Supply Chain Risk Management In Palm Sugar Small And Medium Enterprises (Smes)

Komang Eka Dana Suputra; I Wayan Gede Sedana Yoga; I G A Lani Triani; Allan Anugerah Baratio Putu; Dewa Ayu Nadha Gita Vahini; Nindya Astrid Serafim Djobo

doi:10.63922/ijebir.v5i05.3403

Komang Eka Dana Suputra Departement of Agricultural Industrial Technology, Faculty of Agricultural Technology, Udayana University, Bali, Indonesia
Komang Eka Dana Suputra Departement of Agricultural Industrial Technology, Faculty of Agricultural Technology, Udayana University, Bali, Indonesia
I G A Lani Triani Departement of Agricultural Industrial Technology, Faculty of Agricultural Technology, Udayana University, Bali, Indonesia
Allan Anugerah Baratio Putu College Student, Departement of Agricultural Industrial Technology, Faculty of Agricultural Technology, Udayana University, Bali, Indonesia
Dewa Ayu Nadha Gita Vahini College Student, Departement of Agricultural Industrial Technology, Faculty of Agricultural Technology, Udayana University, Bali, Indonesia
Nindya Astrid Serafim Djobo College Student, Departement of Agricultural Industrial Technology, Faculty of Agricultural Technology, Udayana University, Bali, Indonesia

DOI: https://doi.org/10.63922/ijebir.v5i05.3403

Keywords: Supply Chain Risk Management; SCOR; FMEA; House of Risk; Palm Sugar; SMEs

Abstract

This study develops a supply chain risk management framework for the organic lontar palm sugar supply chain in Palmira Indonesia, Karangasem, Bali. The research is driven by critical operational instabilities, notably a 20% discrepancy between recorded and physical inventory and frequent production delays caused by inconsistent raw material supply. To address these challenges, the study employs an integrated methodology combining the Supply Chain Operations Reference (SCOR) model, Failure Mode and Effects Analysis (FMEA), and the House of Risk (HOR) framework. The supply chain was systematically mapped across five core processes: Plan, Source, Make, Deliver, and Return, identifying a total of 55 risk events and 60 potential risk agents. The results of HOR Phase I analysis indicate that risk exposure is highly concentrated; Pareto analysis reveals that 13 priority risk agents, representing only 21.6% of the total identified agents, account for 80.04% of the total Aggregate Risk Potential (ARP). The most critical agents identified include raw material scarcity (ARP = 2032), weak implementation of standard operating procedures (ARP = 1876), machinery and equipment failure (ARP = 1508), and limited technical capability of suppliers (ARP = 1440). In HOR Phase II, 17 targeted mitigation actions were formulated and prioritized based on their Effectiveness-to-Difficulty (ETD) ratios. The analysis identifies the establishment of periodic evaluation schedules (ETD = 9595) and the standardization of SOPs across all workstations (ETD = 8639) as the most impactful strategies for operational stabilization. These findings provide a structured diagnostic and a practical roadmap for small-scale agro-industrial systems to minimize disruption-driven waste, enhance product conformity, and improve the overall reliability of value-added organic supply chains.

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