Muhammad Raffiza Azka, . (2023) PENERAPAN ALGORITMA “K-MEANS CLUSTERING” UNTUK MENGETAHUI PREFERENSI JENIS USAHA MIKRO WARGA KECAMATAN INDRAMAYU TAHUN 2020. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
MSMEs or Micro, Small and Medium Enterprises have become one of the main sources of income for many Indonesians. To develop MSMEs in an area, we need to know the MSME preferences of residents of that area. It is hoped that from the results of this study we can find out which types of Micro Enterprises are most in demand. In this study, the method to be used is the K-Means Clustering method. Elbow method will be used to determine the number of clusters. After the clustering process, clusters will be tested using the silhouette coefficient method and the Davies Bouldin Index. For this research, data clustering will be divided into several labels based on the type of Micro Enterprises. The research will use Micro Enterprises data from Indramayu District. The total raw data to be used in this study is 24,000. Because the data is still in an inadequate condition, it is necessary to pre-process the data first because the data conditions are a bit messy so that there are no obstacles in the research process. This research will use Python and Excel to pre-process the data and apply K-Means Clustering.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | No.Panggil : 1910511062 Pembimbing : Nurhafifah Matondang Penguji 1 : Bayu Hananto Penguji 2 : Anita Muliawati |
| Uncontrolled Keywords: | Micro Enterprises, K-Means, Clustering, Elbow Method, Silhouette Coefficient, Davies Bouldin Index, Indramayu, Preprocess |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Muhammad Raffiza Azka |
| Date Deposited: | 24 Jul 2023 04:01 |
| Last Modified: | 24 Jul 2023 04:01 |
| URI: | http://repository.upnvj.ac.id/id/eprint/25329 |
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