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Enci Mulyani
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.
Strategic Planning for Rice Seed Productivity Using Integration of modified TF-IDF and SWOT-QSPM Enci Mulyani; Ridho Ananda; Famila Dwi Winati
JURNAL INFOTEL Vol 18 No 1 (2026): February
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v18i1.1416

Abstract

The agricultural sector of Indonesia is dependent on the availability of highquality rice seeds for its functionality. The effective management of these seeds is therefore of paramount importance to ensure the continuity of productivity and the security of food supplies. However, the aspirations of farmers, who are the primary actors, are often ineffective and only available in an unstructured narrative form. This complicates the process of strategic decision-making. The objective of this study is to enhance rice seed productivity by developing a strategy that employs an integrative informatics approach, integrating text mining, SWOT analysis, and the QSPM method. The data was collected via 100 open-endedinterviews with farmers and processed through text cleansing, modified TF-IDF weighting, and token classification into SWOT factors. The classification results were then employed to construct IFAS and EFAS matrices, which were used to determine strategic positioning. The utilization of the QSPM matrix facilitated the identification of priority strategies. The analysis indicated that the seed aspect falls into quadrant IV, suggesting a predominance of weaknesses and threats, necessitating a defensive (WT) strategy. The primary strategy identified was the provision of superior seeds that are resistant to extreme weather; this strategy achieved the highest score in the QSPM analysis. The strategy’s feasibility level, as validated by three experts, exceeded 83%, thus categorizing it as "highly feasible." The present study concludes that integrating text mining techniques with SWOT-QSPM transforms opinion data into an objective, adaptable, and applicable decision-making strategy based on local data.
Co-Authors Famila Dwi Winati Miftahol Arifin Muhammad Iqbal Faturohman Ridho Ananda