Jurnal
Analysis of the K-Means Algorithm on Clean Water Customers Based on the Province
- Bagikan:
One of the important needs of environmental health is clean water. Clean water is
the most important necessity of living beings in supporting survival. The study aimed to cluster
the number of cleaned water customers by province (1995-2015). The method used is data
mining clustering using k-means. The sample data used 34 provinces with attribute assessment
of the number of cleaned water customers by province. The clustering process is done with 3
clusters, namely (C1) Cluster High, (C2) Cluster Normal and (C3) Cluster Low, for the number
of cleaned water customers who are low on the need of clean water. The results showed, C1: 6
provinces, C2: 4 provinces and C3: 24 provinces. The end centroid values used are: C1
(296587.22), C2 (995898.56) and C3 (70832.29). The results obtained on the Davies-Bouldin
index for "the number of cleaned water consumers" are -0.470. based on performance results, it
can be concluded that k-means algorithm is best because it has the smallest Davies-Bouldin
index value. Based on research results, 70% of Indonesian people are still low awareness of the
need for clean water.
Detail Information
| Item Type |
Jurnal
|
|---|---|
| Penulis |
Yoyon Efendi - Personal Name
Agus Perdana Windarto - Personal Name Muhammad Noor Hasan Siregar - Personal Name Wildan Suharso - Personal Name Barany Fachri - Personal Name Adi Supriyatna - Personal Name Irmawati Carolina - Personal Name Dafwen Toresa - Personal Name |
| Student ID | |
| Dosen Pembimbing | |
| Penguji | |
| Kode Prodi PDDIKTI | |
| Edisi |
Published
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| Departement | |
| Kontributor | |
| Bahasa |
English
|
| Penerbit | IOP Publishing : Parapat., |
| Edisi |
Published
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| Subyek | |
| No Panggil | |
| Copyright |
IOP Publishing
|
| Doi |