Abstract

Food waste is one of the most recent global issues that is getting more attention nowadays. Food waste is all food that is not consumed or thrown away even though it is fit for human consumption. This paper presents a method of direct weighing of edible food that is not consumed in the student canteen. Based on preliminary observations, food is classified into carbohydrates, vegetables, meat and others. The results of weighing data show more accurate results compared to previous study. With a total of 226 data, the research was focused on the carbohydrate and vegetable variables. The computer algorithm using the elbow method shows the unsupervised K-Means clustering of 4 clusters. The quality of the clustering method is good, with an average silhouette coefficient of 0.6. This research can be used as a basis for further studies on food waste and life cycle assessment.

Highlights

  • Food waste is one of the most recent global issues that is getting more attention nowadays

  • Food and Agriculture Organization of the United Nations (FAO) estimated that 30% of food globally that are produced for human consumption turned into food loss or food waste, which cost more than 1 trillion dollars for economic, environmental and social aspects

  • The significant number should become a deep concern for everyone, knowing that based on a report published by FAO in 2019, there were still 1 of 9 people do not have enough food to eat. It is a global issue, and many countries have a serious commitment to participate in the Sustainable Development Goals (SDG) program, with a vision to reduce half food waste of the total number

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Summary

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Introduction
Materials and Method
Scope of the Research
Data Column
Inertia Centroid
Cluster N
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