HARIANTO, ANDRI (2024) PENERAPAN METODE K-MEANS CLUSTERING PADA DATA ASURANSI KENDARAAN BERMOTOR UNTUK SEGMENTASI NASABAH. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
This research aims to apply the K-Means Clustering method to motor vehicle insurance company customer data and to determine customer segmentation based on K-Means Clustering results on motor vehicle insurance company customer data. The method used in this research is a quantitative descriptive approach. The subject of this research is policy data from an insurance company. Data collection techniques in this research were observation, interviews, and literature study. Evaluation of research results in this study refers to the use of the Davies Bouldin Index (DBI) as a tool to assess the quality of segmentation results from the K-Means Clustering method. The research results show that the analysis and visualization of the segmentation results, both in the form of reports and distribution graphs, is expected to provide a clear understanding of the characteristics of each customer group. Finally, through this research, a report was produced that contributes to general understanding and progress in the use of the K-Means Clustering method in customer segmentation. Penelitian ini bertujuan untuk menerapkan metode K-Means Clustering pada data nasabah perusahaan asuransi kendaraan bermotor serta untuk mengetahui segmentasi nasabah berdasarkan hasil K-Means Clustering pada data nasabah perusahaan asuransi kendaraan bermotor. Metode yang digunakan dalam penelitian ini adalah pendekatan deskriptif kuantitatif. Adapun subjek pada penelitian ini adalah data data polis dari salah satu perusahaan asuransi. Teknik pengumpulan data pada penelitian ini adalah observasi, wawancara, dan studi literatur. Evaluasi hasil penelitian dalam penelitian ini mengacu pada penggunaan Davies Bouldin Indeks (DBI) sebagai alat untuk menilai kualitas segmentasi hasil dari metode KMeans Clustering. Hasil penelitian menunjukkan bahwa analisis dan visualisasi dari hasil segmentasi tersebut baik dalam bentuk laporan dan grafik sebaran diharapkan dapat memberikan pemahaman yang jelas tentang karakteristik masing-masing kelompok nasabah. Terakhir melalui penelitian ini dihasilkan laporan yangmemberikan kontribusi pada pemahaman umum serta kemajuan dalam penggunaan metode K-Means Clustering dalam segmentasi nasabah.
| Item Type: | Thesis (S1) |
|---|---|
| Call Number CD: | FIK/INFO. 24 193 |
| Call Number: | SIK/15/24/146 |
| NIM/NIDN Creators: | 41519110013 |
| Uncontrolled Keywords: | Metode K-Means Clustering, Asuransi Kendaraan Bermotor, Segmentasi |
| 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 > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 300 Social Science/Ilmu-ilmu Sosial > 360 Social Problems and Services/Permasalahan dan Kesejahteraan Sosial > 368 Insurance/Asuransi |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | ANANDA NADIRA PUTRI |
| Date Deposited: | 05 Sep 2024 06:53 |
| Last Modified: | 12 Sep 2024 02:45 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/91200 |
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