[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122513-id":3,"doc-seo-122513-113":31,"detail-sidebar-cat-0-id-113":92},{"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":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},122513,962085571259,"Theodora","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",52,"Teknologi","SISTEM MONITORING BERBASIS IOT UNTUK PREDICTIVE MAINTENANCE GENERATOR SET MENGGUNAKAN MACHINE LEARNING - Tesis","Generator set merupakan komponen penting sebagai sumber listrik cadangan maupun utama. Pemeliharaan reaktif atau preventif yang bersifat manual sering kurang efisien dan rawan kesalahan sehingga memicu downtime tak terduga serta biaya operasional tinggi. Penelitian ini mengembangkan sistem predictive maintenance berbasis IoT dan machine learning untuk pemantauan kondisi genset secara real-time. ESP32 dan sensor mengumpulkan data tegangan, arus, temperatur, tekanan oli, putaran, getaran, level bahan bakar, dan jam operasional, lalu divisualisasikan melalui dashboard Node-RED. Tiga algoritma diuji; Random Forest unggul dengan akurasi 98,47%.","SISTEM MONITORING BERBASIS IOT UNTUK PREDICTIVE MAINTENANCE GENERATOR SET MENGGUNAKAN MACHINE LEARNING  \nTESIS  \nDisusun sebagai Salah Satu Syarat Menyelesaikan Program Studi Strata 2 pada Program Studi Magister Teknik Mesin Fakultas Teknik  \nOleh :  \nMADY DEKA APRILIYA  \nNIM. U100210010  \nPROGRAM STUDI MAGISTER TEKNIK MESIN FAKULTAS TEKNIK  \nUNIVERSITAS MUHAMMADIYAH SURAKARTA  \nSISTEM MONITORING BERBASIS IOT UNTUK PREDICTIVE MAINTENANCE GENERATOR SET MENGGUNAKAN MACHINE  \nLEARNING  \nMady Deka Apriliya, Supriyono, Joko Sedyono  \nFakultas Teknik, Universitas Muhammadiyah Surakarta, Jl. A. Yani Tromol Pos 1 Pabelan Kartasura, Surakarta, Jawa Tengah 57102, Indonesia  \n[U100210010@student.ums.ac.id](U100210010@student.ums.ac.id)  \nABSTRAK  \nGenerator set merupakan komponen penting dalam infrastruktur modern sebagaisumber listrik cadangan atau utama. Namun, pemeliharaan tradisional reaktif atau preventif seringkali tidak efisien dan rentan terhadap kesalahan manusia, yang dapat menyebabkan downtime tak terduga dan biaya operasional yang tinggi. Sebagai solusinya, penelitian ini mengusulkan pengembangan sistem predictive maintenance berbasis Internet of Things (IoT) dan Machine Learning untuk memantau kondisi genset secara real-time. Sistem ini dirancang menggunakan mikrokontroler ESP32 dan berbagai sensor untuk mengumpulkan data pentingseperti tegangan, arus, temperatur, tekanan oli, putaran mesin, getaran, level bahan bakar, dan jam operasional. Data yang terkumpul kemudian dikirim danditampilkan melalui web dashboard menggunakan platform Node-RED. Penelitian ini juga mengimplementasikan dan membandingkan tiga algoritma Machine Learning Random Forest (RF), Support Vector Machine (SVM), dan K-Nearest Neighbors (KNN) untuk memprediksi potensi kegagalan genset. Hasilnya, sistem monitoring berbasis IoT yang diimplementasikan menunjukkan kinerja stabil dan andal, dengan akurasi akuisisi data sensor yang memadai. Dari perbandingan model, algoritma Random Forest menunjukkan kinerja paling unggul denganakurasi keseluruhan mencapai 98,47% . Model ini sangat efektif dalam mengklasifikasikan kondisi Anomaly dan Normal, serta menunjukkan peningkatan signifikan dalam mendeteksi kelas Failure dengan sedikit false negatives. Sementara itu, model Support Vector Machine (SVM) dan K-Nearest Neighbors (KNN) memiliki akurasi sekitar 83%, tetapi menunjukkan kelemahan dalam mendeteksi kondisi Failure, di mana Support Vector Machine (SVM) hanya berhasil mendeteksi 42% dan K-Nearest Neighbors (KNN) 56% kasus kegagalan yang sebenarnya. Penelitian ini berhasil membuktikan bahwa system predictive maintenance berbasis Internet of Things (IoT) dan Machine Learning dengan model Random Forest sebagai prediktor, dapat meningkatkan keandalan genset melaluideteksi dini kegagalan, mengurangi downtime tak terencana, dan mengoptimalkan biaya pemeliharaan. Hal ini memberikan referensi penting untuk implementasi teknologi serupa dalam industri.  \nKata Kunci : Predictive Maintenance, Internet of Things, Machine Learning, Generator Set, Random Forest  \nIoT-B Monitoring System for Predictive Maintenance of Generator Sets  \nUsing Machine Learning  \nMady Deka Apriliya, Supriyono, Joko Sedyono Faculty of Engineering, Universitas Muhammadiyah Surakarta, Jl. A. Yani Tromol Pos 1 Pabelan Kartasura, Surakarta, Jawa Tengah 57102, Indonesia  \n[U100210010@student.ums.ac.id](U100210010@student.ums.ac.id)  \nABSTRACT  \nGenerator sets are a crucial component of modern infrastructure as a backup or primary power source. However, traditional reactive or preventive maintenance is often inefficient and prone to human error, which can lead to unexpected downtime and high operational costs. As a solution, this study proposes the development of a predictive maintenance (PdM) system based on the Internet of Things (IoT) and Machine Learning (ML) to monitor generator set conditions in real time. The system is designed using an ESP32 microcontroller and various sensors to collect critical data s","cbCaiuZXz7l6dlRw","https://ap.wps.com/l/cbCaiuZXz7l6dlRw","pdf",1300948,3,1,17,"Indonesian","id",113,"# Abstrak\n# Kata Pengantar\n# Sistem Monitoring Berbasis IoT dan Machine Learning\n## Perancangan Sistem dan Pengumpulan Data Sensor\n## Implementasi Web Dashboard Node-RED\n## Perbandingan Algoritma Machine Learning\n### Random Forest\n### Support Vector Machine (SVM)\n### K-Nearest Neighbors (KNN)","[{\"question\":\"Apa tujuan penelitian sistem monitoring ini?\",\"answer\":\"Mengembangkan sistem predictive maintenance berbasis IoT dan machine learning untuk memantau kondisi generator set secara real-time serta mendeteksi potensi kegagalan lebih dini.\"},{\"question\":\"Data apa saja yang dikumpulkan oleh sensor pada sistem?\",\"answer\":\"Sistem mengumpulkan tegangan, arus, temperatur, tekanan oli, putaran mesin, getaran, level bahan bakar, dan jam operasional.\"},{\"question\":\"Algoritma machine learning apa yang menunjukkan kinerja terbaik dan berapa akurasinya?\",\"answer\":\"Random Forest menunjukkan kinerja terbaik dengan akurasi keseluruhan 98,47% serta efektif mengklasifikasikan kondisi Anomaly dan Normal.\"}]","SISTEM MONITORING BERBASIS IOT UNTUK PREDICTIVE MAINTENANCE GENERATOR SET MENGGUNAKAN MACHINE LEARNING - Tesis | PDF",1785811025,26,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"iot-based-monitoring-system-for-predictive-maintenance-of-generator-sets-using-machine-learning-thesis","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/id/document/","Document",2,{"item":50,"name":12,"@type":44,"position":20},"https://docshare.wps.com/id/document/teknologi/",{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/id/document/iot-based-monitoring-system-for-predictive-maintenance-of-generator-sets-using-machine-learning-thesis/122513/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-17","2026-08-04",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Apa tujuan penelitian sistem monitoring ini?","Question",{"text":76,"@type":77},"Mengembangkan sistem predictive maintenance berbasis IoT dan machine learning untuk memantau kondisi generator set secara real-time serta mendeteksi potensi kegagalan lebih dini.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Data apa saja yang dikumpulkan oleh sensor pada sistem?",{"text":81,"@type":77},"Sistem mengumpulkan tegangan, arus, temperatur, tekanan oli, putaran mesin, getaran, level bahan bakar, dan jam operasional.",{"name":83,"@type":74,"acceptedAnswer":84},"Algoritma machine learning apa yang menunjukkan kinerja terbaik dan berapa akurasinya?",{"text":85,"@type":77},"Random Forest menunjukkan kinerja terbaik dengan akurasi keseluruhan 98,47% serta efektif mengklasifikasikan kondisi Anomaly dan Normal.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,99,103,107,111,115,119,123,125,129,133],{"id":95,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},55,"Agama & Spiritualitas",60,"religion-spirituality",{"id":100,"doc_module":4,"doc_module_name":47,"category_name":101,"show_sort_weight":97,"slug":102},48,"Cerita & Novel","story-novel",{"id":104,"doc_module":4,"doc_module_name":47,"category_name":105,"show_sort_weight":97,"slug":106},56,"Gaya Hidup","lifestyle",{"id":108,"doc_module":4,"doc_module_name":47,"category_name":109,"show_sort_weight":97,"slug":110},51,"Komik","comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":97,"slug":114},53,"Layanan Kesehatan","healthcare",{"id":116,"doc_module":4,"doc_module_name":47,"category_name":117,"show_sort_weight":97,"slug":118},54,"Penelitian & Laporan","research-report",{"id":120,"doc_module":4,"doc_module_name":47,"category_name":121,"show_sort_weight":97,"slug":122},49,"Sastra","literature",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":97,"slug":124},"technology",{"id":126,"doc_module":4,"doc_module_name":47,"category_name":127,"show_sort_weight":97,"slug":128},50,"Ujian","exam",{"id":130,"doc_module":4,"doc_module_name":47,"category_name":131,"show_sort_weight":97,"slug":132},57,"Umum","general",{"id":134,"doc_module":4,"doc_module_name":47,"category_name":135,"show_sort_weight":4,"slug":136},181,"Formulir","formulir"]