?url_ver=Z39.88-2004&rft_id=1617051095&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=PERBANDINGAN+KINERJA+SUPPORT+VECTOR+MACHINE+(SVM)+DAN+CONVOLUTIONAL+NEURAL+NETWORK+(CNN)+UNTUK+KLASIFIKASI+KUPU-KUPU&rft.creator=ANINDITA%2C++VEYBA+ALDARIZKY&rft.subject=000+Ilmu+komputer%2C+informasi+dan+pekerjaan+umum&rft.subject=005+Pemrograman+komputer%2C+program+dan+data&rft.description=Taman+Kupu+Gita+Persada+adalah+tempat+yang+digunakan+untuk+memelihara+kupu-kupu+yang+berlokasi+di+Lampung+dan+memelihara+kurang+lebih+211+spesies+kupu-kupu+yang+dikembangbiakan.+Kupu-kupu+memiliki+berbagai+jenis+tekstur+dan+warna+pada+sayapnya.+Keterbatasan+pada+mata+manusia+untuk+membedakan+tekstur+dan+warna+pada+spesies+kupu-kupu+adalah+alasan+untuk+melakukan+penelitian+identifikasi+kupu-kupu+berdasarkan+pengenalan+pola.+Dataset+yang+digunakan+terdiri+dari+800+gambar+kupu-kupu+sayap+bagian+atas+dari+delapan+spesies%3A+Ariadne+ariadne%2C+Cethosia+penthesilea%2C+Papilio+peranthus%2C+Pacliopta+aristolochiae%2C+Papilio+memnon%2C+Papilio+nephelus%2C+Parantica+aspiasa%2C+dan+Troides+helena.+Tahap+pre-processing+yang+dilakukan+adalah+scaling%2C+segmentasi%2C+dan+grayscale.+Metode+SVM+digunakan+untuk+mengenali+ciri-ciri+citra+kupu-kupu+menggunakan+arah+sudut+0%C2%B0%2C+45%C2%B0%2C+90%C2%B0%2C+dan+135%C2%B0.+Metode+klasifikasi+SVM+pada+penelitian+ini+menggunakan+metode+kernell.+Metode+klasifikasi+CNN+pada+penelitian+ini+menggunakan+nilai+learning+rate+0%2C001+dan+0%2C01+dengan+nilai+epoch+10%2C+30%2C+50%2C+80%2C+dan+100.+Hasil+pada+penelitian+ini+adalah+klasifikasi+CNN+menghasilkan+tingkat+akurasi+tertinggi+sebesar+99%2C7%25+dan+kesalahan+klasifikasi+sebesar+0%2C3%25+pada+pengujian+dengan+nilai+epoch+%3D+100+dan+learning+rate+%3D+0%2C01%2C+klasifikasi+SVM+menghasilkan+tingkat+akurasi%0D%0Atertinggi+sebesar+67%2C50%25+dan+kesalahan+klasifikasi+sebesar+32%2C50%25+pada+pengujian+dengan+arah+sudut+135%C2%B0.+Kinerja+metode+CNN+memiliki+akurasi+32%2C19%25+lebih+tinggi+dibandingkan+dengan+kinerja+metode+SVM+pada+klasifikasi+kupu-kupu.%0D%0A%0D%0AKata+kunci%3A+Kupu-kupu%2C+CNN%2C+SVM%2C+Pengenalan+pola%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0Aabstract%0D%0A%0D%0AGita+Persada+Butterfly+Park+is+used+to+keep+butterflies+located+in+Lampung+and+maintains+approximately+211+species+of+butterflies+that+are+bred.+Butterflies+have+a+variety+of+textures+and+colors+on+their+wings.+The+limitation+of+the+human+eye+to+distinguish+texture+and+color+in+butterfly+species+is+the+reason+for+conducting+butterfly+identification+studies+based+on+pattern+recognition.+The+dataset+used+consisted+of+800+images+of+upper-winged+butterflies+from+eight+species%3A+Ariadne+ariadne%2C+Cethosia+penthesilea%2C+Papilio+Peranthus%2C+Pacliopta+aristolochiae%2C+Papilio+memnon%2C+Papilio+nephelus%2C+Parantica+aspiasa%2C+and+Troides+helena.+The+pre-processing+stage+is+scaling%2C+segmentation%2C+and+grayscale.+The+SVM+method+is+used+to+identify+the+characteristics+of+the+butterfly+image+using+the+angles+of+0%C2%B0%2C+45%C2%B0%2C+90%C2%B0%2C+and+135%C2%B0.+The+SVM+classification+method+in+this+study+using+kernel+method.+The+CNN+classification+method+in+this+study+uses+a+learning+rate+value+of+0.001+and+0.01+with+epoch+values+of+10%2C+30%2C+50%2C+80%2C+and+100.+The+results+in+this+study+are+that+the+CNN+classification+produces+the+highest+accuracy+rate+of+99.7%25+and+the+error+rate+is+0.3%25+in+the+test+with+an+epoch+value+%3D+100+and+a+learning+rate+%3D+0.01%2C+SVM+classification+produces+an+accuracy+level+the+highest+was+67%2C50%25+and+the+error+rate%0D%0Awas+32%2C50%25+in+the+test+with+an+angle+of+135%C2%B0+.+The+performance+of+the+CNN+method+had+higher+accuracy+32%2C19%25+than+the+performance+of+the+SVM+method+on+the+classification+of+the+butterflies.%0D%0A%0D%0AKeywords%3A+Butterfly%2C+CNN%2C+SVM%2C+Pattern+Recognition&rft.publisher=FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM+&rft.date=2023-02-22&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F71818%2F1%2FABSTRAK.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F71818%2F2%2FSKRIPSI%2520FULL.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F71818%2F3%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN.pdf&rft.identifier=++ANINDITA%2C+VEYBA+ALDARIZKY++(2023)+PERBANDINGAN+KINERJA+SUPPORT+VECTOR+MACHINE+(SVM)+DAN+CONVOLUTIONAL+NEURAL+NETWORK+(CNN)+UNTUK+KLASIFIKASI+KUPU-KUPU.++FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM+%2C+UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F71818%2F