SERVICE WORKSHOP LOCATION SELECTION USING NETWORK-BASED MCLP AND MULTI-CRITERIA DECISION ANALYSIS: INTEGRATING ACCESSIBILITY, INDUSTRIAL SUITABILITY, AND FLOOD RISK ASSESSMENT IN EAST JAVA

Anargya Raakan Maulana; Manahan Parlindungan Saragih Siallagan

doi:10.31539/tq4q5p52

Authors

Anargya Raakan Maulana Institut Teknologi Bandung
Manahan Parlindungan Saragih Siallagan Institut Teknologi Bandung

DOI:

https://doi.org/10.31539/tq4q5p52

Keywords:

Small And Medium Enterprises, Geographic Information Systems, Service-Level Agreement, Maximal Covering Location Problem, Weighted Linear Combination, Facility Location

Abstract

This study addresses the strategic problem of service facility location for small and medium enterprises (SMEs) operating in geographically diverse and risk-prone regions, using a spatial decision-support framework. The research focuses on PT Cahaya Amanah Nusantara (PT CAN), an Indonesian SME providing refrigeration repair and maintenance services, and applies a quantitative geospatial analysis design. Data were derived from OpenStreetMap road networks, historical service request records, administrative spatial data, and managerial assessments. The analysis was conducted in three stages. First, service coverage was evaluated through travel-time-based accessibility analysis under Service-Level Agreement (SLA) constraints, and optimal candidate locations were identified using the Maximal Covering Location Problem (MCLP) with a single-facility objective. Second, the selected locations were assessed based on strategic geographic and environmental factors, including industrial activity density and flood risk exposure. Third, a Multi-Criteria Decision Analysis (MCDA) using the Weighted Linear Combination (WLC) method integrated accessibility performance, environmental risk, and strategic suitability based on managerial weighting preferences. The results indicate that Kabupaten Gresik achieved the highest composite score of 0.937016, reflecting strong SLA performance and high strategic attractiveness, despite a relatively low environmental contribution. The findings demonstrate that the proposed framework provides a transparent, logic-based, and easily interpretable decision-making tool for ranking service facility locations and evaluating trade-offs between efficiency, alignment, and robustness. This study contributes an open-source, SME-oriented geospatial decision-support approach for facility location planning in heterogeneous and risk-sensitive environments.

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