Evaluasi Tata Kelola TI pada Industri Manufaktur Kereta Api dalam Proses Pengadaan Menggunakan COBIT 2019
Abstract
The procurement process in the railway manufacturing industry exhibits high complexity due to product characteristics that vary in specification for every project. PT Industri Kereta Api (INKA), a strategic state-owned enterprise (SOE) located in Madiun, East Java, faces challenges in information technology (IT) governance to support this process, while simultaneously being bound by regulatory mandates for independent IT maturity assessments. This study aims to measure the maturity level of IT governance in PT INKA's procurement process and formulate measurable improvement recommendations. The evaluation was conducted using the COBIT 2019 framework across five strategic domains: APO10 (Managed Vendors), APO12 (Managed Risk), BAI03 (Managed Solutions Identification and Build), BAI06 (Managed IT Changes), and MEA01 (Performance and Conformance Monitoring). Utilizing a descriptive approach, this research involved purposive stakeholders from PT INKA's IT department. Data collection was carried out through semi-structured interviews, field observations, document analysis, and the COBIT 2019 assessment instrument based on the NPLF scale. The evaluation results reveal that all domains are currently at Level 3 (Established Process), indicating a 1-level gap from the targeted Level 4 (Predictable Process). The primary obstacle is the lack of consistent quantitative measurement implementation, such as standardized vendor KPI (Key Performance Indicators ), threshold-based KRI (Key Risk Indicators), and an integrated business intelligence platform. The resulting recommendations are practical and phased, with priority given to the establishment of a Change Advisory Board. This study contributes empirical evidence on IT governance evaluation specifically addressing procurement in the railway manufacturing industry, characterized by high product customization, and serves as a practical reference for similar industry in developing capability improvement measures toward a more predictable process level.
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