Sania Fitri Octavia
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

Penerapan K-Means dan Fuzzy C-Means untuk Pengelompokan Data Kasus Covid-19 di Kabupaten Indragiri Hilir Sania Fitri Octavia; Mustakim Mustakim
Building of Informatics, Technology and Science (BITS) Vol 3 No 2 (2021): September 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (406.275 KB) | DOI: 10.47065/bits.v3i2.1005

Abstract

In the beginning of 2020 world was shocked because new virus spreaded, that is Coronavirus Disease 2019 (Covid-19). This virus spread quickly in almost country, including Indonesia. Covid-19 virus deployment started in various regions in Indonesia stay increasing everyday. this research has been done the region clustering that infected Covid-19 case in Indragiri Hilir district to inform to central government about Covid-19 handling. To do Clustering in this research used K-Means and Fuzzy C-Means Algorithm. After done some of test, it's obtained the ratio which was tested with Silhouette Index and Partition Coefficient, SI validity value of K-Means is 0,950 while PCI validity value of Fuzzy C-Means is 0,960. The results have been obtained shown that Fuzzy C-Means Method is the best Method to do Clustering Covid-19 data in Indragiri Hilir district Because the validity value is closed to 1 which is located in K=3.
Penerapan Algoritma Association Rules Dalam Penentuan Pola Pembelian Berdasarkan Hasil Clustering Sania Fitri Octavia; Mustakim Mustakim; Inggih Permana; Siti Monalisa
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6129

Abstract

Zanafa Bookstore is one of the bookstores in Pekanbaru city that is required to meet customer needs and has the right focus in developing sales strategies every day. During the new school year there is an increase in sales, it is known that in July there are the most purchase transactions which are the beginning of the new school year for students and students. In addition, the placement of the book layout is only based on the employee's estimated shelf so that it will affect the convenience of consumers in choosing and finding books if the books are arranged far apart. By placing the layout in accordance with consumer purchasing patterns, it can improve the quality of customer service in bookstores. The book layout can also be used as a reference when adding book stock, information is needed by utilizing transaction data using data mining, namely by using Association rules commonly called Market Basket Analysis. This research uses K-Medoid for clustering on Apriori and FP-Growth in generating rule patterns on large-scale data. Several experiments were conducted on K-Medoid starting from cluster 2 to cluster 7, each of which will be applied to Apriori and FP-Growth with 30% support and 70% confidence. By comparing the evaluation results of each algorithm with each other, it is known that FP-Growth has superior results to Apriori with a total strength of rules of 1.2012. So that the results of the association rules obtained can be used as a reference in the placement of book layouts in the Zanafa bookstore.