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Penelitian ini memprediksi financial distress berdasarkan rasio-rasio keuangan dari laporan keuangan bulanan salah satu bank konvensional, lalu menentukan rasio yang paling berpengaruh. Model machine learning yang digunakan meliputi Logistic Regression, Support Vector Machine, dan Random Forest. Hasil analisis menunjukkan Random Forest menjadi model terbaik dengan akurasi 96,77%, dan rasio Total Asset Turnover paling memengaruhi financial distress.",{"@graph":63,"@context":124},[64,81,103],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,72,75,78],{"item":68,"name":69,"@type":70,"position":71},"https://docshare.wps.com","Home","ListItem",1,{"item":73,"name":9,"@type":70,"position":74},"https://docshare.wps.com/id/document/",2,{"item":76,"name":31,"@type":70,"position":77},"https://docshare.wps.com/id/document/penelitian-laporan/",3,{"item":79,"name":59,"@type":70,"position":80},"https://docshare.wps.com/id/document/prediction-of-financial-distress-in-a-conventional-bank-using-machine-learning/126675/",4,{"url":79,"name":59,"@type":82,"image":83,"author":88,"headline":59,"publisher":91,"fileFormat":94,"inLanguage":57,"description":61,"dateModified":95,"datePublished":96,"encodingFormat":94,"isAccessibleForFree":97,"interactionStatistic":98},"DigitalDocument",{"url":84,"@type":85,"width":86,"height":87},"https://docshare.wps.com/thumbnails/prediction-of-financial-distress-in-a-conventional-bank-using-machine-learning/126675.png","ImageObject",300,407,{"name":89,"@type":90},"Lucas Martin","Person",{"url":68,"name":92,"@type":93},"DocShare","Organization","application/pdf","2026-09-18","2026-08-05",true,{"@type":99,"interactionType":100,"userInteractionCount":102},"InteractionCounter",{"@type":101},"ViewAction",7,{"@type":104,"mainEntity":105},"FAQPage",[106,112,116,120],{"name":107,"@type":108,"acceptedAnswer":109},"Apa tujuan utama penelitian ini?","Question",{"text":110,"@type":111},"Menentukan prediksi financial distress pada salah satu bank konvensional berdasarkan rasio keuangan, sekaligus mengidentifikasi rasio yang paling berpengaruh.","Answer",{"name":113,"@type":108,"acceptedAnswer":114},"Model machine learning apa saja yang digunakan untuk prediksi?",{"text":115,"@type":111},"Penelitian menggunakan Logistic Regression, Support Vector Machine, dan Random Forest.",{"name":117,"@type":108,"acceptedAnswer":118},"Model mana yang memberikan hasil terbaik dan berapa akurasinya?",{"text":119,"@type":111},"Random Forest menjadi model terbaik dengan akurasi sebesar 96,77% dalam memprediksi financial distress.",{"name":121,"@type":108,"acceptedAnswer":122},"Rasio keuangan apa yang paling berpengaruh terhadap financial distress menurut hasil penelitian?",{"text":123,"@type":111},"Rasio Total Asset Turnover merupakan rasio yang sangat berpengaruh terhadap financial distress berdasarkan model terbaik.","https://schema.org",{"og:url":79,"og:type":126,"og:title":59,"og:site_name":92,"og:description":61},"article",{"robots":128,"canonical":79},"index,follow",{"doc_id":130,"site_id":56},126675,1785934172,{"code":4,"msg":5,"data":133},{"doc_id":130,"user_id":134,"nickname":89,"user_avatar":135,"doc_module":4,"category_id":30,"category_name":31,"doc_title":59,"doc_description":61,"doc_content":136,"file_id":137,"file_url":138,"file_type":139,"file_size":140,"view_count":102,"is_deleted":4,"is_public":71,"is_downloadable":71,"audit_status":71,"page_count":141,"language":142,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":143,"faqs":144,"seo_title":145,"seo_description":61,"update_tm":131,"read_time":146},962084925502,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","Received 11th March 2023 Accepted 21st March 2023 Published 31st July 2023  \nOpen Access  \nDOI:  \n10.35472/indojam.v3i1.1284  \nPrediksi Finansial Distress pada Salah Satu Bank Konvensional Menggunakan Machine Learning  \nFuji Lestari *a  \na Program Studi Sains Aktuaria, Jurusan Sains, Intitut Teknologi Sumatera  \n*[Corresponding E-mail:](Corresponding E-mail: fuji.lestari@at.itera.ac.id)[ f](Corresponding E-mail: fuji.lestari@at.itera.ac.id)[uji.lestari@at.itera.ac.id](Corresponding E-mail: fuji.lestari@at.itera.ac.id)  \nAbstract: Financial distress is when a company experiences a shortage or insufficient funds to run the company. Prediction of financial distress is needed to prevent bankruptcy. In this study, financial distress predictions were made based on financial ratios obtained from monthly financial reports from a bank convention, after which the proportion that had the most influence on financial distress was determined. The models used in this study are several machine learning models, namely, Logistic Regression, Support Vector Machine, and Random Forest. Based on the analysis results, the best model for predicting financial pressure is the Random Forest Model, with an accuracy of 96.77%. Based on the best model obtained, namely the Random Forest, it can be determined that the ratio that is very influential on financial distress is the ratio of Total Asset Turnover.  \nKeywords: Financial Distress, Machine Learning, Random Forest, Prediction  \nAbstrak: Financial distress merupakan suatu keadaan perusahaan saat mengalami kekurangan atauketidakcukupan dana dalam menjalankan perusahaan. Prediksi financial distress sangat untuk dibutuhkan untuk mencegah adanya kebangkrutan. Pada penelitian ini, dilakukan prediksi finansial distress berdasarkan rasio-rasiokeuangan yang diperoleh dari laporan keuangan bulanan dari sebuah bank konvensional, setelah itu ditentukanrasio yang paling berpengaruh terhadap financial distress. Model yang yang digunakan dalam penelitian ini adalah beberapa model machine learning yaitu, Logistic Regression, Support Vector Machine, dan Random Forest. Berdasarkan hasil analisis, model terbaik dalam memprediksi financial ditress adalah Model Random Forest dengan akurasi sebesar 96,77% . Berdasarkan model terbaik yang diperoleh, yaitu Random Forest, dapat ditentukan rasio yang sangat berpengaruh pada financial distress adalah rasio Total Asset Turnover.  \nKata Kunci: Financial Distress, Machine Learning, Random Forest, Prediksi  \nPendahuluan  \nPerekonomian merupakan salah satu komponen penting dalam melihat pertumbuhan suatu negara. Pertumbuhan perekonomian yang baik mengimplikasikan pertumbuhan negara yang baik pula. Namun, perekonomian negara saat ini sedangtidak dalam kondisi baik. Hal ini terlihat dari kondisi proyeksi perekonomian Indonesia yang sedang mangalami trend yang turun. Berdasarkan proyeksi dari World Economic Outlook IMF pada tahun 2022, ekonomi dunia mengalami pertumbuhan ekonomisebesar 3,2% dan tahun berikutnya pertumbuhanekonomi dunia juga diperkirakan akan semakin  \nmelemah di angka 2,7% . Hal ini dipengaruhi olehinflasi yang cukup tinggi sehingga pertumbuhanekonomi dunia mengalami penurunan. Akibatnya, keadaan ini dapat merepresentasikan kondisikeuangan global yang tidak baik.  \nKeadaan ekonomi tersebut mempengaruhi banyak industri yang mendukung dalam meningkatkan perekonomian negara. Salah satunya adalah industriperbankan. Perbankan mempunyai peranan penting dalam perekonomian sebagai lembaga intermediasi yang menyalurkan dana masyakarat ke dalaminvestasi aset produktif yang akan mendorongproduktivitas sektor riil, akumulasi kapital, dan pertumbuhan output agregat [1]. Berdasarkan data  \nBadan Pusat Statistik (BPS), sektor jasa keuangan danasuransi berkontribusi 4,34% terhadap Produk Domestik Bruto nasional yang nilai totalnya mencapai Rp16,97 kuadriliun pada 2021 [2] .  \nKondisi ekonomi yang sedang melemah akan berdampak langsung pada industri perbankan. Olehkarena itu perlu dilak","cbCaib9gUNF6gbh7","https://ap.wps.com/l/cbCaib9gUNF6gbh7","pdf",692740,5,"Indonesian","# Pendahuluan\n## Latar belakang kondisi ekonomi dan peran perbankan\n## Kebutuhan analisis rasio keuangan untuk pencegahan financial distress\n# Metode\n## Logistic Regression\n## Support Vector Machine\n## Random Forest (kerangka model)","[{\"question\":\"Apa tujuan utama penelitian ini?\",\"answer\":\"Menentukan prediksi financial distress pada salah satu bank konvensional berdasarkan rasio keuangan, sekaligus mengidentifikasi rasio yang paling berpengaruh.\"},{\"question\":\"Model machine learning apa saja yang digunakan untuk prediksi?\",\"answer\":\"Penelitian menggunakan Logistic Regression, Support Vector Machine, dan Random Forest.\"},{\"question\":\"Model mana yang memberikan hasil terbaik dan berapa akurasinya?\",\"answer\":\"Random Forest menjadi model terbaik dengan akurasi sebesar 96,77% dalam memprediksi financial distress.\"},{\"question\":\"Rasio keuangan apa yang paling berpengaruh terhadap financial distress menurut hasil penelitian?\",\"answer\":\"Rasio Total Asset Turnover merupakan rasio yang sangat berpengaruh terhadap financial distress berdasarkan model terbaik.\"}]","Prediksi Finansial Distress pada Salah Satu Bank Konvensional Menggunakan Machine Learning | PDF",8]