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Invoice sebagai dokumen resmi menentukan apakah transaksi dapat diproses segera atau mengalami penundaan. Kajian empiris mengenai faktor yang memengaruhi status pembayarannya masih terbatas. Penelitian ini menganalisis pengaruh jenis perusahaan, jenis pengadaan, dan nilai invoice menggunakan regresi logistik serta random forest. Hasil menunjukkan nilai invoice dan jenis pengadaan berpengaruh signifikan, dengan random forest lebih akurat (94,47%) dibanding regresi logistik (59,30%).",{"@graph":51,"@context":100},[52,68,83],{"@type":53,"itemListElement":54},"BreadcrumbList",[55,59,62,65],{"item":56,"name":57,"@type":58,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":60,"name":10,"@type":58,"position":61},"https://docshare.wps.com/id/template/",2,{"item":63,"name":15,"@type":58,"position":64},"https://docshare.wps.com/id/template/formulir/",3,{"item":66,"name":47,"@type":58,"position":67},"https://docshare.wps.com/id/template/invoice-payment-status-classification-for-banks-using-logistic-regression-and-random-forest/235631/",4,{"url":66,"name":47,"@type":69,"author":70,"headline":47,"publisher":73,"fileFormat":76,"inLanguage":45,"description":49,"dateModified":77,"datePublished":77,"encodingFormat":76,"isAccessibleForFree":78,"interactionStatistic":79},"DigitalDocument",{"name":71,"@type":72},"Aladdin","Person",{"url":56,"name":74,"@type":75},"DocShare","Organization","application/pdf","2026-09-11",true,{"@type":80,"interactionType":81,"userInteractionCount":4},"InteractionCounter",{"@type":82},"ViewAction",{"@type":84,"mainEntity":85},"FAQPage",[86,92,96],{"name":87,"@type":88,"acceptedAnswer":89},"Penelitian ini menganalisis faktor apa saja untuk status pembayaran invoice bank?","Question",{"text":90,"@type":91},"Penelitian menganalisis faktor berdasarkan jenis perusahaan, jenis pengadaan, dan nilai invoice.","Answer",{"name":93,"@type":88,"acceptedAnswer":94},"Metode apa yang digunakan untuk membandingkan performa klasifikasi status pembayaran?",{"text":95,"@type":91},"Metode yang digunakan adalah regresi logistik dan random forest untuk membandingkan performa klasifikasi.",{"name":97,"@type":88,"acceptedAnswer":98},"Bagaimana hasil akurasi random forest dibanding regresi logistik?",{"text":99,"@type":91},"Random forest menghasilkan akurasi 94,47%, sedangkan regresi logistik sebesar 59,30%, sehingga random forest lebih unggul.","https://schema.org",{"og:url":66,"og:type":102,"og:title":47,"og:site_name":74,"og:description":49},"article",{"robots":104,"canonical":66},"index,follow",{"doc_id":106,"site_id":44},235631,1789099325,{"code":4,"msg":5,"data":109},{"doc_id":106,"user_id":110,"nickname":71,"user_avatar":111,"doc_module":9,"category_id":14,"category_name":15,"doc_title":47,"doc_description":49,"doc_content":112,"file_id":113,"file_url":114,"file_type":115,"file_size":116,"view_count":4,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":117,"language":118,"language_code":45,"site_id":44,"html_lang":45,"table_of_contents":119,"faqs":120,"seo_title":121,"seo_description":49,"update_tm":107,"read_time":122},2336478503145,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Sistemasi:Jurnal Sistem Informasi ISSN:2302-8149  \nVolume 14, Nomor 5, 2025: 2450-2463 e-ISSN:2540-9719  \nKlasifikasi Status Pembayaran Invoice Bank Menggunakan Regresi Logistik dan Random Forest  \nPayment Status Classification Invoice Bank Using Logistic Regression and  \nRandom Forest  \n1Farah Anindia Putri*, 2 Mujiati Dwi Kartikasari  \n1,2Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Islam  \nIndonesia  \nJalan Kaliurang Km 14,5 Sleman, Yogyakarta, Indonesia  \n*e-mail: [21611162@students.uii.ac.id](21611162@students.uii.ac.id)  \n(received: 26 June 2025, revised: 19 July 2025, accepted: 20 July 2025)  \nAbstrak  \nManajemen pembayaran merupakan aspek penting dalam operasional keuangan bank, khususnya dalam memastikan kelancaran transaksi pengadaan barang dan jasa. Invoice sebagai dokumen resmi memiliki peran dalam menentukan apakah suatu transaksi dapat segera diproses atau mengalami penundaan. Meskipun peran invoice sangat sentral, kajian empiris mengenai faktor-faktor yang memengaruhi status pembayarannya masih terbatas, terutama dalam konteks institusi perbankan. