[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-232051-113":3,"detail-sidebar-cat-0-id-113":80,"doc-detail-232051-id":127},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":73,"head_meta":75,"extra_data":77,"updated_unix":79},113,"id","comparison-of-cart-and-svm-algorithms-for-determining-student-acceptance-in-state-universities","Perbandingan Algoritma CART dan SVM untuk Penentuan Penerimaan Siswa di Perguruan Tinggi Negeri","","Kegiatan seleksi masuk perguruan tinggi negeri bertujuan memperoleh calon mahasiswa yang unggul melalui beberapa jalur, yaitu SNMPTN (jalur undangan), SBMPTN, dan ujian mandiri. Penelitian menggunakan data 143 siswa dengan 7/8 atribut serta preprocessing melalui data transformation. Data dipisahkan menjadi training dan testing menggunakan 10-fold cross validation, lalu dilakukan klasifikasi dengan perbandingan dua metode: CART dan SVM dengan pembobotan gain ratio. Hasil menunjukkan akurasi CART sebesar 86,10% dan SVM sebesar 86,71% untuk memprediksi penerimaan siswa.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/id/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/id/document/penelitian-laporan/","Penelitian & Laporan",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/id/document/comparison-of-cart-and-svm-algorithms-for-determining-student-acceptance-in-state-universities/232051/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/comparison-of-cart-and-svm-algorithms-for-determining-student-acceptance-in-state-universities/232051.png","ImageObject",300,407,{"name":42,"@type":43},"Jordan Avery","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-09-20","2026-09-10",true,{"@type":52,"interactionType":53,"userInteractionCount":33},"InteractionCounter",{"@type":54},"ViewAction",{"@type":56,"mainEntity":57},"FAQPage",[58,64,68],{"name":59,"@type":60,"acceptedAnswer":61},"Apa tujuan penelitian ini dalam seleksi masuk PTN?","Question",{"text":62,"@type":63},"Untuk memprediksi dan menentukan penerimaan siswa di perguruan tinggi negeri melalui perbandingan metode klasifikasi berdasarkan data siswa.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"Bagaimana preprocessing dilakukan sebelum proses klasifikasi?",{"text":67,"@type":63},"Penelitian melakukan preprocessing menggunakan data transformation agar menyederhanakan proses training pada data siswa.",{"name":69,"@type":60,"acceptedAnswer":70},"Algoritma apa saja yang dibandingkan dan bagaimana cara evaluasinya?",{"text":71,"@type":63},"Metode yang dibandingkan adalah CART dan SVM dengan pembobotan gain ratio, dievaluasi menggunakan 10-fold cross validation untuk membagi training dan testing.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},232051,1789068523,{"code":4,"msg":81,"data":82},"success",[83,88,92,96,100,104,107,111,115,119,123],{"id":84,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},55,"Agama & Spiritualitas",60,"religion-spirituality",{"id":89,"doc_module":4,"doc_module_name":25,"category_name":90,"show_sort_weight":86,"slug":91},48,"Cerita & Novel","story-novel",{"id":93,"doc_module":4,"doc_module_name":25,"category_name":94,"show_sort_weight":86,"slug":95},56,"Gaya Hidup","lifestyle",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":86,"slug":99},51,"Komik","comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":86,"slug":103},53,"Layanan Kesehatan","healthcare",{"id":105,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":86,"slug":106},54,"research-report",{"id":108,"doc_module":4,"doc_module_name":25,"category_name":109,"show_sort_weight":86,"slug":110},49,"Sastra","literature",{"id":112,"doc_module":4,"doc_module_name":25,"category_name":113,"show_sort_weight":86,"slug":114},52,"Teknologi","technology",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":86,"slug":118},50,"Ujian","exam",{"id":120,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":86,"slug":122},57,"Umum","general",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":4,"slug":126},181,"Formulir","formulir",{"code":4,"msg":81,"data":128},{"doc_id":78,"user_id":129,"nickname":42,"user_avatar":130,"doc_module":4,"category_id":105,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":131,"file_id":132,"file_url":133,"file_type":134,"file_size":135,"view_count":33,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":136,"language":137,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":138,"faqs":139,"seo_title":140,"seo_description":12,"update_tm":79,"read_time":141},1099523882367,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","COMPARISON OF ALGORITHM BETWEEN CLASSIFICATION & REGRESSION TREES AND SUPPORT VECTOR MACHINE IN DETERMINING STUDENT ACCEPTANCE IN STATE UNIVERSITIES  \nM. Anwar Sadat*1, Pujiono2, Anggun Pambudi3, Sholihul Ibad4  \n1,2,3Master's Program in Informatics Engineering, Faculty of Computer Science , Universitas Dian Nuswantoro Semarang, Indonesia  \n4Information Systems Study Program, Institut