?url_ver=Z39.88-2004&rft_id=1917051030&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=EVALUASI+KINERJA+METODE+SUPPORT+VECTOR+MACHINE+(SVM)%2C+NAIVE+BAYES+DAN+DECISION+TREE+UNTUK+DIAGNOSA+PENYAKIT+JANTUNG&rft.creator=SENDY+%2C+HANI+PRAMITA&rft.subject=500+ilmu+pengetahuan+alam+dan+matematika&rft.description=Jantung+adalah+otot+yang+bekerja+paling+keras+di+tubuh.+Jantung+rata-rata+berdetak+100.000+kali+sehari%2C+untuk+memasok+oksigen+ke+seluruh+tubuh.Ada+berbagai+jenis+penyakit+jantung.+Pembelajaran+mesin+paling+banyak+digunakan+untuk+prediksi+penyakit+di+bidang+medis.+Banyak+peneliti+menjadi+tertarik+menggunakan+pembelajaran+mesin+untuk+mendiagnosis+penyakit+karena+membantu+mengurangi+waktu+diagnosis+dan+meningkatkan+akurasi+dan+efisiensi.+Data+yang+digunakan+pada+penelitian+ini+yaitu+data+dari+Heart+Disease+Dataset+yang+bersumber+dari+Public+Health+Dataset+dengan+jumlah+data+1025+dan+atribut+14+atribut.+Metode+yang+digunakan+dalam+klasifikasi+penderita+penyakit+jantung+yaitu+Support+Vector+Machine+(SVM)%2C+Naive+Bayes+dan+Decision+Tree.+Mendapatkan+hasil+perbandingan+hasil+klasifikasi+penyakit+jantung+model+Support+Vector+Machine+(SVM)%2C+model+Naive+Bayes+dan+model+Decision+Tree+dapat+digunakan+sebagai+salah+satu+metode+prediksi+penyakit+jantung.+Model+Support+Vector+Machine+(SVM)+dan+Decision+Tree+memiliki+performa+ketepatan+prediksi+sangat+baik+dengan+memperoleh+nilai+akurasi+sebesar+99%25+dan+metode+Naive+Bayes+yang+memperoleh+nilai+akurasi+yaitu+84%25.%0D%0A%0D%0AKata+Kunci+%3A+Jantung%2C+Pembelajaran+Mesin%2C+Klasifikasi.%0D%0AThe+heart+is+the+hardest+working+muscle+in+the+body.+The+average+heart+beats+100%2C000+times+a+day%2C+to+supply+oxygen+throughout+the+body.+There+are+different+types+of+heart+disease.+Machine+learning+is+most+widely+used+for+disease+prediction+in+the+medical+field.+Many+researchers+are+becoming+interested+in+using+machine+learning+to+diagnose+diseases+because+it+helps+reduce+diagnosis+time+and+increases+accuracy+and+efficiency.+The+data+used+in+this+study+are+data+from+the+Heart+Disease+Dataset+which+originates+from+the+Public+Health+Dataset+with+a+total+of+1025+data+and+14+attributes.+The+methods+used+in+the+classification+of+people+with+heart+disease+are+Support+Vector+Machine+(SVM)%2C+Naive+Bayes%2C+and+Decision+Tree.+Obtaining+the+results+of+a+comparison+of+the+results+of+the+classification+of+heart+disease+with+the+Support+Vector+Machine+(SVM)+model%2C+the+Naive+Bayes+model%2C+and+the+Decision+Tree++model+can+be+used+as+a+method+of+predicting+heart+disease.+The+Support+Vector+Machine+(SVM)+and+Decision+Tree+models+have+very+good+predictive+accuracy+performance+by+obtaining+an+accuracy+value+of+99%25+and+the+Naive+Bayes+method+which+obtains+an+accuracy+value+of+84%25.%0D%0A%0D%0AKeywords+%3A+Heart%2C+Machine+Learning%2C+Classification.%E2%80%83&rft.publisher=FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM&rft.date=2023-08-23&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F75571%2F1%2FABSTRAK.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F75571%2F2%2FSKRIPSI%2520FULL.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F75571%2F3%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN.pdf&rft.identifier=++SENDY+%2C+HANI+PRAMITA++(2023)+EVALUASI+KINERJA+METODE+SUPPORT+VECTOR+MACHINE+(SVM)%2C+NAIVE+BAYES+DAN+DECISION+TREE+UNTUK+DIAGNOSA+PENYAKIT+JANTUNG.++FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM%2C+UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F75571%2F