Multidiciplinary Output Research for Actual and International Issue (Morfai Journal)
Vol. 6 No. 2 (2026): Multidiciplinary Output Research For Actual and International Issue

DEVELOPING AN OPERATIONAL STRATEGY TO ENHANCE MAINTENANCE EFFICIENCY: A CASE STUDY OF PROF RENTAL BALIKPAPAN

Eva Ervina (Unknown)
Liane Okdinawati (Unknown)



Article Info

Publish Date
31 Jan 2026

Abstract

Micro-enterprises in Indonesia play a critical role in economic development, yet they often face operational inefficiencies that threaten sustainability. Prof Rental Balikpapan, a motorcycle rental start-up operating in East Kalimantan, exemplifies these challenges. Despite strong market demand and revenue growth during its initial seven months, the company experienced severe volatility in maintenance costs, which exceeded budget allocations by 394% between January and July 2025. This unpredictability undermines profitability and constrains fleet expansion, highlighting the need for a structured operational strategy to stabilize costs and improve reliability. This research aims to address three core questions: (1) What factors contribute to high and inconsistent maintenance costs at Prof Rental Balikpapan? (2) How can a preventive maintenance schedule be structured to reduce costs and ensure timely servicing? (3) How can a standardized Standard Operating Procedure (SOP) be developed to institutionalize maintenance discipline? To answer these questions, a mixed-method approach was employed, combining qualitative diagnostics and quantitative reliability analysis. Primary data were collected through semi-structured interviews with the founder, operational staff, and external mechanic, while secondary data included financial records, maintenance logs, and OEM guidelines. Qualitative analysis using content analysis and BPMN process mapping revealed systemic weaknesses: reactive maintenance behavior, absence of usage-based scheduling, reliance on external workshops for diagnosis, and fragmented documentation. These factors collectively drive cost volatility and operational risk. Quantitative analysis reinforced these findings. Descriptive statistics and Pareto analysis showed that 36.89% of total maintenance costs were concentrated in engine overhauls, while failure interval variability exceeded 50% for high-risk units, confirming the lack of preventive control mechanisms. To address these issues, the study designed a preventive maintenance schedule using Failure Interval Analysis (FIA), which calculates maintenance intervals based on rental-day exposure rather than calendar assumptions. The proposed plan differentiates intervals by unit reliability, introducing monthly checks for high-risk units and quarterly checks for newer assets. Cost projections indicate that shifting from reactive to preventive maintenance reduces total expenditure by approximately 60%, from IDR 7,103,000 to IDR 3,470,000 over six months, while improving predictability and minimizing downtime. This preventive plan will be implemented for a short-term horizon of six months, followed by an evaluation in month seven to validate cost performance improvements. To institutionalize execution discipline, a standardized SOP was developed, integrating preventive triggers, approval thresholds, and documentation protocols. The SOP formalizes roles, introduces Maintenance Work Orders (MWO) for budget locking, and mandates a “reset mechanism” to ensure continuity of preventive cycles. These measures collectively transform maintenance from an ad-hoc, reactive process into a structured, system-driven operation. The contribution of this research lies in demonstrating how micro-enterprises can apply reliability-based preventive strategies and process standardization to achieve cost stability and operational resilience. By integrating FIA-driven scheduling with SOP governance, this study provides a practical framework for improving maintenance efficiency in resource-constrained service businesses. Future research is recommended to conduct longitudinal evaluations and explore digitalization or IoT-based solutions for real-time maintenance monitoring.

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