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All Journal JURNAL TEKNIK Journal Industrial Manufacturing
Andri Oktarian
UNIVERSITAS BUDDHI DHARMA
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Digitalisasi Supply Chain Integrasi Teknologi dan Peningkatan Kinerja Rantai Pasok di Era Industri 4.0 Andri Oktarian
Jurnal Teknik Vol. 14 No. 2 (2025): Juli - Desember 2025
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jt.v14i2.15194

Abstract

The advancement of digital technologies has revolutionized global supply chain management by transforming conventional systemsinto intelligent, interconnected networks. This study aims to analyzethe role of digitalization in enhancing integration, efficiency, and resilience within modern supply chains. A quantitative explanatory approach was employed using the Structural Equation Modeling–Partial Least Squares (SEM-PLS) method on 120 respondents from manufacturing and logistics companies in Indonesia that have adopted Internet of Things (IoT), Artificial Intelligence (AI), Big Data, Blockchain, and Cloud Computing technologies. The results indicate that digitalization has a significant positive effect on supply chain integration (β = 0.62; p < 0.001), which in turn improves operational performance (β = 0.57; p < 0.001) and organizational resilience (β = 0.49; p < 0.001). Mediation analysis confirms that supply chain integration actsas the primary conduit linking digitalization with enhanced performance and resilience. The R² values (0.52–0.61) and Q² values (>0.30) demonstrate strong predictive power of the proposed model. Theoretically, this study expands the understanding of digital integration capability as a key factor in achieving competitive advantage and organizational adaptability. Practically, the findings emphasize the importance of cross-functional collaboration, data interoperability, and digital readiness of human resources to build resilient supply chains in the era of Industry 4.0.Keywords: artificial intelligence, digital supply chain, industry 4.0, integration capability, supply chain resilience
Penerapan Model Transformer Untuk Memprediksi Tingkat Akurasi Permintaan Distribusi Barang Pada Sistem Pergudangan Andri Oktarian; Sri Lestari; Sulkhan
Journal Industrial Manufacturing Vol. 11 No. 2 (2026): Journal Industrial Manufacturing
Publisher : Program Studi Teknik Industri Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/ztmchn70

Abstract

Proses akurasi dalam menentukan peramalan permintaan barang (demand forecasting) menjadi hal yang sangat penting, terutama dalam elemen manajemen supply chain, khususnya pada sistem operasional gudang guna meminimalisir tingkat kesalahan dalam pengiriman dan ketidaksesuaian stok barang. Penelitian ini bertujuan untuk melihat tingkat akurasi model Transformer dalam memprediksi permintaan barang di gudang. Sebagai bahan perbandingan, hasil akurasi model ini akan dibandingkan dengan metode konvensional seperti Moving Average dan ARIMA. Metode penelitian yang digunakan bersifat kuantitatif dengan pendekatan eksperimen, menggunakan data simulasi yang mencerminkan pola permintaan gudang (tren, musiman, dan noise). Hasil penelitian yang dilakukan menunjukkan bahwa model Transformer memiliki tingkat akurasi yang lebih tinggi dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 9.12%, dibandingkan dengan ARIMA (15.87%) dan Moving Average (20.34%). Berdasarkan hasil temuan ini, model Transformer mampu menangkap pola kompleks dalam data time series dan berpotensi meningkatkan efisiensi operasional gudang serta mengurangi risiko kesalahan distribusi.
Co-Authors SRI LESTARI Sulkhan