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PENERAPAN DATA MINING UNTUK CLUSTERING DATA PENDUDUK MISKIN MENGGUNAKAN ALGORITMA K-MEANS
APPLICATION OF DATA MINING FOR POOR POPULATION DATA CLUSTERING USING K-MEANS ALGORITHM STUDY PROGRAM OF INFORMATICS ENGINEERING, STIKOM DB, 2018
Undergraduate Theses from gdlhub / 2019-05-18 14:59:40By : Dina Sunia, STIKOM Dinamika Bangsa Jambi
Created : 2019-05-18, with 7 files
Keyword : Data Mining, penduduk miskin, K-means
Sumber data dari BPS kota jambi Pada Maret 2017 jumlah penduduk miskin sebesar 286,55 ribu jiwa (8,19%), berkurang sebesar 4,26 ribu jiwa dibandingkan dengan penduduk miskin pada september 2016 yang sebesar 290,81 ribu jiwa (8,37%). Berdasarkan angka tersebut terlihat masih tingginya angka kemiskinan yang ada di wilayah Kota Jambi secara umum. Berdasarkan kondisi tersebut perlu dilakukan pengklasteran untuk membantu Dinas Sosial Kota Jambi dalam pengelompokan keluarga miskin sehingga bantuan dapat tersalurkan dengan tepat. Dengan mengamati persoalan diatas maka diperlukan Data Mining untuk mengelompokkan penerima bantuan dengan menggunakan metode K-Means dalam pengklasteran penduduk miskin. Hasil perhitungan menunjukkan, dari 512 sample data penduduk miskin di Kecamatan Jambi Selatan, dengan jumlah klaster sebanyak 5, dengan iterasi sebanya 3 diperoleh 13 penduduk masuk sebagai anggota klaster 1, 153 penduduk berada diklaster 2, 129 penduduk di klaster 3, 138 penduduk berada di klaster 4, dan 79 penduduk berada di klaster 5.
Description Alternative :Source of data from BPS in Jambi City In March 2017 the number of poor people was 286.55 thousand people (8.19%), a decrease of 4.26 thousand people compared to the poor population in September 2016 which amounted to 290.81 thousand people (8.37 %). Based on these figures, there is still a high rate of poverty in the Jambi City area in general. Based on these conditions it is necessary to do clusters to help BKKBN in grouping poor families so that assistance can be channeled appropriately. By observing the above problems, Data Mining is needed to classify beneficiaries by using the K-Means method in the clustering of the poor. The calculation results show, from 512 data samples of poor population in South Jambi Subdistrict, with a total cluster of 5, with an iteration of 3 obtained 13 residents entered as cluster members 1, 153 residents were in cluster 2, 129 residents in cluster 3, 138 residents were in cluster 4, and 79 residents are in cluster 5.
| Property | Value |
|---|---|
| Publisher ID | gdlhub |
| Organization | STIKOM Dinamika Bangsa Jambi |
| Contact Name | Herti Yani, S.Kom |
| Address | Jln. Jenderal Sudirman |
| City | Jambi |
| Region | Jambi |
| Country | Indonesia |
| Phone | 0741-35095 |
| Fax | 0741-35093 |
| Administrator E-mail | elibrarystikom@gmail.com |
| CKO E-mail | elibrarystikom@gmail.com |
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- Pembimbing : Kurniabudi, S.Kom, M.Kom dan Pareza Alam Jusia, S.Kom, M.Kom, Editor: Calvin
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