Ferizal, Ferizal (2026) Pengembangan Dan Pengujian Model Struktural Adopsi Kecerdasan Buatan (Ai), Otomatisasi Dan Digitalisasi Pada Sistem Grading Tandan Buah Segar (Tbs) Pabrik Kelapa Sawit Dalam Kerangka Industri 4.0. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Industri kelapa sawit Indonesia masih menghadapi tantangan dalam sistem penilaian kematangan Tandan Buah Segar (TBS) yang bergantung pada metode manual, sehingga mengakibatkan inkonsistensi kualitas, peningkatan kadar Free Fatty Acid (FFA), penurunan Oil Extraction Rate (OER), dan inefisiensi operasional yang berdampak langsung pada nilai bisnis pabrik. Penelitian ini bertujuan mengembangkan dan menguji model struktural yang menghubungkan kesiapan pabrik, implementasi teknologi Industri 4.0 pada sistem grading TBS, serta dampaknya terhadap kinerja sistem dan nilai bisnis pabrik kelapa sawit Indonesia. Penelitian menggunakan Systematic Literature Review (SLR) berbasis PRISMA 2020 dan Covariance-Based Structural Equation Modeling (CB-SEM) dengan AMOS. Data dikumpulkan dari responden pabrik kelapa sawit Indonesia yang mencakup tiga level jabatan yaitu strategis, taktis, dan operasional. Hasil penelitian menunjukkan bahwa kesiapan infrastruktur teknologi, platform data digital, dan implementasi sistem grading berbasis kecerdasan buatan berpengaruh signifikan terhadap kinerja sistem. Dampak operasional terbukti menjadi jalur utama penciptaan nilai bisnis, sementara kapabilitas SDM berkontribusi langsung terhadap nilai bisnis secara independen dari kinerja teknis sistem. Penelitian ini memberikan panduan berbasis bukti empiris bagi manajemen pabrik kelapa sawit dalam memprioritaskan investasi teknologi Industri 4.0 secara bertahap dan terukur.
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The Indonesian palm oil industry continues to face fundamental challenges in the Fresh Fruit Bunch (FFB) maturity grading system, which relies heavily on manual assessment methods, resulting in quality inconsistencies, elevated Free Fatty Acid (FFA) levels, declining Oil Extraction Rate (OER), and operational inefficiencies that directly impact mill business value. This study aims to develop and test a structural model linking mill readiness, Industry 4.0 technology implementation in the FFB grading system, and its effects on system performance and business value in Indonesian palm oil mills. The study employs a Systematic Literature Review (SLR) based on PRISMA 2020 and Covariance-Based Structural Equation Modeling (CB-SEM) using AMOS software. Data were collected from respondents across Indonesian palm oil mills representing three organizational levels: strategic, tactical, and operational. The findings reveal that technology infrastructure readiness, digital data platforms, and AI-based grading system implementation significantly influence system performance. Operational impact is confirmed as the primary pathway to business value creation, while Human Capability demonstrates a direct and independent contribution to business value, separate from technical system performance. This study provides empirically grounded guidance for palm oil mill management in prioritizing Industry 4.0 technology investments in a structured and measurable manner.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Industri kelapa sawit, grading berbasis AI, data digital, Industri 4.0, CB-SEM, AMOS, SLR, PRISMA 2020, technology readiness, business value. palm oil industry, AI grading, digital data, industry 4.0, CB-SEM, AMOS, SLR, technology readiness, business value. |
| Subjects: | Q Science T Technology > T Technology (General) |
| Divisions: | Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT) |
| Depositing User: | Ferizal Ferizal |
| Date Deposited: | 16 Jul 2026 08:18 |
| Last Modified: | 16 Jul 2026 08:18 |
| URI: | http://repository.its.ac.id/id/eprint/135237 |
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