IMPLEMENTASI DATA MINING CLUSTERING JUMLAH PESERTA KB DI PROVINSI DKI JAKARTA MENGGUNAKAN ALGORITMA K-MEANS DENGAN VISUALISASI WEBGIS

RAMADHAN, RIFKI (2023) IMPLEMENTASI DATA MINING CLUSTERING JUMLAH PESERTA KB DI PROVINSI DKI JAKARTA MENGGUNAKAN ALGORITMA K-MEANS DENGAN VISUALISASI WEBGIS. S1 thesis, Universitas Mercu Buana.

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Abstract

This research will implement the clustering method with the K-Means algorithm for clustering on data on how many family planning participants are in DKI Jakarta Province to determine which areas have the number of family planning participants from the lowest to the highest. To find out which areas have the highest to lowest number of family planning participants and will be visualized using WebGIS. The data collected is data on family planning participants in DKI Jakarta Province in the 2018 - 2019 period and has 3318 records. The results of the best modeling performance obtained an accuracy of 0.88 or 88%, these results were obtained using K_Range = 3 in the SSE (Sum Square Error) calculation. The results of the study obtained Cluster 0 with the highest number of family planning participants in DKI Jakarta Province which has 5 total provinces and 3004 total data. Then the results are visualized with WebGIS. Keywords: KB, Clustering, Elbow Method, WebGIS. Pada penelitian ini akan melakukan implementasi metode clustering dengan algoritma K-Means untuk clustering pada data berapa banyak peserta KB di Provinsi DKI Jakarta untuk menetukan daerah mana yang memiliki jumlah angka peserta KB dari yang terendah hingga tertinggi. Untuk mengetahui daerah mana yang memiliki angka peserta KB tertinggi hingga terendah dan akan divisulisasikan dengan WebGIS. Data yang di kumpulkan merupakan data peserta KB di Provinsi DKI Jakarta pada periode 2018 - 2019 dan memiliki 3318 record. Hasil dari kinerja pembuatan model terbaik memperoleh akurasi sebesar 0.88 atau 88%, hasil tersebut didapatkan menggunakan K_Range = 3 pada perhitungan SSE (Sum Square Error). Hasil dari penelitian yang didapatkan Cluster 0 dengan jumlah peserta KB tertinggi di Provinsi DKI Jakarta yang memiliki 6 total provinsi dan 3004 total data. Kemudian hasilnya divisualisasikan dengan WebGIS. Keywords: KB, Clustering, Metode Elbow, WebGIS.

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 23 176
NIM/NIDN Creators: 41519010162
Uncontrolled Keywords: KB, Clustering, Metode Elbow, WebGIS.
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 003 Systems/Sistem-sistem
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 003 Systems/Sistem-sistem > 003.5 Computer Modeling and Simulation/Model dan Simulasi Komputer
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika > 004.1 General Works on Specific Types of Computers/Karya Umum tentang Tipe-tipe Khusus Komputer
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: CALVIN PRASETYO
Date Deposited: 02 Nov 2023 07:28
Last Modified: 02 Nov 2023 07:28
URI: http://repository.mercubuana.ac.id/id/eprint/83722

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