Dona Marcelina
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Analisis Tren Penjualan dan Prediksi Produk CV. Sentosa Menggunakan Regresi Linier Dona Marcelina; Indah Pratiwi Putri; Evi Yulianti; Agustina Heryati
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.v8i1.7649

Abstract

This study analyzed sales trends and forecasted the sales of CV Sentosa's products, namely Ater 360 New (X1), Bon Bon (X2), Mini Peanut Crackers (X3), and Marie Susu Int (X4), during the period of January 2019 to August 2023. Monthly sales data were processed using exploratory data analysis (EDA) and linear regression to predict sales trends. The linear regression analysis results indicated that X2 and X3 experienced sales growth with a slope of m=0.01, representing an average increase of 0.01 units per month. Conversely, X4 showed a slight decline with m=−0.01, while X1 remained stable with m=−0.00, indicating minimal changes in sales volume. The accuracy evaluation of the predictions based on MAE, MSE, and RMSE showed that X2 had the best performance with MAE 0.14, MSE 0.03, and RMSE 0.19, followed by X1 and X3, which had similar prediction errors. Although X4 initially showed significant growth, its model exhibited higher prediction errors (MAE 0.17, MSE 0.04, RMSE 0.21). This study provides valuable insights for CV Sentosa's business strategies, highlighting X2 and X3 as promising products due to their consistent growth trends and accurate predictions. This research provides a strong foundation for CV Sentosa in formulating more effective marketing strategies and product development in the future
Prediksi Kepuasan Pelanggan pada Layanan E-government Menggunakan Algoritma Decision Tree Indah Permatasari; Dona Marcelina; Evi Purnamasari
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.v8i1.7718

Abstract

The Online Licensing Service Information System (SIPPERI) implemented by DPMPTSP Palembang City aims to enhance efficiency, transparency, and accountability in public services. However, several challenges were reported by users, including unintuitive navigation, slow system responses, and inaccurate information. These challenges impact the level of user satisfaction with the service. This study uses the decision tree algorithm to evaluate user satisfaction based on data obtained through questionnaires with a Likert scale assessment involving 100 respondents. The analysis process uses the Python programming language. The dimensions analyzed include Efficiency (E), Trust (T), Reliability (R), Service (CS), Usability (U), Information Availability (I), and Interaction (SI). The analysis results show that the decision tree algorithm achieves an accuracy rate of 95%. The highest-scoring dimensions were recorded in the indicators Download Speed of Forms (R1: 392) and Accuracy of Instructions (E4: 392). Conversely, the lowest-scoring dimensions were Intuitive Navigation (E1: 300) and Information Availability (I1: 314). This study provides strategic recommendations for DPMPTSP Palembang City to improve dimensions with low scores to enhance user experience and strengthen public trust in e-government services.