Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal JSAI (Journal Scientific and Applied Informatics)
Belly, Belly Nagustria
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Optimasi Strategi Penjualan Produk Zaskia Melalui Integrasi Algoritma K-Nearest Neighbors (KNN) dan Regresi Linier Ermatita; Belly, Belly Nagustria
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.8074

Abstract

This study aims to evaluate the model's performance in classifying and predicting the number of product sales based on several attributes. The K-Nearest Neighbors (KNN) algorithm was used for the classification task and showed good performance with an accuracy of 91.22%, recall of 92.96%, and precision of 90.18%. These results indicate that the model has a high generalization ability in recognizing sales patterns. For quantitative prediction of the number of sales, a linear regression model is used with independent variables such as regular price, selling price, rating, number of ratings, and number of favorites. The regression model yielded a coefficient of determination (R²) of 0.78, indicating that 78% of the variability of the sales amount can be explained by these variables. The coefficient analysis results show that the rating, number of ratings, and number of favorites have a positive influence on the sales amount, while the selling price and normal price have no significant effect. The Root Mean Squared Error (RMSE) value of 33.09 indicates a fairly low level of prediction error. These findings indicate that the model used is effective in helping analyze and forecast product sales.
Co-Authors Ermatita -