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All Journal Indonesian Journal of Innovation Studies PELS (Procedia of Engineering and Life Science)
Andreyanto, Muhammad Faisal
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice

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Refining Sugar Production Forecasts: Analyzing Forecasting Techniques for Operational Precision: Prakiraan Produksi Gula Penyulingan: Menganalisis Teknik Peramalan untuk Ketepatan Operasional Andreyanto, Muhammad Faisal; Wahyuni, Hana Catur
Procedia of Engineering and Life Science Vol. 5 (2024): Proceedings of the 7th Seminar Nasional Sains 2024
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/pels.v7i0.1558

Abstract

This study compares the efficacy of moving averages and double exponential smoothing (Holt's method) in predicting sugar production, using historical data. Results reveal that double exponential smoothing outperforms moving averages, offering more accurate forecasts, particularly in contexts requiring responsiveness to data trends. These findings hold significant implications for enhancing operational efficiency and readiness in the sugar industry, guiding maintenance scheduling and production target achievement. Highlights: Double exponential smoothing (Holt's method) surpasses moving averages in accuracy. Importance of forecasting in operational efficiency and maintenance scheduling. Applicability of forecasting techniques in the sugar industry context. Keywords: Forecasting, Moving Average, Sugar Production
Optimization of Shrimp Cracker Drying Parameters Using RSM and RCA: Optimasi Parameter Pengeringan Kerupuk Udang Menggunakan RSM dan RCA Andreyanto, Muhammad Faisal; Sulistiyowati, Wiwik
Indonesian Journal of Innovation Studies Vol. 26 No. 4 (2025): October
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v26i4.2105

Abstract

General Background Shrimp cracker production requires strict quality control, particularly in moisture content, which determines texture, shelf life, and defect occurrence. Specific Background In industrial practice, defects such as mold growth remain a critical issue due to suboptimal drying and process control conditions. Knowledge Gap Previous studies have not fully integrated process optimization and root cause identification to address both quality parameters and defect sources simultaneously. Aims This study aims to optimize drying parameters and identify root causes of defects using Response Surface Methodology (RSM) and Root Cause Analysis (RCA). Results The optimal conditions were obtained at a temperature of 70°C, drying time of 60 minutes, and thickness of 5 mm, producing a moisture content of 9.00% with a desirability value of 1.00. RCA findings indicate that mold defects are caused by high raw material moisture, inadequate storage conditions, and limited production supervision. Novelty This study integrates RSM-based parameter optimization with RCA-based defect analysis within a single framework. Implications The results provide practical recommendations for improving production control, reducing defects, and maintaining consistent product quality in shrimp cracker manufacturing. Keywords: Shrimp Cracker, Process Optimization, Moisture Content, Response Surface Methodology, Root Cause Analysis Key Findings Highlights Optimal drying parameters identified through statistical modeling approach Major defect source linked to raw material and process control conditions Integrated analytical framework supports systematic quality improvement
Co-Authors Hana Catur Wahyuni Wiwik Sulistiyowati