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All Journal Journal of Industrial Engineering and Operation Management (JIEOM) Advance Sustainable Science, Engineering and Technology (ASSET)
Mangngenre, Saiful
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Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Barriers to Lean Manufacturing Implementation in the Bakery Industry: An Empirical Study from Indonesia Caroline Felicita Aurelius; Mangngenre, Saiful; Setiawan, Irwan
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i4.1974

Abstract

The implementation of lean manufacturing is essential for companies to minimize waste by reducing non-value-added activities while maintaining product quality and customer satisfaction. Despite its advantages, various barriers hinder its optimal application. This study aims to identify the factors that impede the implementation of lean manufacturing and determine the most dominant factors in bakery factories in Indonesia. The research was conducted across 14 bakery factories on the islands of Sumatra, Java, Kalimantan, and Sulawesi. Data was collected using a survey questionnaire and analyzed using factor analysis and the Decision Making and Evaluation Laboratory (DEMATEL) method. The results reveal seven key factors with significant influence, with technology emerging as the most dominant factor (1.404), followed by organizational culture (0.497). These findings underscore the importance of addressing the technological limitations and organizational culture to enhance lean manufacturing efficiency. The practical implications of this study suggest that bakery companies should focus on improving their technological infrastructure and fostering a culture supportive of lean principles to optimize production efficiency. Theoretical implications include the extension of lean manufacturing frameworks to address sector-specific challenges in the bakery industry, contributing to the broader field of sustainable manufacturing practices
Perencanaan Agregat Dengan Metode Forecasting Model ARIMA dan Agregat Planning Heuristik Indah, A. Besse Riyani; Aswal, A Haedir; Ikasari S, Diniary; Mangngenre, Saiful; Busri, Nur Khaerani; BJ, Muhammad Facheruddin
Journal of Industrial Engineering and Operation Management (JIEOM) Vol 8, No 2 (2025)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/jieom.v8i2.19969

Abstract

Perencanaan produksi yang optimal sangat penting untuk meningkatkan efisiensi operasional, khususnya di industri manufaktur yang menghadapi fluktuasi permintaan. Penelitian ini dilakukan di PT. Ciomas Adisatwa Maros dengan tujuan mengoptimalkan produksi menggunakan metode forecasting ARIMA dan strategi perencanaan agregat heuristik. Data historis permintaan McDonald’s (Mcd R) digunakan sebagai dasar peramalan, dengan model ARIMA (1,1,1) terpilih sebagai model terbaik. Tiga skenario perencanaan agregat dianalisis yaitu existing, pengendalian tenaga kerja, dan pengendalian overtime. Hasil menunjukkan bahwa skenario pengendalian overtime memberikan efisiensi biaya tertinggi dengan penghematan sebesar 21,37% dibandingkan skenario existing. Kombinasi ARIMA dan metode heuristik terbukti efektif dalam menghasilkan perencanaan produksi yang efisien tanpa mengurangi kapasitas produksi. Temuan ini menjadi acuan penting bagi perusahaan dalam menyusun strategi produksi yang adaptif terhadap perubahan permintaan dan berkontribusi dalam peningkatan daya saing industri pengolahan pangan.Kata Kunci:  Perencanaan Agregat, ARIMA, Forecasting, Optimalisasi Produksi, Efisiensi Biaya
Co-Authors A. Besse Riyani Indah Aswal, A Haedir BJ, Muhammad Facheruddin Caroline Felicita Aurelius Ikasari S, Diniary IRWAN SETIAWAN Nur Khaerani Busri