[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-id-113":3,"doc-seo-126719-113":53,"doc-detail-126719-id":128},{"code":4,"msg":5,"data":6},0,"success",[7,13,17,21,25,29,33,37,41,45,49],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},55,"Document","Agama & Spiritualitas",60,"religion-spirituality",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":11,"slug":16},48,"Cerita & Novel","story-novel",{"id":18,"doc_module":4,"doc_module_name":9,"category_name":19,"show_sort_weight":11,"slug":20},56,"Gaya Hidup","lifestyle",{"id":22,"doc_module":4,"doc_module_name":9,"category_name":23,"show_sort_weight":11,"slug":24},51,"Komik","comic",{"id":26,"doc_module":4,"doc_module_name":9,"category_name":27,"show_sort_weight":11,"slug":28},53,"Layanan Kesehatan","healthcare",{"id":30,"doc_module":4,"doc_module_name":9,"category_name":31,"show_sort_weight":11,"slug":32},54,"Penelitian & Laporan","research-report",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":11,"slug":36},49,"Sastra","literature",{"id":38,"doc_module":4,"doc_module_name":9,"category_name":39,"show_sort_weight":11,"slug":40},52,"Teknologi","technology",{"id":42,"doc_module":4,"doc_module_name":9,"category_name":43,"show_sort_weight":11,"slug":44},50,"Ujian","exam",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":47,"show_sort_weight":11,"slug":48},57,"Umum","general",{"id":50,"doc_module":4,"doc_module_name":9,"category_name":51,"show_sort_weight":4,"slug":52},181,"Formulir","formulir",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":121,"head_meta":123,"extra_data":125,"updated_unix":127},113,"id","comparison-of-the-best-machine-learning-model-to-predict-corrosion-inhibition-capability-of-benzimidazole-compounds","Perbandingan Model Machine Learning Terbaik untuk Memprediksi Kemampuan Penghambatan Korosi oleh Senyawa Benzimidazole","","Penelitian ini merupakan studi eksperimen untuk menyelidiki inhibitor korosi dari senyawa benzimidazole dengan pendekatan machine learning (ML). Korosi menimbulkan kerugian besar melalui hilangnya material konstruksi, gangguan keselamatan kerja, serta pencemaran lingkungan akibat produk korosi. ML digunakan untuk memperoleh model dengan akurasi terbaik agar prediksi terhadap kemampuan penghambatan korosi lebih relevan dan tepat. Evaluasi dilakukan pada algoritma ML linear dan non-linear menggunakan k-fold cross-validation dengan metrik R2 dan RMSE, dan hasilnya menunjukkan AdaBoost regressor (ADA) sebagai model dengan performa prediksi terbaik pada dataset senyawa benzimidazole dari literatur.",{"@graph":63,"@context":120},[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/comparison-of-the-best-machine-learning-model-to-predict-corrosion-inhibition-capability-of-benzimidazole-compounds/126719/",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/comparison-of-the-best-machine-learning-model-to-predict-corrosion-inhibition-capability-of-benzimidazole-compounds/126719.png","ImageObject",300,407,{"name":89,"@type":90},"Ava Thompson","Person",{"url":68,"name":92,"@type":93},"DocShare","Organization","application/pdf","2026-09-20","2026-08-05",true,{"@type":99,"interactionType":100,"userInteractionCount":102},"InteractionCounter",{"@type":101},"ViewAction",10,{"@type":104,"mainEntity":105},"FAQPage",[106,112,116],{"name":107,"@type":108,"acceptedAnswer":109},"Mengapa machine learning digunakan untuk memprediksi kemampuan penghambatan korosi?","Question",{"text":110,"@type":111},"Machine learning dipakai untuk memperoleh model dengan akurasi terbaik sehingga prediksi kemampuan penghambatan korosi menjadi lebih relevan dan akurat terhadap suatu material.","Answer",{"name":113,"@type":108,"acceptedAnswer":114},"Bagaimana metode evaluasi performa model ML dilakukan?",{"text":115,"@type":111},"Penelitian mengevaluasi algoritma ML linear dan non-linear menggunakan k-fold cross-validation untuk mengukur performa model.",{"name":117,"@type":108,"acceptedAnswer":118},"Model ML apa yang menghasilkan performa prediksi terbaik dan berdasarkan metrik apa?",{"text":119,"@type":111},"AdaBoost regressor (ADA) menunjukkan performa prediksi terbaik, dinilai menggunakan metrik coefficient of determination (R2) dan root mean square error (RMSE).","https://schema.org",{"og:url":79,"og:type":122,"og:title":59,"og:site_name":92,"og:description":61},"article",{"robots":124,"canonical":79},"index,follow",{"doc_id":126,"site_id":56},126719,1785934396,{"code":4,"msg":5,"data":129},{"doc_id":126,"user_id":130,"nickname":89,"user_avatar":131,"doc_module":4,"category_id":30,"category_name":31,"doc_title":59,"doc_description":61,"doc_content":132,"file_id":133,"file_url":134,"file_type":135,"file_size":136,"view_count":102,"is_deleted":4,"is_public":71,"is_downloadable":71,"audit_status":71,"page_count":137,"language":138,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":139,"faqs":140,"seo_title":141,"seo_description":61,"update_tm":127,"read_time":142},962084925782,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","Perbandingan Model Machine Learning Terbaik untuk Memprediksi Kemampuan Penghambatan Korosi oleh  \nSenyawa Benzimidazole  \nComparison of the