Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Journal of Information Systems and Business Technology
Raihanullah
Universitas Pamulang
Computer Science & IT Library & Information Science

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

Found 2 Documents
Search

 1 
Mengukur Dampak Adopsi Payment Gateway Terhadap Loyalitas Pelanggan Dan Peningkatan Volume Transaksi UMKM Bayu Aditya Nuryansyah; Raihanullah; Oriandika Rasyid Rasyid
Journal of Information Systems and Business Technology Vol 1 No 4 (2025): Journal of Information Systems and Business Technology
Publisher : PT Jurnal Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to measure the impact of payment gateway adoption on customer loyalty and transaction volume growth in Micro, Small, and Medium Enterprises (MSMEs). Digital transformation has encouraged MSMEs to adapt to modern payment systems, including e-wallets, virtual accounts, and debit/credit cards. This study uses a quantitative method by distributing questionnaires to 120 MSME players in urban and semi-urban areas. Data analysis was performed using Path Analysis to test the direct and indirect relationships between the variables of perceived ease of use, trust, and satisfaction with the variables of customer loyalty and increased transaction volume. The results show that the adoption of payment gateways has a significant positive effect on customer loyalty (p < 0.05) and MSME transaction volume. The trust factor has the greatest contribution in encouraging customers to make repeat transactions. This study confirms that payment digitization can be an effective strategy for MSMEs in improving business performance. The implications of this study can be used as a basis for MSMEs and payment gateway service providers in improving service quality and transaction features.  
Analisis Segmentasi Pelanggan dan Prediksi Churn pada E-commerce Menggunakan K-Means Clustering dan Random Forest: Studi Kasus Olist Brazilian E-commerce Bayu Aditiya Nuryansyah; Raihanullah; Oriandika Rasyid
Journal of Information Systems and Business Technology Vol 2 No 3 (2026): Journal of Information Systems and Business Technology
Publisher : PT Jurnal Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid growth of the e-commerce industry requires digital platforms to focus on customer retention strategies to ensure business sustainability. This study aims to integrate a customer intelligence approach through customer segmentation and loyalty risk prediction. The methods applied in this study combine unsupervised learning techniques using the K-Means algorithm and supervised learning using the Random Forest algorithm on the Olist Brazilian E-commerce dataset. The clustering process based on the Recency, Frequency, and Monetary metrics produced optimal groupings with a Silhouette Score of 0.36. Furthermore, the Random Forest model successfully predicted the potential for churn with an accuracy rate of 85.37%. The combination of these two methods significantly contributes to mapping high-risk customer segments, enabling management to formulate precise retention programs.
Co-Authors Bayu Aditiya Nuryansyah Bayu Aditya Nuryansyah Oriandika Rasyid Oriandika Rasyid Rasyid