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Analisis Perkembangan Ketahanan Pangan di Indonesia : Pendekatan Menggunakan Big Data dan Data Mining Fadila, Lalu Moh. Arsal; Putri, Nadia Arsyta
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1890

Abstract

Food security is a crucial topic for Indonesia as it is intricately linked to social, economic, and political aspects. The majority of Indonesia's population relies on the agricultural sector to meet their daily needs, both in terms of economic livelihood and food nutrition. Therefore, the Indonesian government must ensure that the food needs of its population are sustainably met by emphasizing the development of food security. The process of food security development requires accurate and up-to-date data. Utilizing Big Data has become an alternative to fulfill the need for large, accurate, and efficiently manageable data. One component of Big Data is Google Trends. In this research, Google Trends was analyzed using LSTM and K-Means Clustering methods. The results showed that the LSTM model was able to predict the trends related to food security in Indonesia quite effectively. Furthermore, the topics related to food security from Google Trends could be clustered using K-Means Clustering, resulting in the formation of three clusters. Of particular concern is Cluster 1, as it indicated relatively low information regarding the topic of food security in Indonesia.