Best Machine Learning Model to Predict Corrosion Inhibition Capability of Benzimidazole Compounds  \nCornellius Adryan Putra Sumarjono 1, Muhamad Akrom2, Gustina Alfa Trisnapradika3  \n1,2,3Prodi Teknik Informatika, Universitas Dian Nuswantoro [E-mail:](E-mail:1 111202012994@mhs.dinus.ac.id)[1](E-mail:1 111202012994@mhs.dinus.ac.id)[ 111202012994@mhs.dinus.ac.id](E-mail:1 111202012994@mhs.dinus.ac.id), [2](2 m.akrom@dsn.dinus.ac.id)[ m.akrom@dsn.dinus.ac.id](2 m.akrom@dsn.dinus.ac.id), [3](3gustina.alfa@dsn.dinus.ac.id)[gustina.alfa@dsn.dinus.ac.id](3gustina.alfa@dsn.dinus.ac.id)  \nAbstrak  \nPenelitian ini merupakan studi eksperimen untuk melakukan penyelidikan inhibitor korosi olehsenyawa Benzimidazole dengan melakukan pendekatan machine learning (ML) . Karena korosi menyebabkan banyak kerugian yang timbul karena kehilangan material konstruksi, keselamatankerja dan pencemaran lingkungan akibat produk korosi dalam bentuk senyawa yang mencemarkan lingkungan. Melakukan pendekatan ML adalah untuk mendapatkan model akurasi yang terbaik sehingga dapat digunakan untuk memprediksi dengan relevan dan akurat terhadapsuatu material. Dalam penelitian ini, kami mengevaluasi algoritma ML dengan metode linear dan nonlinear dengan menggunakan metode k-fold cross-validation untuk membantu dalam mengukur performa model ML. Mengacu pada metrik coefficient of determination (R2) dan root mean square error (RMSE), kami menyimpulkan bahwa model AdaBoost regressor (ADA) merupakan model dengan performa prediksi terbaik dari eksperimen yang kami lakukan dari literatur untuk dataset senyawa benzimidazole. Keberhasilan model penelitian ini menawarkan perspektif baru tentang kemampuan model ML untuk memprediksi penghambat korosi yang efektif.  \nKata Kunci: Machine learning, korosi, cross-validation, benzimidazole, adaboost regressor  \nAbstract  \nThis research is an experimental study to investigate corrosion inhibitors by Benzimidazole compounds using a machine learning (ML) approach. Corrosion causes many losses arising from the loss of construction materials, work safety, and environmental pollution due to corrosion products in the form of compounds that pollute the environment. Taking an ML approach is to get the best accuracy model so that it can be used to make relevant and accurate predictions about a material. In this research, we evaluate ML algorithms with linear and non-linear methods using the k-fold cross-validation method to help measure the performance of the ML model. Referring to the coefficient of determination (R2) and root mean square error (RMSE) metrics, we conclude that the AdaBoost regressor (ADA) model is the model with the best predictive performance from the experiments we conducted from the literature for the benzimidazole compound dataset. The success of this research model offers a new perspective on the ability of ML models to predict effective corrosion inhibitors.  \nKeywords: Machine learning, corrosion, cross-validation, benzimidazole, AdaBoost regressor  \n1. PENDAHULUAN  \nKorosi merupakanproses penurunan ataupeluruhan material yang disebabkan oleh reaksi kimia antara logam dan lingkungan dimana terdapat banyak zat korosif yang menyebabkanterjadinya korosi sekitarnya [1] . Proses korosi melibatkan oksidasi logam oleh oksigen di udara atau zat korosif lainnya, yang menghasilkan produk korosi seperti oksida, hidroksida, atau garam logam. Reaksi korosi ini dapat mempengaruhi kualitas dan kinerja material, mengurangi umur  \npakai, dan menyebabkan kerugian ekonomi yang signifikan [2], [3] . Beberapa faktor yang mempengaruhi laju korosi meliputijenis logam yang terlibat, sifat lingkungan korosif (misalnya, kelembaban, pH, suhu, konsentrasi zat korosif), dan faktor-faktor lain seperti tegangan mekanis atau keausan gesekan [4]. Proses korosi juga dapat dipercepat oleh adanya galvanik (kontak a","cbCaiouG6q1kFmY7","https://ap.wps.com/l/cbCaiouG6q1kFmY7","pdf",562062,8,"Indonesian","# Pendahuluan\n## Latar belakang korosi dan faktor yang memengaruhi laju korosi\n## Senyawa benzimidazole dan penggunaannya sebagai inhibitor korosi\n## Kesenjangan penelitian serta pendekatan QSPR berbasis machine learning\n## Studi terdahulu dan perbandingan model ML","[{\"question\":\"Mengapa machine learning digunakan untuk memprediksi kemampuan penghambatan korosi?\",\"answer\":\"Machine learning dipakai untuk memperoleh model dengan akurasi terbaik sehingga prediksi kemampuan penghambatan korosi menjadi lebih relevan dan akurat terhadap suatu material.\"},{\"question\":\"Bagaimana metode evaluasi performa model ML dilakukan?\",\"answer\":\"Penelitian mengevaluasi algoritma ML linear dan non-linear menggunakan k-fold cross-validation untuk mengukur performa model.\"},{\"question\":\"Model ML apa yang menghasilkan performa prediksi terbaik dan berdasarkan metrik apa?\",\"answer\":\"AdaBoost regressor (ADA) menunjukkan performa prediksi terbaik, dinilai menggunakan metrik coefficient of determination (R2) dan root mean square error (RMSE).\"}]","Perbandingan Model Machine Learning Terbaik untuk Memprediksi Kemampuan Penghambatan Korosi oleh Senyawa Benzimidazole | PDF",12]