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Miftahol Arifin
Telkom University, Indonesia
Computer Science & IT Electrical & Electronics Engineering

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Data-Driven Product Segmentation for Shallot Commodities using PCA and K-Means Clustering Approach Famila Dwi Winati; Miftahol Arifin; Muhammad Iqbal Faturohman; Enci Mulyani
JURNAL INFOTEL Vol 17 No 3 (2025): August
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i3.1307

Abstract

The shallot industry plays a strategic role in the Indonesian economy, especially in the Brebes Regency as the largest production center. However, challenges in the form of price fluctuations and low value-added products still burden farmers. Previous research tends to focus on individual products without considering a holistic product clustering strategy. This study aims to address the gap by applying the K-Means clustering method combined with Principal Component Analysis (PCA) to identify patterns in shallot and processed product sales data. The research data includes sales of 308 products from 2022-2024. The variables analyzed include product type, size, number of sold, and turnover. The results of the analysis formed three main groups, which are group 0 (small products with low performance), group 1 (large products with superior performance) and group 2 (medium products with stable performance). The findings indicate the importance of more targeted marketing strategies and product diversification. The implications of this study include optimizing superior products, revitalizing low-performing products, and developing stable products to expand the market. A customized e-Commerce-based strategy per cluster can improve the financial performance of the organization and the welfare of shallot farmers in a sustainable manner.
A Mathematical Model for Blockchain Adoption in High-Risk Asset Management Miftahol Arifin; Elisa Kusrini; Winda Nur Cahyo; Imam Djati Widodo
JURNAL INFOTEL Vol 18 No 2 (2026): May
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v18i2.1544

Abstract

This study develops and empirically validates a mathematical adoption model for blockchain-based information systems using an Extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Previous blockchain adoption studies predominantly assessed behavioral determinants through isolated hypothesis testing, with limited efforts to integrate contextual factors into a unified structural model. To address this gap, the proposed framework incorporates blockchain-specific and organizational constructs, including trust and perceived security, operational resilience expectation, technology adaptability, and regulatory compliance, along with the core UTAUT dimensions. A quantitative, explanatory, and cross-sectional design was employed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to estimate model parameters from survey data collected from 132 professionals operating in high-risk power plant asset management environments. The model explains 68.9% of the variance in behavior intention and 42.0% of actual system use. Trust and perceived security emerged as the strongest predictor of behavioral intention, followed by performance expectation and operational resilience expectation. The findings demonstrate the suitability of Extended UTAUT for mathematically representing the adoption behavior of blockchain in high-risk organizational settings and provide a transferable analytical framework for future studies of the adoption of blockchain-based information systems.
Co-Authors Enci Mulyani Famila Dwi Winati Imam Djati Widodo Kusrini, Elisa Muhammad Iqbal Faturohman Winda Nur Cahyo