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi status pembayaran invoice berdasarkan jenis perusahaan, jenis pengadaan, dan nilai invoice. Metode yang digunakan meliputi regresi logistik dan random forest untuk membandingkan performa klasifikasi kedua pendekatan. Hasil analisis menunjukkan bahwa jenis pengadaan dan nilai invoice berpengaruh signifikan terhadap status pembayaran, dengan nilai invoice sebagai variabel paling dominan berdasarkan p-value. Pada model random forest, nilai invoice juga menunjukkan tingkat kepentingan tertinggi. Dari sisi akurasi, random forest memberikan hasil yang lebih unggul dengan akurasi sebesar 94,47%, dibandingkan regresilogistik sebesar 59,30% . Meskipun keduanya memiliki nilai presisi yang hampir sama (sekitar 97%), random forest mencatat recall sebesar 97,41% dan F1-score yang lebih tinggi dibandingkan regresilogistik (recall 69,19%). Temuan ini menunjukkan bahwa random forest merupakan metode yang lebih efektif dalam memprediksi status pembayaran dan berpotensi mendukung pengambilan keputusan berbasis data dalam sistem manajemen pembayaran perbankan.  \nKata kunci: invoice, pembayaran, random forest, regresi logistik  \nAbstract  \nPayment management is an essential aspect of a bank’s financial operations, particularly in ensuring the smooth execution of procurement transactions for goods and services. The invoice, as an official document, plays a role in determining whether a transaction can be processed promptly or experiences a delay. Despite its central role, empirical research exploring the factors influencing invoice payment status remains limited, especially within the context of banking institutions. This study aims to analyze the factors that affect invoice payment status based on company type, procurement type, and invoice value. The methods employed include logistic regression and random forest to compare the classification performance of both approaches. The analysis reveals that procurement type and invoice value significantly influence payment status, with invoice value emerging as the most dominant variable based on the smallest p-value. In the random forest model, invoice value also ranks highest in terms of variable importance. In terms of accuracy, the random forest model outperforms logistic regression, achieving an accuracy of 94.47% compared to 59.30%. Although both methods yield similar precision (approximately 97%), random forest demonstrates a substantially higher recall (97.41%) and F1-score, whereas logistic regression records a recall of only 69.19%. These findings suggest that random forest is a more effective methodfor predicting payment status and holds strong potential for supporting datadriven decision-making in bank payment management systems.  \nKeywords: invoice, logistic regression, payment, random forest  \nSistemasi:Jurnal Sistem In","cbCaigfg9EnA0QLR","https://ap.wps.com/l/cbCaigfg9EnA0QLR","pdf",388036,14,"Indonesian","# Pendahuluan\n## Latar belakang dan peran bank\n## Peran invoice dalam sistem pembayaran\n## Status pembayaran dan kebutuhan analisis berbasis data","[{\"question\":\"Penelitian ini menganalisis faktor apa saja untuk status pembayaran invoice bank?\",\"answer\":\"Penelitian menganalisis faktor berdasarkan jenis perusahaan, jenis pengadaan, dan nilai invoice.\"},{\"question\":\"Metode apa yang digunakan untuk membandingkan performa klasifikasi status pembayaran?\",\"answer\":\"Metode yang digunakan adalah regresi logistik dan random forest untuk membandingkan performa klasifikasi.\"},{\"question\":\"Bagaimana hasil akurasi random forest dibanding regresi logistik?\",\"answer\":\"Random forest menghasilkan akurasi 94,47%, sedangkan regresi logistik sebesar 59,30%, sehingga random forest lebih unggul.\"}]","Klasifikasi Status Pembayaran Invoice Bank Menggunakan Regresi Logistik dan Random Forest | PDF",5]