[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118854-en":3,"doc-seo-118854-105":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},118854,8796095360427,"Lucas Martin","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","Preventing recession through GDP growth prediction - A classical and machine learning classification approach","Classification methods support prediction and analysis by assigning data to predefined categories. This research compares classical and machine learning classifiers using regional GDP data from 2019–2020, covering periods before and during the COVID-19 pandemic. Predictor variables include workers’ percentage, foreign direct investment (PMA), regional revenue (PAD), DAU, DBH, and a COVID-19 dummy. Logistic regression, neural network (NN), random forest, SVM, and BMA are evaluated, with NN achieving 100% accuracy on training and testing. COVID-19 and PMA are the most influential predictors across models.","Contents lists available online at TALENTA Publisher  \nDATA SCIENCE: JOURNAL OF COMPUTING AND APPLIED INFORMATICS (JoCAI)  \nJournal homepage: [https://talenta.usu.ac.id/JoCAI](https://talenta.usu.ac.id/JoCAI)  \n| Preventing recession through GDP growth prediction: A classical and machine learning classification approach\u003Cbr>Prilyandari Dina Saputri 1, Arin Berliana Angrenani2, Ika Nur Laily Fitriana2\u003Cbr>1 Department of Actuarial Science, Institut Teknologi Sepuluh Nopember\u003Cbr>2 Department of Statistics, Institut Teknologi Sepuluh Nopember\u003Cbr>[email:](email:1 prilyandaridina@its.ac.id)[1](email:1 prilyandaridina@its.ac.id)[ prilyandaridina@its.ac.id](email:1 prilyandaridina@its.ac.id), [2](2 aberlianaa@gmail.com)[ aberlianaa@gmail.com](2 aberlianaa@gmail.com) , [2](2 ikanurlaily97@gmail.com)[ ikanurlaily97@gmail.com](2 ikanurlaily97@gmail.com) |  |\n| --- | --- |\n| A R T I C L E I N F O Article history:\u003Cbr>Received 19 December 2022 Revised 18 June 2023 Accepted 13 May 2023 Keywords:\u003Cbr>Accuracy COVID-19\u003Cbr>Data Classification\u003Cbr>Machine Learning Regional GDP\u003Cbr>Corresponding Author:\u003Cbr>[prilyandaridina@its.ac.id](prilyandaridina@its.ac.id) | A B S T R A C T\u003Cbr>Classification methods are a popular method applied in many various fields of science. This research proposed a comparison of classification methods using regional GDP data for 2019-2020, before and during the COVID-19 pandemic, by predictor variables; percentage of workers, foreign direct investment (PMA), regional revenue (PAD), general allocation fund (DAU), revenue sharing fund (DBH), and the dummy of COVID-19. Economic growth, most commonly using a gross regional domestic product, is experiencing a recession or acceleration, especially before and during the COVID-19 pandemic. To represent the effect of predictor factors on categorical response variables, different machine learning classification algorithms are used, namely logistic regression, neural network (NN), random forest, support vector machine (SVM), and bayesian model averaging (BMA) . Every classifier has its unique characteristic, performing wellin certain datasets but not in others. Hence, it is always a quest to find the best classifier to use for a certain dataset. The results are that all selected machine learning models can classify the regional GDP growth perfectly for the training data, but, NN model outperforms the other methods with an accuracy of 100% in training and testing data. COVID-19 and the PMA are the most significant variables predicting regional GDP growth for all models. Further research relating to interpretable machine learning, such as feature interaction, global surrogate, and Shapley values, is also necessary to predict regional GDP growth using machine learning methods. |\n| IEEE style in citing this article: [citation Heading]\u003Cbr>P D. Saputri, A. B. Anggrenani and I. N. L. Fitriana, \" Preventing recession through GDP growth prediction: A classical and machine learning 7classification approach,\" DATA SCIENCE: JOURNAL OF COMPUTING AND APPLIED INFORMATICS (JoCAI) , vol. 7, no. 2, pp. 51-68 , 2023. |  |\n\n1. Introduction  \nClassification is a data mining technicality that specifies classes to a data set to help with predictions and analysis. The classification is also a function to extract data in a group to base classes or groups. A classification task starts with a data group whose category tasks do know. The classification aims to truly predict the targeted status in the data and discover how that set of attributes reaches its conclusion [1]. Classification methods categorize data to use at their highest level of effectiveness and efficiency [2] .  \nClassification methods are a popular method applied in many various fields of science. Training data is used in classification models to develop a classification model that predicts the class label for a new sample. Classification model outputs might be discrete, as in a decision tree classifier, or continuous, as in a Naive Bayes classif","cbCaihOXslBG6Mnv","https://ap.wps.com/l/cbCaihOXslBG6Mnv","pdf",702912,1,17,"English","en",105,"# Introduction\n## Classification methods and machine learning models\n## Economic growth and GDP metrics\n## Regional GDP as a macroeconomic indicator","[{\"question\":\"Which data period and context are used to predict regional GDP growth?\",\"answer\":\"The study uses regional GDP data for 2019–2020, comparing conditions before and during the COVID-19 pandemic.\"},{\"question\":\"What predictor variables are used in the classification models?\",\"answer\":\"The predictors include percentage of workers, foreign direct investment (PMA), regional revenue (PAD), general allocation fund (DAU), revenue sharing fund (DBH), and a COVID-19 dummy variable.\"},{\"question\":\"Which classifier performs best and what accuracy does it achieve?\",\"answer\":\"The neural network (NN) model outperforms others, reaching 100% accuracy on both training and testing data.\"}]","Preventing recession through GDP growth prediction - A classical and machine learning classification approach | PDF",1785720630,43,{"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},"preventing-recession-through-gdp-growth-prediction-a-classical-and-machine-learning-classification-approach","",{"@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/preventing-recession-through-gdp-growth-prediction-a-classical-and-machine-learning-classification-approach/118854/",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","2026-08-03",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},"Which data period and context are used to predict regional GDP growth?","Question",{"text":75,"@type":76},"The study uses regional GDP data for 2019–2020, comparing conditions before and during the COVID-19 pandemic.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What predictor variables are used in the classification models?",{"text":80,"@type":76},"The predictors include percentage of workers, foreign direct investment (PMA), regional revenue (PAD), general allocation fund (DAU), revenue sharing fund (DBH), and a COVID-19 dummy variable.",{"name":82,"@type":73,"acceptedAnswer":83},"Which classifier performs best and what accuracy does it achieve?",{"text":84,"@type":76},"The neural network (NN) model outperforms others, reaching 100% accuracy on both training and testing data.","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"]