CLASSIFICATION OF FOOD MENU AND GROUPING OF FOOD POTENTIAL TO SUPPORT THE FOOD SECURITY AND NUTRITION QUALITY

M. Fariz Fadillah Mardianto, Suliyanto, Faried Effendy, Antonio Nikolas Manuel Bonar Simamora, Ayuning Dwis Cahyasari, Chaerobby Fakhri Fauzaan Purwoko, Netha Aliffia

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The Movement for Diverse, Nutritious, Balanced, and Safe Diet, in this article called by B2SA is a program from the Indonesian government to improve resilience and nutritional quality in line with one of the Sustainable Development Goals, especially during the Coronavirus Disease (COVID-19) pandemic. In this article, classification and grouping methods are carried out to determine the development of supporting the B2SA program in Indonesia, such as the classified menu arrangement and the potential for grouped foodstuffs, especially in East Java, which is one of the provinces with a high COVID-19 spread rate and contributes greatly to food security in Indonesia. The application of the classification method in this study is to compare the performance of logistic regression and random forest. In addition, the clustering method is applied by comparing the performance of Single Linkage and K-Means. The results of this study are the category of food menu recommended by the population of East Java, which turned out to be 49.3% not meeting the B2SA standard. As for the results of the grouping, there are four groups for potential food categories of staple foods and side dishes, two groups for the category of fruits and vegetables. These results are expected to be a recommendation for the government in supporting the stability of food security to strengthen the resilience of the food industry in Indonesia because it is a region that has food potential in Indonesia.

Original languageEnglish
Article number2
JournalCommunications in Mathematical Biology and Neuroscience
Volume2022
DOIs
Publication statusPublished - 2022

Keywords

  • Classification method
  • Cluster analysis
  • Computational Statistics
  • Food security
  • Improvement of nutritional quality

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