Bandung Regency, West Java, Indonesia
Project: Implementation of Classification Methods for Mathematics and Bahasa Indonesia Questions in Elementary, Junior High School, and Senior High School Levels
- managed dataset (about 340 Mathematics multiple-choices questions) by labelling all data into three labels (easy, medium, or hard) and cleaning data which is invalid
- built and trained text classification models with Support Vector Machine (SVM) and Multinomial Naïve Bayes (MNB) with Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF) as feature extraction, and succeed to reach models performance upper 70% accuracy score
- achieved grade 95/100 final score from the field supervisor