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All Journal Sistemasi: Jurnal Sistem Informasi J-Com (Journal of Computer)
Rizki Rahmawati
Sekolah Tinggi Manajemen Informatika dan Komputer Royal
Computer Science & IT Electrical & Electronics Engineering

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CRM Method in Improving Clothing Marketing at Irma Collection with Bootstrap 3 Rizki Rahmawati; Masitah Handayani; Rika Nofitri
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i2.4025

Abstract

The purpose of this research is to improve clothing marketing at Irma Collection with Bootstrap 3 because Irma Collection does not have a means or system to spread its products. Customers must come directly to the store, this causes customers to ask first about detailed information about the product so that it is less effective because there is no facility that helps customers to find out information about the product. Irma Collection really needs improvement, namely the construction of a system in order to provide good service and satisfy customer interest and make it easier for owners to recap reports on goods sold. With the Customer Relationship Management (CRM) system, it is expected that Irma Collection will be easier to attract many customers and maintain customer interest to become regular customers at Irma Collection.
PENGELOMPOKAN DATA PENDUDUK MISKIN DI SUMATERA UTARA MENGGUNAKAN K-MEANS Ayu Safitri; Rizki Rahmawati; Sri Ayu Wandira
J-Com (Journal of Computer) Vol 4, No 1 (2024): Maret 2024
Publisher : LPPM STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/j-com.v4i1.2998

Abstract

Abstract: The government has made many efforts to eradicate poverty in society by implementing programs such as pro-poor, basic food assistance and cash assistance which are useful for achieving the standards of a prosperous society. The results of data processing are useful in future decision making. Considering the large amount of public data, finding out poor people is not an easy thing for the government to do, as is the case in North Sumatra. This research uses the K-Means Clustering (Multidimensional) method, making it easier to see patterns and structures in data that are difficult to see in the original representation. The application of the K-Means Clustering (Multidimensional) algorithm produces 3 clusters with a silhouette_score value of 33, namely cluster 0 with a high level of population poverty of 1, cluster 1 with a moderate level of population poverty of 4 and cluster 2 with a low level of population poverty as many as 28. Keywords: Resident; Poor; Data Mining; K-Means  Abstrak: Banyak upaya yang dilakukan pemerintah untuk menghapus kemiskinan pada masyarakat dengan cara melakukan program seperti pro-poor, bantuan sembako maupun bantuan uang tunai yang berguna untuk mencapai standar masyarakat sejahtera. Hasil pengolahan data tersebut berguna dalam pengambilan keputusan kedepannya. Mengingat banyaknya data masyarakat, maka untuk mengetahui masyarakat miskin bukanlah hal mudah yang dilakukan oleh pemerintah, sama halnya di Sumatera Utara. Penelitian ini menggunakan metode K-Means Clustering (Multidimensi) memudahkan untuk melihat pola dan struktur dalam data yang sulit dilihat dalam representasi aslinya. Penerapan algoritma K-Means Clustering (Multidimensi) menghasilkan 3 cluster, yaitu dengan cluster 0 dengan tingat kemiskinan penduduk yang tinggi sebanyak 1, cluster 1 dengan tingat kemiskinan penduduk yang sedang sebanyak 4 dan cluster 2 dengan tingkat kemiskinan penduduk yang rendah sebanyak 28. Kata kunci: Penduduk; Miskin; Multidimensi; Data Mining; K-Means
Co-Authors Ayu Safitri Masitah Handayani Rika Nofitri Sri Ayu Wandira