiap Kecamatan agar dapat kebijakan peraturan ditaati oleh zona-zona tertentu. K-Means algoritma mengelompokkan data berdasarkan titik pusat klaster (Centeroid) paling dekat dengan tersebut (Metisen & Sari, 2015). bertujuan memaksimalkan kesamaan dalam dan meminimalkan antar (Asroni Adrian, Kualitas hasil Clustering lebih baik dari Euclidean Distance Manhattan metode diharapkan menentukan Malang. Metode memperoleh nilai Silhouette Coefficient Standart Deviasi perbandingan 0,71 > 0,64 0,46466002 < 0,4961977.
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ژورنال
عنوان ژورنال: JATI (Jurnal Mahasiswa Teknik Informatika)
سال: 2022
ISSN: ['2598-828X']
DOI: https://doi.org/10.36040/jati.v6i2.4808