Klasifikasi Judul Skripsi Program Studi Teknik Informatika Menggunakan Algoritma Naive Bayes

Oleh Fitria Nurhayati dan Arfiani Nur Khusna

Abstract:

Thesis preparation at UAD Informatics Engineering Study Program is divided into 2 areas of interest, namely Intelligent Systems (SC) and Software and Data Engineering (relata). The existing thesis title data is only used as an archive, and has never been processed or classified to find out the thesis topic trends based on the student’s area of interest each year. So there is no reference for curriculum evaluation. This research includes the data collection stage, the division of data into 2 parts (training data and test data), manual labeling of training data, text prepocessing, and classification. This study uses 1290 thesis title data, showing the results of the thesis title taking trend in 2013 to 2018 most of the students took the title relatively. Accuracy testing has a value of 94.6%, precision 97.3% and recall 85.7%.

Key Words: Confussion Matrix, Judul Skripsi, K-Fold Cross Validation, Klasifikasi, Naive Bayes