[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124701-id":3,"doc-seo-124701-113":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},124701,549768064778,"Finn","https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8",54,"Penelitian & Laporan","Peningkatan Akurasi Identifikasi Penyakit Busuk Pangkal Batang di Perkebunan Kelapa Sawit Menggunakan Unmanned Aerial Vehicle (UAV) dan Machine Learning","Penyakit busuk pangkal batang (BSR) akibat Ganoderma sp tetap menjadi penyakit utama pada perkebunan kelapa sawit dan belum memiliki tindakan pengendalian yang efektif, sehingga kultur teknis menjadi pilihan utama untuk memperpanjang umur tanaman. Ketepatan identifikasi serta klasifikasi tanaman sehat dan terinfeksi BSR diperlukan untuk mendukung perlakuan kultur teknis. Penelitian ini memperluas studi Santoso (2020) dengan remote sensing citra kamera multispektral tiga band dan machine learning, menambahkan sepuluh indeks vegetasi serta mengevaluasi enam belas model klasifikasi. Hasilnya meningkatkan akurasi interpretasi hingga 87,18% dan nilai kappa menjadi 0,69 dari 0,48, terutama dipengaruhi variabel penting dari indeks vegetasi dan band merah.","J. Pen. Kelapa Sawit, 2023, 31(2): 82-95  \nPeningkatan Akurasi Identifikasi Penyakit Busuk Pangkal Batang di Perkebunan Kelapa Sawit Menggunakan Unmanned Aerial Vehicle (UAV) dan Machine Learning  \nAccuracy Improvement of Basal Stem Rot Disease Identification in Oil Palm Plantation Using Unmanned Aerial Vehicle and Machine Learning  \nHeri Santoso  \nAbstrak Penyakit busuk pangkal batang (BSR) yang disebabkan oleh jamur Ganoderma sp pada tanaman kelapa sawit masih menjadi penyakit utama dan belum ada tindakan pengendaliannya yang efektif. Perlakuan kultur teknis untuk memperpanjang umur tanaman masih menjadi tindakan utama dalam pengendalian penyakit BSR ini. Ketepatan identifikasi dan klasifikasitanaman sehat dan terinfeksi penyakit BSR secaracepat dan tepat sangat diperlukan untuk mendukung perlakuan kultur teknis. Penelitian ini melanjutkan penelitian Santoso (2020) untuk identifikasi danklasifikasi tanaman kelapa sawit sehat dan terinfeksipenyakit BSR dengan menggunakan pendekatan remote sensing dari image yang direkam oleh kamera multispektral tiga band dan machine learning. Tujuan utama dari penelitian ini adalah meningkatkan akurasi interpretasi tanaman sehat dan terinfeksi penyakit BSR dengan penambahan variabel berupa sepuluh indeks vegetasi yang memanfaatkan ketiga band dari kamera multispektral ( merah , hijau , dan near infrared/NIR) dan penerapan enam belas machine learning classification model. Hasil penelitian menunjukkan model random forest dan stochastic gradient boosting mampu meningkatkan akurasi interpretasi menjadi 87.18 % dari 79.49 % dan kappa value menjadi 0.69 dari 0.48. Peningkatan akurasi initidak lepas dari variabel penting dalam fiting model yang digunakan dalam penelitian ini yang didominasioleh variabel dari indeks vegetasi dan band merah. Model ini perlu diuji untuk mengidentifikasi tanamansehat dan terinfeksi penyakit BSR dengan taraf  \nPenulis yang tidak disertaidengan catatan kaki instansi adalah penelitipadaPusat Penelitian Kelapa Sawit  \nHeri Santoso (*)  \nPusat Penelitian Kelapa Sawit  \nJl. Brigjen Katamso No. 51 Medan 20158 Indonesia  \nEmail: [hs_jmp@yahoo.com](hs_jmp@yahoo.com)  \ninsidensi rendah dan sedang.  \nKata kunci: penyakit busuk pangkal batang, kelapasawit, UAV, multispectral, indeks vegetasi, machine learning  \nAbstract The basal stem rot disease caused by Ganoderma sp remains a majority disease in oil palm plantations, and there is no effective treatment. The technical culture becomes a majority treatment to prolong the oil palm life. The identification and classification accuracy of healthy and infected by BSR (unhealthy) oil palm is needed to support the technical culture of treatment. This study is based on Santoso's previous study (2020), which identifies and classifies healthy and unhealthy oil palms using remote sensing from an image of a multispectral camera with three bands and machine learning. This study aims to improve the interpretation accuracy of healthy and unhealthy oil palms by adding ten vegetation indexes from three bands (red, green, and near-infrared/NIR) of a multispectral camera and applying sixteen models of machine learning. The results showed that the random forest and stochastic gradient boosting had improved 87. 