?url_ver=Z39.88-2004&rft_id=1917031032&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=PENANGANAN+IMBALANCE+DATA+DENGAN+RANDOM+OVERSAMPLING%0D%0A(ROS)+PADA+KLASIFIKASI+PENDERITA+DIABETES+MENGGUNAKAN%0D%0ASUPPORT+VECTOR+MACHINE+(SVM)&rft.creator=DHIFA+ZHAFIRAH%2C+1917031032&rft.subject=000+Ilmu+komputer%2C+informasi+dan+pekerjaan+umum&rft.subject=001+Ilmu+pengetahuan&rft.description=ABSTRACT%0D%0AHANDLING+OF+IMBALANCE+DATA+WITH+RANDOM%0D%0AOVERSAMPLING+(ROS)+IN+CLASSIFICATION+OF+DIABETIC%0D%0APATIENTS+USING+SUPPORT+VECTOR+MACHINE+(SVM)%0D%0ABy%0D%0ADhifa+Zhafirah%0D%0ADiabetes+mellitus+is+a+health+problem+that+often+occurs+in+Indonesia%2C+especially+in%0D%0ALampung+Province.+This+disease+is+a+condition+in+which+the+body+does+not+produce%0D%0Aenough+or+use+the+insulin+hormone+that+carries+glucose+into+the+body's+cells.+The%0D%0Apurpose+of+this+research+is+to+create+a+machine-learning+model+that+can+detect%0D%0Adiabetes+early+using+a+Support+Vector+Machine+(SVM).+However%2C+the+dataset+used%0D%0Ain+the+research+has+data+imbalance+problems.+Therefore%2C+Random+Oversampling%0D%0A(ROS)+is+used+to+overcome+this+problem.+The+results+obtained+from+this+study%2C+ROS%0D%0Ais+able+to+handle+imbalance+data+so+that+the+accuracy+value+obtained+reaches+96.43%25%0D%0A(excellent+classification)+with+the+C-Classification+model+and+Radial+Basis+Function%0D%0A(RBF)+kernel%2C+as+well+as+sigma+one+and+cost+one+parameter+for+the+training+data%0D%0Ascheme+90%25+and+10%25+testing+data.+This+accuracy+value+increases+sharply+compared%0D%0Ato+without+ROS%2C+which+is+only+around+76%25.%0D%0AKeywords+%3A+Diabetes+Melitus%2C+Imbalance+Data%2C+Random+Oversampling%2C+Support%0D%0AVector+Machine%0D%0A%0D%0A%0D%0ADiabetes+melitus+adalah+salah+satu+masalah+kesehatan+yang+sering+terjadi+di%0D%0AIndonesia+khususnya+Provinsi+Lampung.+Penyakit+ini+merupakan+suatu+kondisi%0D%0Adimana+tubuh+tidak+cukup+untuk+menghasilkan+atau+menggunakan+hormon+insulin%0D%0Ayang+membawa+glukosa+ke+dalam+sel-sel+tubuh.+Tujuan+penelitian+ini+adalah%0D%0Amembuat+model+machine+learning+yang+dapat+mendeteksi+dini+penyakit+diabetes%0D%0Amenggunakan+Support+Vector+Machine+(SVM).+Namun%2C+pada+dataset+yang%0D%0Adigunakan+dalam+penelitian+memiliki+masalah+ketidakseimbangan+data+(imbalance%0D%0Adata).+Oleh+karena+itu%2C+digunakan+Random+Oversampling+(ROS)+untuk+mengatasi%0D%0Amasalah+tersebut.+Hasil+yang+diperoleh+dari+penelitian+ini%2C+ROS+mampu+menangani%0D%0Aimbalance+data+sehingga+nilai+akurasi+yang+didapatkan+mencapai+96.43%25+(excellent%0D%0Aclassification)+dengan+model+type+C-Classification+dan+kernel+Radial+Basis%0D%0AFunction+(RBF)%2C+serta+parameter+sigma+1+dan+cost+1+untuk+skema+data+latih+90%25%0D%0Adan+data+uji+10%25.+Nilai+akurasi+ini+meningkat+tajam+dibandingkan+tanpa+ROS+yang%0D%0Ahanya+sekitar+76%25.%0D%0AKata+Kunci+%3A+Diabetes+Melitus%2C+Ketidakseimbangan+Data%2C+Random+Oversampling%2C%0D%0ASupport+Vector+Machine&rft.publisher=FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM&rft.date=2023-02-08&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F69842%2F1%2FABSTRAK.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F69842%2F2%2FSKRIPSI%2520FULL.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F69842%2F3%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN.pdf&rft.identifier=++DHIFA+ZHAFIRAH%2C+1917031032++(2023)+PENANGANAN+IMBALANCE+DATA+DENGAN+RANDOM+OVERSAMPLING+(ROS)+PADA+KLASIFIKASI+PENDERITA+DIABETES+MENGGUNAKAN+SUPPORT+VECTOR+MACHINE+(SVM).++FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM%2C+UNIVERSITAS+LAMPUNG.++++(Submitted)++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F69842%2F