SYSTEM ANALYSIS AND DESIGN PRODUCTION OF EDIBLE BIOFILM FROM MINT LEAF ESSENTIAL OIL AS AN ANTIMICROBIAL

Authors

  • Griselda Happy Ramadhani Department of Industrial Engineering, Faculty of Engineering and Computer Science, Indraprasta PGRI University
  • Syifa Robbani Universitas Sriwijaya
  • Ninta Sri Ulina Department of Industrial Engineering, Faculty of Engineering and Computer Science, Indraprasta PGRI University

DOI:

https://doi.org/10.24961/j.tek.ind.pert.2025.35.2.196

Abstract

Poor packaging can definitely contribute to food spoilage, reducing food quality and shelf life. Active 
packaging using edible biofilm with antimicrobial essential oils can inhibit microbial growth and extend product 
freshness. The purpose of this study was to classify edible biofilm products to determine their quality and predict 
proper drying conditions. The method involved system modeling using Unified Modeling Language (UML) and 
Business Process Model and Notation (BPMN) to map the production process from raw material handling to 
industrial scale manufacturing. Subsequently, machine learning models were applied: the Decision Tree model 
for classifying product quality including physical, mechanical, and antimicrobial properties and Ordinary Least 
Squares (OLS) linear regression for predicting drying parameters. The research steps consisted of creating system 
models to improve clarity and team alignment, collecting relevant data on elongation, tensile strength, moisture 
content, and antimicrobial activity, then applying the Decision Tree for quality classification and antimicrobial 
categorization into four levels. OLS regression was used to model the relationship between drying conditions and 
final moisture content. Results demonstrated that UML and BPMN modeling enhanced understanding and 
consistency in production flow. The Decision Tree classified edible biofilm quality into three categories with 80.5% 
accuracy and antimicrobial ability into four inhibitory levels with 95% accuracy. The OLS regression predicted 
drying outcomes with 64% explanatory power and statistical significance (p-value < 0.05). This study contributes 
to intelligent packaging development by integrating system modeling and machine learning, enabling early 
classification a nd drying prediction to improve quality control, efficiency, and reliability in active food packaging.


Keywords: antrimicobe, decision tree, edible biofilm, linear regression, use case

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Published

2025-08-30

How to Cite

SYSTEM ANALYSIS AND DESIGN PRODUCTION OF EDIBLE BIOFILM FROM MINT LEAF ESSENTIAL OIL AS AN ANTIMICROBIAL. (2025). Jurnal Teknologi Industri Pertanian, 35(2). https://doi.org/10.24961/j.tek.ind.pert.2025.35.2.196