[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124120-id":3,"doc-seo-124120-113":31,"detail-sidebar-cat-0-id-113":96},{"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},124120,5909887256941,"Levi","https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc",52,"Teknologi","PENERAPAN MACHINE LEARNING UNTUK MEMANTAU KERUSAKAN KONTAINER PADA GATE TERMINAL PETIKEMAS MAKASSAR NEW PORT - Sistem deteksi kerusakan atap kontainer dengan YOLO","Penelitian ini merancang dan membangun sistem untuk memantau serta menentukan kerusakan atap kontainer secara otomatis sebelum kontainer masuk ke container yard. Pemantauan dilakukan di area gate menggunakan metode Machine Learning You Only Look Once (YOLO). Tiga jenis kerusakan yang dianalisis meliputi karat, lubang, dan penyok, yang umumnya dipicu kesalahan manusia, cuaca ekstrem, maupun benturan objek. Hasil menunjukkan akurasi deteksi 88,8% pagi, 90,9% siang, 87,7% sore, dan 83,6% malam, dengan performa lebih rendah pada malam akibat pencahayaan kurang optimal. Sistem real-time mampu menampilkan bukti dokumentasi dan terus memberi notifikasi untuk gate inspector.","PENERAPAN MACHINE LEARNING UNTUK MEMANTAU KERUSAKAN KONTAINERPADA GATE TERMINAL PETIKEMAS MAKASSAR NEW PORT  \nAbdul Kadir Muhammad1 ,*, Imran Habriansyah2, Putri Aulia. SN3,**, Mithahul Jannah4,**  \n1,2,4Jurusan Teknik Mesin Politeknik Negeri UjungPandang, Makassar  \n3 Jurusan TeknikElektro Politeknik Negeri UjungPandang, Makassar  \nABSTRACT  \nThis research was conducted to design and develop a system capable of automatically monitoring and determining roof damage on containers before they enter the container yard. The monitoring is carried out at the gate area by applying a Machine Learning method, namely You Only Look Once (YOLO). Three types of damage are being monitored: rust, holes, and dents. Human error, extreme weather conditions, or collisions with other objects usually cause this damage. The results of the study show that YOLO in monitoring and identifying container damage achieved an 88.8% detection accuracy in the morning with a detection process duration of 31.5 seconds, a 90.9% detection accuracy during the day with a detection process duration of 31.1 seconds, an 87.7% detection accuracy in the afternoon with a detection process duration of 32.6 seconds, and an 83.6% detection accuracy at night with a detection process duration of 33.2 seconds. The low detection accuracy at night, which is only 83.6% is caused by less than optimal lighting, in contrast to daytime lighting. The realtime monitoring system functions quite well, as it can provide documentation evidence and continuously notify the gate inspector regarding the physical condition of the container roof.  \nKeywords: Container, Gate, Machine Learning, Real-Time Monitoring System, You Only Look Once  \nABSTRAK  \nPenelitian ini dilakukan untuk merancang dan membuat sebuah sistem yang dapat secara otomatis memantau dan menentukan kerusakan pada atap kontainer sebelum masuk ke lapangan penumpukan (container yard) . Pemantauan ini dilakukan pada area gate dengan menerapkan metode Machine Learning, yaitu You Only Look Once (YOLO) . Terdapattiga jenis kerusakan yang dipantau, yaitu karat, lubang dan penyok. Kerusakan ini biasanya disebabkan oleh kesalahan manusia, kondisi cuaca ekstrem, atau benturan dengan objek lain. Hasil penelitian menunjukkan bahwa YOLO dalam memantau dan menentukan kerusakan pada kontainer mencapai tingkat akurasi deteksi 88.8% pada pagi hari dengan durasiproses deteksi 31.5 detik, akurasi deteksi 90.9% pada siang hari dengan durasi proses deteksi 31.1 detik, akurasi deteksi 87.7% pada sore hari dengan durasi proses deteksi 32.6 detik, dan akurasi deteksi 83.6% pada malam hari dengan durasiproses deteksi 33.2 detik. Akurasi deteksi yang rendah pada malam hari, yaitu hanya 83.6% disebabkan oleh pencahayaanyang kurang maksimal, berbeda dengan pencahayaan pada siang hari. Sistem monitoring real-time berjalan dengan cukupbaik, dengan sistem yang mampu menampilkan bukti dokumentasi dan memberikan pemberitahuan secara terus-meneruspada gate inspector terkait dengan kondisi fisik atap kontainer.  \nKata Kunci: Gate, Kontainer, Machine Learning, Sistem Monitoring Real-Time, You Only Look Once  \n1. PENDAHULUAN  \nPelabuhan adalah tempat yang terdiri dari daratan dan perairan di sekitarnya dengan batas-batas tertentusebagai tempat kegiatan pemerintahan dan kegiatan layanan jasa [1] . Pelabuhan memiliki peranan yang sangat penting dan sangat strategis dalam menunjang pertumbuhan perekonomian dan perdagangan antar Kota dan Provinsi secara khusus, serta antar Negara secara umum. Pelabuhan sebagai salah satu sistem transportasi laut internasional yang pantas dan layak dijadikan hubport dari Indonesia [2] . Negara Indonesia sebagai negara maritim, peranan angkutan laut sangat penting bagi kehidupan sosial ekonomi penduduknya [3] . Pelabuhan menjadi salah satu unsur penentu terhadap aktivitas perdagangan. Pelabuhan yang dikelola secara baik danefisien akan mendorong kemajuan perdagangan, bahkan di daerah industri akan maju dengan sendirinya[4] .  \nSalah satu","cbCaivbNN4Eeo6uB","https://ap.wps.com/l/cbCaivbNN4Eeo6uB","pdf",1502202,4,1,7,"Indonesian","id",113,"# Pendahuluan\n## Latar belakang peran pelabuhan\n## Terminal Petikemas Makassar New Port\n## Permasalahan pemeriksaan atap kontainer\n# Metode penelitian\n## Penerapan YOLO untuk deteksi kerusakan\n## Jenis kerusakan yang dipantau\n# Hasil dan pembahasan\n## Akurasi deteksi berdasarkan waktu\n## Penyebab penurunan akurasi pada malam\n# Kesimpulan","[{\"question\":\"Sistem apa yang dibangun dalam penelitian ini?\",\"answer\":\"Penelitian ini membangun sistem monitoring real-time yang otomatis memantau dan menentukan kerusakan atap kontainer sebelum kontainer masuk ke container yard di area gate.\"},{\"question\":\"Metode machine learning apa yang digunakan untuk mendeteksi kerusakan?\",\"answer\":\"Metode yang digunakan adalah You Only Look Once (YOLO) untuk mendeteksi kerusakan pada atap kontainer.\"},{\"question\":\"Jenis kerusakan apa saja yang dipantau pada kontainer?\",\"answer\":\"Terdapat tiga jenis kerusakan yang dipantau, yaitu karat, lubang, dan penyok.\"},{\"question\":\"Mengapa akurasi deteksi lebih rendah pada malam hari?\",\"answer\":\"Akurasi deteksi malam hari lebih rendah karena pencahayaan kurang maksimal dibandingkan pencahayaan pada siang hari.\"}]","PENERAPAN MACHINE LEARNING UNTUK MEMANTAU KERUSAKAN KONTAINER PADA GATE TERMINAL PETIKEMAS MAKASSAR NEW PORT - Sistem deteksi kerusakan atap kontainer dengan YOLO | PDF",1785820554,11,{"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":91,"head_meta":93,"extra_data":95,"updated_unix":29},"application-of-machine-learning-to-monitor-container-damage-at-the-gate-of-makassar-new-port-container-roof-damage-detection-system-with-yolo","",{"@graph":37,"@context":90},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"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":51},"https://docshare.wps.com/id/document/teknologi/",3,{"item":53,"name":13,"@type":44,"position":20},"https://docshare.wps.com/id/document/application-of-machine-learning-to-monitor-container-damage-at-the-gate-of-makassar-new-port-container-roof-damage-detection-system-with-yolo/124120/",{"url":53,"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",[72,78,82,86],{"name":73,"@type":74,"acceptedAnswer":75},"Sistem apa yang dibangun dalam penelitian ini?","Question",{"text":76,"@type":77},"Penelitian ini membangun sistem monitoring real-time yang otomatis memantau dan menentukan kerusakan atap kontainer sebelum kontainer masuk ke container yard di area gate.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Metode machine learning apa yang digunakan untuk mendeteksi kerusakan?",{"text":81,"@type":77},"Metode yang digunakan adalah You Only Look Once (YOLO) untuk mendeteksi kerusakan pada atap kontainer.",{"name":83,"@type":74,"acceptedAnswer":84},"Jenis kerusakan apa saja yang dipantau pada kontainer?",{"text":85,"@type":77},"Terdapat tiga jenis kerusakan yang dipantau, yaitu karat, lubang, dan penyok.",{"name":87,"@type":74,"acceptedAnswer":88},"Mengapa akurasi deteksi lebih rendah pada malam hari?",{"text":89,"@type":77},"Akurasi deteksi malam hari lebih rendah karena pencahayaan kurang maksimal dibandingkan pencahayaan pada siang hari.","https://schema.org",{"og:url":53,"og:type":92,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":94,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":97},[98,103,107,111,115,119,123,127,129,133,137],{"id":99,"doc_module":4,"doc_module_name":47,"category_name":100,"show_sort_weight":101,"slug":102},55,"Agama & Spiritualitas",60,"religion-spirituality",{"id":104,"doc_module":4,"doc_module_name":47,"category_name":105,"show_sort_weight":101,"slug":106},48,"Cerita & Novel","story-novel",{"id":108,"doc_module":4,"doc_module_name":47,"category_name":109,"show_sort_weight":101,"slug":110},56,"Gaya Hidup","lifestyle",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":101,"slug":114},51,"Komik","comic",{"id":116,"doc_module":4,"doc_module_name":47,"category_name":117,"show_sort_weight":101,"slug":118},53,"Layanan Kesehatan","healthcare",{"id":120,"doc_module":4,"doc_module_name":47,"category_name":121,"show_sort_weight":101,"slug":122},54,"Penelitian & Laporan","research-report",{"id":124,"doc_module":4,"doc_module_name":47,"category_name":125,"show_sort_weight":101,"slug":126},49,"Sastra","literature",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":101,"slug":128},"technology",{"id":130,"doc_module":4,"doc_module_name":47,"category_name":131,"show_sort_weight":101,"slug":132},50,"Ujian","exam",{"id":134,"doc_module":4,"doc_module_name":47,"category_name":135,"show_sort_weight":101,"slug":136},57,"Umum","general",{"id":138,"doc_module":4,"doc_module_name":47,"category_name":139,"show_sort_weight":4,"slug":140},181,"Formulir","formulir"]