ANALISIS PENENTUAN DOSEN PEMBIMBING SKRIPSI MAHASISWA MENGGUNAKAN NAIVE BAYES CLASSIFIER

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dc.contributor.authorRahayu, Sri
dc.contributor.supervisorFatayat, Fatayat
dc.contributor.supervisorSalambue, Roni
dc.contributor.supervisorAminuddin, Al
dc.date.accessioned2021-08-23T03:19:08Z
dc.date.available2021-08-23T03:19:08Z
dc.date.issued2020-09
dc.description.abstractDetermination of the mentor lecturer for students is very influential in completing the final task. Lecturers who are competent and in accordance with the field of student's final assignment able to direct of the student's final assignment. In this thesis, text mining is used to classify the appropriate guidance lecturers for students in completing the final assignment. Classification is applied to the title of the student's final assignment based on experience and field of mentor lecturers. The algorithm used naive bayes classifier algorithm. Before the data classification processed at the text preprocessing stage, which consist of case folding, stopcharacter removal, stopword, stemming, and weighted. Evaluation to measure the accuracy of this system using confussion matrix which resulted in 78% accuracy in mentor lecturers and generate acuration of 95% in field of expertise.en_US
dc.description.sponsorshipJurusan Ilmu Komputer Fakultas Matematika dan Ilmu Pengetahuan Alamen_US
dc.identifier.otherwahyu sari yeni
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/10089
dc.language.isoenen_US
dc.subjectMentor Lectureren_US
dc.subjectNaive Bayes Classifieren_US
dc.subjectText preprocessingen_US
dc.subjectfinal projecten_US
dc.titleANALISIS PENENTUAN DOSEN PEMBIMBING SKRIPSI MAHASISWA MENGGUNAKAN NAIVE BAYES CLASSIFIERen_US
dc.typeArticleen_US

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