18% of the interpretation accuracy by 79.49% in the previous research and 0.69 kappa value from 0.48 in the previous research. This study's accuracy and kappa value improvement maybe caused by adding variables from the vegetation indexes that become variable importance besides the red band in the fitting model. The model in this study needs to validate for identifying and classifying healthy and unhealthy oil palm caused by BSRin the area with low and moderate incidence.  \nKeywords: basal stem rot disease, oil palm, UAV, multispectral, vegetation indexes, machine learning  \nNaskah masuk: 14/02/2023; Naskah diterima: 13/06/2023 82  \nHeri Santoso  \nPENDAHULUAN  \nPenyakit busuk pangkal batang (BSR) padatanaman kelapa sawit yang disebabkan oleh jam","cbCaif3zySFCw4D7","https://ap.wps.com/l/cbCaif3zySFCw4D7","pdf",18300568,3,1,14,"Indonesian","id",113,"# PENDAHULUAN\n## Latar belakang dan urgensi identifikasi BSR\n## Pendekatan remote sensing dan machine learning untuk klasifikasi","[{\"question\":\"Mengapa identifikasi dini penyakit BSR pada kelapa sawit penting?\",\"answer\":\"Karena gejala visual umumnya muncul saat tanaman sudah terinfeksi berat, sedangkan tindakan kultur teknis dan isolasi menuntut pemilahan cepat tanaman sehat dan terinfeksi untuk mencegah penularan.\"},{\"question\":\"Bagaimana penelitian ini meningkatkan akurasi identifikasi BSR?\",\"answer\":\"Dengan menambahkan sepuluh indeks vegetasi berbasis tiga band kamera multispektral (merah, hijau, NIR) dan menerapkan enam belas model machine learning untuk klasifikasi.\"},{\"question\":\"Model machine learning apa yang menunjukkan peningkatan terbaik?\",\"answer\":\"Random forest dan stochastic gradient boosting, yang meningkatkan akurasi interpretasi menjadi 87,18% dari 79,49% serta meningkatkan nilai kappa menjadi 0,69 dari 0,48.\"}]","Peningkatan Akurasi Identifikasi Penyakit Busuk Pangkal Batang di Perkebunan Kelapa Sawit Menggunakan Unmanned Aerial Vehicle (UAV) dan Machine Learning | PDF",1785893997,22,{"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},"accuracy-improvement-of-basal-stem-rot-disease-identification-in-oil-palm-plantation-using-unmanned-aerial-vehicle-uav-and-machine-learning","",{"@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/penelitian-laporan/",{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/id/document/accuracy-improvement-of-basal-stem-rot-disease-identification-in-oil-palm-plantation-using-unmanned-aerial-vehicle-uav-and-machine-learning/124701/",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","2026-08-05",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},"Mengapa identifikasi dini penyakit BSR pada kelapa sawit penting?","Question",{"text":76,"@type":77},"Karena gejala visual umumnya muncul saat tanaman sudah terinfeksi berat, sedangkan tindakan kultur teknis dan isolasi menuntut pemilahan cepat tanaman sehat dan terinfeksi untuk mencegah penularan.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Bagaimana penelitian ini meningkatkan akurasi identifikasi BSR?",{"text":81,"@type":77},"Dengan menambahkan sepuluh indeks vegetasi berbasis tiga band kamera multispektral (merah, hijau, NIR) dan menerapkan enam belas model machine learning untuk klasifikasi.",{"name":83,"@type":74,"acceptedAnswer":84},"Model machine learning apa yang menunjukkan peningkatan terbaik?",{"text":85,"@type":77},"Random forest dan stochastic gradient boosting, yang meningkatkan akurasi interpretasi menjadi 87,18% dari 79,49% serta meningkatkan nilai kappa menjadi 0,69 dari 0,48.","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},[94,99,103,107,111,115,117,121,125,129,133],{"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":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":97,"slug":116},"research-report",{"id":118,"doc_module":4,"doc_module_name":47,"category_name":119,"show_sort_weight":97,"slug":120},49,"Sastra","literature",{"id":122,"doc_module":4,"doc_module_name":47,"category_name":123,"show_sort_weight":97,"slug":124},52,"Teknologi","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"]