[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123409-en":3,"doc-seo-123409-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123409,13056703019662,"Evangeline","https://ap-avatar.wpscdn.com/avatar/be000253a8e92610077?_k=1778726343310543188",8,"Research & Report","Analysis of Food Security Index Predictions in Indonesia Using Machine Learning Approach - Research report","Food is a fundamental human need, so countries require reliable measures to monitor sufficiency, availability, and quality through the Food Security Index (FSI). The study builds a predictive model for Indonesia’s FSI using regency and city data from the Indonesian Food Security and Vulnerability Atlas (FSVA) during 2018–2024 (3,598 records). Multiple Linear Regression, LASSO, Random Forest, XGBoost, Support Vector Regression, and ensemble models are assessed with R², RMSE, and MAE. Results identify XGBoost as the strongest approach, enabling FSI projections for 2025–2026.","Analysis of Food Security Index Predictions in Indonesia Using Machine Learning Approach  \nFrederic Morado Saragih 􀁪 , Wahyu Catur Wibowo  \nFaculty of Computer Science, Universitas Indonesia, Depok, Indonesia  \n􀁪 Corresponding author email: [frederic.morado@ui.ac.id](frederic.morado@ui.ac.id)  \nArticle history: submitted: March 14, 2025; accepted: June 1, 2025; available online: July 6, 2025 Abstract. Food is one of the basic human needs that should always be available. To fulfill the role ofin a region, the concept of food security is established to measure sufficiency, availability and quality of food. Food security for a country is expressed using Food Security Index (FSI) . FSI score for a country reflects its ability for survival. It is therefore very important to measure the score and be able to predict future scores to enable control and improvement. To realize the improvement of Indonesia's food security, a model is needed to predict the Food Security Index in Indonesia. This paper explores the model using data from the Indonesian Food Security and Vulnerability Atlas (FSVA) at the Regency and City levels in 2018-2024 period with a total of 3,598 records. We evaluated Multiple Linear Regression, Least Absolute Shrinkage and Selection Operator, Random Forest, eXtreme Gradient Boosting, Support Vector Regression, and Ensemble Machine Learning models for predicting the FSI score. The models are evaluated using r-squared (R2), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) . The results shows that the XGBoost method is the best method for predicting the Food Security Index in Indonesia with an R2 value of R² of 0.978, RMSE of 0.024, and MAE of 0.016 . In addition, the XGBoost method predicts the average national Food Security Index score in 2025 and 2026 to be 75.14 respectively.  \nKeywords: data mining; model evaluation; food security and vulnerability atlas  \nINTRODUCTION  \nFood is one of the primary needs that must always be met by humans. In Indonesia, the right of citizens to obtain food is regulated in Article 27 paragraph 2 of the 1945 Constitution which states that “Tiap- tiap warga negara berhak atas pekerjaan dan penghidupan yang layak bagi kemanusiaan”. As a basic need anda form of human rights, food plays a very important role in life in an area. To fulfill the role of food for an area, the concept of food security was formed to measure sufficiency, availability and quality of food. In Article 1 of Law Number 18 of 2012 concerning food, food security is a condition of fulfilling food for the state up to individuals, which is reflected in the availability of sufficient food, both in quantity and quality, safe, diverse, nutritious, evenly distributed, and affordable and does not conflict with religion, beliefs, and culture of the community, to be able to live healthily, actively, and productively in a sustainable manner (Perum Bulog, 2014) . On the global scale, food security is integral to the United Nations Sustainable Development Goals  \n(SDGs), particularly Goal 2 , Zero Hunger, which targets the eradication of hunger, achievement of food security and improved nutrition, and the promotion of sustainable agriculture (Pristiandaru, 2023 ; United Nations, 2015) .  \nIn Indonesia, the level of food security is periodically assessed through the Food Security Index (FSI) as documented in the Food Security and Vulnerability Atlas (FSVA)(Sabarella et al., 2022) . In 2023, the national average FSI score reached 74.43 (out of 100), based on evaluations across 416 regencies and 98 cities. Despite this moderate score, food security in Indonesia remains a complex issue influenced by a wide array of determinants. Direct factors include food consumption patterns and access to healthcare, while indirect factors encompass food availability, political stability, distribution infrastructure, and socioeconomic conditions (B. Saragih, 2022) . In addition, conditions where not everyone has the ease of obtaining the fo","cbCaiefkD8KQfaqG","https://ap.wps.com/l/cbCaiefkD8KQfaqG","pdf",617122,1,17,"English","en",105,"# Introduction\n## Food security concepts and policy relevance\n## Food Security Index and Food Security and Vulnerability Atlas (FSVA)\n## Research gap and study aim\n## Related work and research question","[{\"question\":\"What is the purpose of predicting the Food Security Index (FSI) in Indonesia?\",\"answer\":\"Predicting FSI helps enable monitoring and supports government decision-making to allocate resources and strengthen policies for improving food security.\"},{\"question\":\"Which dataset and time period are used to train and evaluate the models?\",\"answer\":\"The study uses Indonesian Food Security and Vulnerability Atlas (FSVA) data at regency and city levels covering 2018–2024, totaling 3,598 records.\"},{\"question\":\"Which machine learning method performs best for FSI prediction and how is it evaluated?\",\"answer\":\"XGBoost performs best, evaluated using R², RMSE, and MAE, achieving R²≈0.978, RMSE≈0.024, and MAE≈0.016.\"}]","Analysis of Food Security Index Predictions in Indonesia Using Machine Learning Approach - Research report | PDF",1785816327,43,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"analysis-of-food-security-index-predictions-in-indonesia-using-machine-learning-approach-research-report","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/analysis-of-food-security-index-predictions-in-indonesia-using-machine-learning-approach-research-report/123409/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the purpose of predicting the Food Security Index (FSI) in Indonesia?","Question",{"text":75,"@type":76},"Predicting FSI helps enable monitoring and supports government decision-making to allocate resources and strengthen policies for improving food security.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which dataset and time period are used to train and evaluate the models?",{"text":80,"@type":76},"The study uses Indonesian Food Security and Vulnerability Atlas (FSVA) data at regency and city levels covering 2018–2024, totaling 3,598 records.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning method performs best for FSI prediction and how is it evaluated?",{"text":84,"@type":76},"XGBoost performs best, evaluated using R², RMSE, and MAE, achieving R²≈0.978, RMSE≈0.024, and MAE≈0.016.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]