[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123627-en":3,"doc-seo-123627-105":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},123627,687197100911,"Himbo","https://ap-avatar.wpscdn.com/avatar/a000239b6f1da00475?x-image-process=image/resize,m_fixed,w_180,h_180&k=1785132997149421697",8,"Research & Report","A Study of Prediction Model for Capture Fisheries Production in Indonesian Sea Waters Using Machine Learning","Capture fisheries potential in Indonesia represents a renewable, long-term resource whose sustainability directly supports food security as population grows. A capture fisheries production prediction model is required to determine key variables that influence production outcomes. This literature study analyzes machine learning methods suitable for predicting capture fisheries production and identifies variables affecting production. Findings indicate neural networks are the most widely used predictive approach, while random forest and linear logistics yield better accuracy results, resulting in 12 determining variables.","JISA (JurnalInformatika dan Sains) Vol. 06, No. 01, June 2023  \ne-ISSN: 2614-8404  \np-ISSN : 2776-3234  \nA Study of Prediction Model for Capture Fisheries Production in Indonesian Sea Waters Using Machine Learning  \nGanjar Adi Pradana  \nProgram Studi Perangkat Lunak Sistem Informasi, Jurusan Manajemen Sistem Informasi, Fakultas Pascasarjana, Universitas Gunadarma  \nEmail: [georgius_ganjar@yahoo.co.id](georgius_ganjar@yahoo.co.id)  \nAbstract − The potential for capture fisheries in Indonesia is a priceless wealth. This wealth has not been explored optimally. Fisheries resources are included in the category of renewable resources whose sustainability needs to be considered. This is important in maintaining food security which will increase over time, due to population growth. Capture Fisheries Production Prediction Model is needed to find out what determining variables affect capture fisheries production. There are many methods for predicting, the method that is widely used today is using machine learning since it ability to handle complex jobs with large input data. This research is a literature study, which aims to: (1) identify and analyze machine learning methods that are suitable for predicting capture fisheries production, and (2) identify variables that can affect capture fisheries production. The results of the study show that the Neural Network method is most widely used as a predictive model. In addition, the Random Forest and Linear Logistics methods provide better accuracy results. The results of the study also succeeded in finding 12 determining variables for the capture fisheries production prediction model.  \nKeywords – Capture Fisheries Production, Machine Learning, and Prediction Models.  \nI. INTRODUCTION  \nIndonesia is the largest archipelagic country in the world. The great marine and fisheries potential is a priceless wealth [1] . However, this wealth has not been explored optimally, especially capture fisheries resources. Fisheries resources are included in the category of renewable resources, then the question often arises of how to maximize the potential of these fishery resources without causing negative impacts in the future. This is important in maintaining food security which will increase over time, due to population growth.  \nSustainability is the key in fisheries development which is expected through wise management to improve the condition of resources and the welfare of the fishing community itself [1, 2] . The main problem is structure of capture fisheries in Indonesia that is still dominated by small-scale fishermen, this affects the amount of production of the main commodities. In addition, Illegal, Unreported and Unregulated Fishing (IUUF) is the biggest threat to the sustainability [3] . In fishing activities at sea, there are factors that can affect the number of catches [2, 4, 5, 7]. Thus it is necessary to know the factors that influence fisheries production. After knowing these factors, analysis and prediction of capture fisheries production can be carried out. This allows stakeholders to receive input to make plans and policies to increase production in this sector.  \nPrediction models are one of the strategies that are commonly used in most companies or organizations in the world to plan their work before it actually happens. The essence of forecasting is predicting future events based on past patterns and applying judgment to the projections. To carry out the assessment process with lots of data, we need a system that is able to predict in order to increase  \neffectiveness. There are many methods for predicting, the method that is widely used today is using machine learning. Machine Learning can be used as a tool to analyze big data, find patterns in the past, to make predictions for the future. The Machine Learning method was chosen in this study because it can handle very complex jobs with large amounts of input data. This can offer a solution to predicting capture fisheries producti","cbCailEJKl8mGxPf","https://ap.wps.com/l/cbCailEJKl8mGxPf","pdf",766660,1,7,"English","en",105,"# Introduction\n## Research background and problem\n## Role of prediction models and machine learning\n# Research Methodology\n## Literature study stages\n## Literature identification and selection\n## Keywords and data sources","[{\"question\":\"Why is a capture fisheries production prediction model important in Indonesia?\",\"answer\":\"It supports sustainable capture fisheries planning by identifying variables that determine production and helps maintain food security as population increases.\"},{\"question\":\"Which machine learning method is reported as the most widely used for the prediction model?\",\"answer\":\"The neural network method is reported as the most widely used predictive model in the reviewed studies.\"},{\"question\":\"What accuracy-performing methods and key variables are identified by the study?\",\"answer\":\"Random forest and linear logistics are found to provide better accuracy results, and the study identifies 12 determining variables for the prediction model.\"}]","A Study of Prediction Model for Capture Fisheries Production in Indonesian Sea Waters Using Machine Learning | PDF",1785817714,18,{"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},"a-study-of-prediction-model-for-capture-fisheries-production-in-indonesian-sea-waters-using-machine-learning","",{"@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/a-study-of-prediction-model-for-capture-fisheries-production-in-indonesian-sea-waters-using-machine-learning/123627/",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},"Why is a capture fisheries production prediction model important in Indonesia?","Question",{"text":75,"@type":76},"It supports sustainable capture fisheries planning by identifying variables that determine production and helps maintain food security as population increases.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning method is reported as the most widely used for the prediction model?",{"text":80,"@type":76},"The neural network method is reported as the most widely used predictive model in the reviewed studies.",{"name":82,"@type":73,"acceptedAnswer":83},"What accuracy-performing methods and key variables are identified by the study?",{"text":84,"@type":76},"Random forest and linear logistics are found to provide better accuracy results, and the study identifies 12 determining variables for the prediction model.","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},[93,97,101,105,110,115,119,122,127,130,134],{"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":21,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]