[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120586-id":3,"doc-seo-120586-113":31,"detail-sidebar-cat-0-id-113":84},{"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},120586,962085564807,"Aurelia","https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8",53,"Layanan Kesehatan","PREDIKSI IMPLAN GIGI MENGGUNAKAN ALGORITMA MACHINE LEARNING - Sistem Pendukung Keputusan Klinis","Kemajuan teknologi digital, terutama kecerdasan buatan (AI), mendorong transformasi layanan kesehatan termasuk pengambilan keputusan untuk kelayakan implan gigi. Penelitian ini membangun model machine learning berbasis algoritma Classification and Regression Tree (CART) untuk memprediksi kandidat implan menggunakan data pasien yang dianonimkan dari Klinik Ellisa Dental, Batam. Data memuat atribut demografis dan klinis seperti usia, jenis kelamin, kebiasaan merokok, kondisi tulang rahang, serta riwayat penyakit kronis. Hasil analisis menunjukkan faktor berat merokok, penyakit sistemik, dan integritas tulang rahang berpengaruh besar pada kesesuaian implan. Kualitas dataset mendukung pemodelan yang kuat dan sistem dirancang sebagai alat bantu keputusan berbasis bukti bagi dokter dalam menilai kelayakan pasien.","PREDIKSI IMPLAN GIGI MENGGUNAKAN ALGORITMA MACHINE LEARNING  \nAlisa Zebua1 ,  \nKoko handoko2  \n1Program Studi Teknik Informatika , Universitas Putera Batam  \n2Program Studi Teknik Informatika , Universitas Putera Batam  \nemail: [pb210210066@upbatam.ac.id](pb210210066@upbatam.ac.id)  \nABSTRACT  \nAdvances in digital technologies, particularly artificial intelligence (AI), are transforming healthcare practices, including dental implant decision-making. This study introduces a machine learning model utilizing the Classification and Regression Tree (CART) algorithm to estimate dental implant candidacy, drawing on anonymized patient records from Ellisa Dental Clinic, Batam. The dataset comprises various demographic and clinical attributes such as age, sex, smoking patterns, bone condition, and the presence of chronic illnesses including diabetes, hypertension, and autoimmune disorders. The exploratory analysis reveals that factors like heavy smoking, systemic diseases, and jawbone integrity substantially affect implant suitability. The quality and consistency of the dataset support robust modeling. The proposed system is intended to function as a clinical decision aid, offering dentists evidence-based recommendations regarding patient eligibility. This work demonstrates the potential of predictive analytics to enhance decision accuracy and streamline dental care, contributing to the integration of AI into routine clinical workflows.  \nKeywords: Artificial intelligence; Dental implant; Decision tree; Eligibility prediction; Medical records.  \nPENDAHULUAN  \nPerkembangan teknologi digital, khususnya AI, telah mengubah layanankesehatan, termasuk kedokteran gigi. Pemasangan implan gigi memerlukanevaluasi cermat, namun sering kali masih bergantung pada penilaian subjektif dokter. Penelitian sebelumnya  \nmenunjukkan bahwa algoritma Decision Tree (CART) efektif dalam menganalisis data medis dan menghasilkan prediksi yang akurat.  \nPenelitian ini penting untuk menghadirkan sistem pendukung keputusan klinis yang  \nandal, terutama di klinik dengan pasien beragam. Dengan memanfaatkan data rekam medis seperti usia, jenis kelamin, kebiasaan merokok, kondisi tulangrahang, dan riwayat penyakit kronis, model prediktif diharapkan dapatmenyaring pasien layak implan secara lebih tepat.  \nMachine Learning atau pembelajaranmesin merupakan cabang darikecerdasan buatan yang terus berkembang, berfokus pada kemampuan sistem komputer untuk mengenali pola dan belajar dari data (Wardhana et al. , 2023) . Beberapa penelitian sebelumnya  \ntelah menunjukkan potensi algoritma CART dalam klasifikasi medis, namun belum banyak diterapkan secara spesifik pada kasus implan gigi di Indonesia. Penelitian ini bertujuan untuk membangun model prediksi kelayakanimplan menggunakan data dari Klinik Ellisa Dental di Batam, sebagai bentukkontribusi terhadap digitalisasi layanankesehatan gigi lokal. Rencanapemecahan masalah dilakukan melaluipendekatan machine learning, dimulaidari proses prapemrosesan data, pelatihan model, hingga evaluasi performa prediksi, guna memastikan validitas dan aplikabilitas model di lingkungan klinis.  \nKAJIAN TEORI  \n2.1 Artificial intelligence (AI)  \nDengan pesatnya kemajuan teknologi, kecerdasan buatan (AI) kini berperan penting dalam berbagai aspek kehidupan. AI dirancang untuk meniru cara berpikir manusia dalam menyelesaikan tugas kompleks secara otomatis. Melalui algoritma pembelajaran mesin, AI mampu menganalisis data besar, mengenali pola, dan menghasilkan prediksi denganakurasi tinggi. Teknologi ini banyak dimanfaatkan di sektor kesehatan, bisnis, pendidikan, dan manufaktur untuk meningkatkan efisiensi dan mempercepat proses kerja (Situmorang & Handoko, 2024) .  \nPerkembangan AI dalam bidang kesehatan memberikan dampak besar, terutama dalam mendukung analisis medis secara akurat (Murdoch, 2021) . Banyak institusi kesehatan mulai mengadopsinya karena AI dapat meringankan tugas tenaga medis, bahkan berpotensi menggantikansebagian peran dokter (Tr","cbCaiaqf8sz4gE5L","https://ap.wps.com/l/cbCaiaqf8sz4gE5L","pdf",566741,4,1,10,"Indonesian","id",113,"# Pendahuluan\n## Latar belakang kebutuhan sistem pendukung keputusan\n## Machine learning untuk prediksi kelayakan implan\n# Kajian Teori\n## Artificial intelligence (AI)\n## Machine learning\n## Decision tree\n## Objek penelitian","[{\"question\":\"Bagaimana tujuan sistem yang dibangun dalam penelitian ini?\",\"answer\":\"Sistem dirancang sebagai clinical decision aid untuk memberikan rekomendasi berbasis bukti mengenai kelayakan pasien, membantu dokter menilai eligibility lebih akurat dan mempercepat alur perawatan.\"}]","PREDIKSI IMPLAN GIGI MENGGUNAKAN ALGORITMA MACHINE LEARNING - Sistem Pendukung Keputusan Klinis | PDF",1785730776,15,{"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":79,"head_meta":81,"extra_data":83,"updated_unix":29},"dental-implant-prediction-using-machine-learning-algorithms-clinical-decision-support-system","",{"@graph":37,"@context":78},[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/layanan-kesehatan/",3,{"item":53,"name":13,"@type":44,"position":20},"https://docshare.wps.com/id/document/dental-implant-prediction-using-machine-learning-algorithms-clinical-decision-support-system/120586/",{"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","2026-08-18","2026-08-03",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72],{"name":73,"@type":74,"acceptedAnswer":75},"Bagaimana tujuan sistem yang dibangun dalam penelitian ini?","Question",{"text":76,"@type":77},"Sistem dirancang sebagai clinical decision aid untuk memberikan rekomendasi berbasis bukti mengenai kelayakan pasien, membantu dokter menilai eligibility lebih akurat dan mempercepat alur perawatan.","Answer","https://schema.org",{"og:url":53,"og:type":80,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":82,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":85},[86,91,95,99,103,105,109,113,117,121,125],{"id":87,"doc_module":4,"doc_module_name":47,"category_name":88,"show_sort_weight":89,"slug":90},55,"Agama & Spiritualitas",60,"religion-spirituality",{"id":92,"doc_module":4,"doc_module_name":47,"category_name":93,"show_sort_weight":89,"slug":94},48,"Cerita & Novel","story-novel",{"id":96,"doc_module":4,"doc_module_name":47,"category_name":97,"show_sort_weight":89,"slug":98},56,"Gaya Hidup","lifestyle",{"id":100,"doc_module":4,"doc_module_name":47,"category_name":101,"show_sort_weight":89,"slug":102},51,"Komik","comic",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":89,"slug":104},"healthcare",{"id":106,"doc_module":4,"doc_module_name":47,"category_name":107,"show_sort_weight":89,"slug":108},54,"Penelitian & Laporan","research-report",{"id":110,"doc_module":4,"doc_module_name":47,"category_name":111,"show_sort_weight":89,"slug":112},49,"Sastra","literature",{"id":114,"doc_module":4,"doc_module_name":47,"category_name":115,"show_sort_weight":89,"slug":116},52,"Teknologi","technology",{"id":118,"doc_module":4,"doc_module_name":47,"category_name":119,"show_sort_weight":89,"slug":120},50,"Ujian","exam",{"id":122,"doc_module":4,"doc_module_name":47,"category_name":123,"show_sort_weight":89,"slug":124},57,"Umum","general",{"id":126,"doc_module":4,"doc_module_name":47,"category_name":127,"show_sort_weight":4,"slug":128},181,"Formulir","formulir"]