Teknologi dan Bisnis Tuban, Indonesia [Email:](Email:1m.anwarsadat@gmail.com)[1](Email:1m.anwarsadat@gmail.com)[m.anwarsadat@gmail.com](Email:1m.anwarsadat@gmail.com)  \n(Article received: December 04, 2023; Revision: December 28, 2023; published: January 08, 2024)  \nAbstract  \nHigher education entrance selection activities are intended to obtain superior student candidates. The opportunity to take part in the selection is given to all high school graduate students and equivalent. The student entrance test at PTN consists of three types of selection routes, namely the SNMPTNor invitation route, the SBMPTN, and the independent examination held by state universities. Starting from the dataset, data selection was carried out from 143 students' data and 7 attribute selections were carried out using preprocessing using data transformation first. The aim of using data transformation is to simplify the data training process for MAN 1 students in Cirebon. Preprocessing for prediction of classification results, accuracy of testing data for 143 students is implemented in the program and the resulting calculation process will be more efficient. After going through the preprocessing stage, the data is divided into training data and testing data using 10-fold cross validation. Next, for the classification process, a comparison of two methods will be used, namely for the first method using CART, the second method using SVM by adding Gain ratio weighting. The results of the research show that in the first experiment the researcher carried out a comparative trial of cross validation and classification performance and used the CART and SVM algorithms. The results comparison using the CART algorithm gets an accuracy of 86.10% and the SVM algorithm method for classifying students entering PTN was 86. 71%.  \nKeywords: Cart Algorithm, PTN participants, SVM algorithm.  \nKOMPARASI ALGORITMA ANTARA CLASSIFICATION & REGRESSION TREES DAN SUPPORT VECTOR MACHINE DALAM PENENTUAN PENERIMAAN SISWA  \nDIDIK DI PERGURUAN TINGGI NEGERI  \nAbstrak  \nKegiatan seleksi masuk perguruan tinggi (PT) dimaksudkan untuk memperoleh calon mahasiswa yang unggul. Kesempatan untuk mengikuti seleksi diberikan kepada seluruh siswa tamatan SMU dan setara. Tes masuk mahasiswa di PTN terdiri atas tiga macam jalur seleksi, yaitu SNMPTN atau jalur undangan, jalur SBMPTN, dan jalur ujian mandiri yang diadakan oleh universitas negeri. Dimulai dari dataset dilakukan seleksi data dari data 143 siswa dan 7 atribut seleksi sejumlah preprocessing menggunakan data transformation terlebih dahulu. Adapun tujuan menggunakan data transformation agar mempermudah proses data training nilai siswa MAN 1 kota Cirebon. Preprocessing prediksi hasil klasifikasi akurasi data testing 143 siswa diimplementasi pada program sertaproses perhitungan yang dihasilkan akan lebih efisien. Setelah melalui tahap preprocessing, data tersebut dibagimenjadi data training dan data testing menggunakan cross validation sebanyak 10-fold cross validation. Selanjutnya untuk proses klasifikasi akan digunakan perbandingan dua metode, yaitu untuk metode pertama menggunakan CART, metode kedua menggunakan SVM dengan menambahkan pemobobotan Gain ratio. Hasil penelitian menunjukkan bahwa pada eksperimen yang pertama peneliti melakukan uji coba perbandingan cross validation dan performance klasifikasi dan menngunakan algoritma CART dan SVM dengan jumlah data 143 siswa dengan atribut 8 dan perbandingan antara data training testing Masuk pengisian data peseta PTN masuk atautidak masuk, Hasil eksperimen perbandingan menggunakan algoritma CART mendapatkan a","cbCaimJ19AadAssX","https://ap.wps.com/l/cbCaimJ19AadAssX","pdf",1469747,16,"Indonesian","# Pendahuluan\n## Tujuan dan konteks seleksi masuk PTN\n## Jalur seleksi PTN (SNMPTN, SBMPTN, ujian mandiri)\n# Metode Penelitian\n## Data dan atribut\n## Preprocessing dan data transformation\n## Pembagian data serta 10-fold cross validation\n## Perbandingan algoritma: CART dan SVM (gain ratio)\n# Hasil dan Pembahasan\n## Akurasi CART\n## Akurasi SVM\n## Analisis perbandingan performa\n# Kesimpulan","[{\"question\":\"Apa tujuan penelitian ini dalam seleksi masuk PTN?\",\"answer\":\"Untuk memprediksi dan menentukan penerimaan siswa di perguruan tinggi negeri melalui perbandingan metode klasifikasi berdasarkan data siswa.\"},{\"question\":\"Bagaimana preprocessing dilakukan sebelum proses klasifikasi?\",\"answer\":\"Penelitian melakukan preprocessing menggunakan data transformation agar menyederhanakan proses training pada data siswa.\"},{\"question\":\"Algoritma apa saja yang dibandingkan dan bagaimana cara evaluasinya?\",\"answer\":\"Metode yang dibandingkan adalah CART dan SVM dengan pembobotan gain ratio, dievaluasi menggunakan 10-fold cross validation untuk membagi training dan testing.\"}]","Perbandingan Algoritma CART dan SVM untuk Penentuan Penerimaan Siswa di Perguruan Tinggi Negeri | PDF",25]