?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=PREDIKSI+GLIKOSILASI+PADA+N-%2C+C-+DAN+O-+DALAM+PROTEOM%0D%0AMANUSIA+MENGGUNAKAN+FITUR+SELEKSI+MRMR+DAN+ALGORITME%0D%0A%0D%0ASUPPORT+VECTOR+MACHINE.&rft.creator=NAURAH+NAZHIFAH%2C+1717051032&rft.subject=004+Pemrosesan+data+dan+ilmu+komputer&rft.description=Tubuh+manusia+mengandung+ribuan+protein.+Pada+proses+pembentukan+protein+banyak%0D%0Amengalami+modifikasi+pasca+translasi.+Salah+satu+hasil+dari+modifikasi+pasca+translasi%0D%0Aadalah+glikosilasi.+Glikosilasi+adalah+proses+penggabungan+glukosa+pada+struktur%0D%0A%0D%0Aprotein.+Pada+tubuh+manusia+glikosilasi+dapat+dilihat+dari+3+kategori%2C+yaitu+N-%0D%0Aglikosilasi%2C+O-glikosilasi+dan+C-glikosilasi.+Untuk+memahami+mekanisme+dan+peran%0D%0A%0D%0Afungsional+glikosilasi%2C+yaitu+dengan+cara+memprediksi+substrat+dari+situs+glikosilasi%0D%0Atersebut.+Pendekatan+komputasi+merupakan+salah+satu+cara+untuk+memprediksi+situs%0D%0Aglikosilasi+tersebut%2C+yaitu+menggunakan+algoritme+Support+Vector+Machine+(SVM).%0D%0AAlgoritme+ini+telah+banyak+digunakan+untuk+prediksi+dan+pengklasifikasian.+Pada%0D%0Apenelitian+ini+menggunakan+2+jenis+data+yaitu+data+Independent+dan+data+Benchmark.%0D%0AFitur+yang+digunakan+merupakan+fitur+ekstraksi+yang+menghasilkan+90+dimensi+dan%0D%0Afitur+seleksi+yang+menggunakan+Maximum+Redundancy+Minimum+Relevance+(MRMR)%0D%0Asebanyak+25%2C+50+dan+75+kolom.+Pengujian+klasifikasi+SVM+menggunakan+5-fold+cross%0D%0Avalidation+dan+confusion+matrix.+Hasil+akurasi+tertinggi+terletak+pada+penggunaan+fitur%0D%0Aseleksi+MRMR+sebanyak+75+kolom.+Pada+Data+Independent+N+akurasi+terbesar+sebesar%0D%0A86%2C66%25+pada+kernel+Sigmoid%2C+sedangkan+untuk+data+Independent+C+akurasi+sebesar%0D%0A87%2C5%25+pada+kernel+Sigmoid+dan+untuk+data+Independent+O+akurasi+sebesar+89%2C31%25%0D%0Aberada+di+kernel+RBF.+Pada+data+Benchmark+N+akurasi+terbesar+sebesar+70%2C54%25+pada%0D%0Akernel+RBF%2C+sedangkan+untuk+data+Benchmark+C+akurasi+terbesar+sebesar+95%2C06%25+dan%0D%0Auntuk+data+Benchmark+O+terdapat+di+kernel+RBF+dengan+akurasi+terbesar+yaitu+92%2C64%25.%0D%0AKata+Kunci%3A+Glikosilasi%2C+MRMR%2C+Post+Translation+Modification%2C+Support+Vector%0D%0AMachine.%0D%0AThe+human+body+contains+thousands+of+proteins.+In+the+process+of+protein+formation%2C%0D%0Athere+are+many+post-translational+modifications.+One+result+of+post-translational%0D%0Amodification+is+glycosylation.+Glycosylation+is+the+process+of+combining+glucose+in%0D%0Aprotein+structures.+In+the+human+body%2C+glycosylation+can+be+seen+from+3+categories%2C%0D%0Anamely+N-glycosylation%2C+O-glycosylation+and+C-glycosylation.+To+understand+the%0D%0Amechanism+and+functional+role+of+glycosylation+by+predicting+the+substrate+of+the%0D%0Aglycosylation+site.+The+computational+approach+is+one+way+to+predict+the+glycosylation%0D%0Asite%2C+using+the+Support+Vector+Machine+(SVM)+algorithm.+This+algorithm+has+been%0D%0Awidely+used+for+prediction+and+classification.+This+study+uses+2+types+of+data%2C+namely%0D%0AIndependent+data+and+Benchmark+data.+The+features+used+are+feature+extraction+which%0D%0Aproduces+90+dimensions+and+feature+selection+using+Maximum+Redundancy+Minimum%0D%0ARelevance+(MRMR)+of+25%2C+50+and+75+columns.+The+SVM+classification+test+uses+5-fold%0D%0Across+validation+and+confusion+matrix.+The+highest+accuracy+result+lies+in+the+use+of+the%0D%0A75+column+MRMR+selection+feature.+In+Independent+data+N%2C+the+highest+accuracy+is%0D%0A86.66%25+in+the+Sigmoid+kernel%2C+while+for+Independent+data+C%2C+the+accuracy+is+87.5%25+in%0D%0Athe+Sigmoid+kernel+and+for+Independent+data+O%2C+the+accuracy+is+89.31%25+in+the+RBF%0D%0Akernel.+In+Benchmark+data+N%2C+the+highest+accuracy+is+70.54%25+in+the+RBF+kernel%2C+while%0D%0Afor+Benchmark+data+C+the+highest+accuracy+is+95.06%25+and+for+Benchmak+data+O+is+in%0D%0Athe+RBF+kernel+with+the+largest+accuracy%2C+which+is+92.64%25.%0D%0AKeywords%3A+Glycosylation%2C+MRMR%2C+Post+Translation+Modification%2C+Support+Vector%0D%0AMachine&rft.publisher=FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM&rft.date=2021&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F61907%2F1%2FABSTRAK%2520-%2520Naurah%2520Nazhifah.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F61907%2F2%2FSKRIPSI%2520FULL%2520-%2520Naurah%2520Nazhifah.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F61907%2F3%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN%2520-%2520Naurah%2520Nazhifah.pdf&rft.identifier=++NAURAH+NAZHIFAH%2C+1717051032++(2021)+PREDIKSI+GLIKOSILASI+PADA+N-%2C+C-+DAN+O-+DALAM+PROTEOM+MANUSIA+MENGGUNAKAN+FITUR+SELEKSI+MRMR+DAN+ALGORITME+SUPPORT+VECTOR+MACHINE.++FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM%2C+UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F61907%2F