Analisis Sentimen Terhadap Ulasan Pengguna MRT Jakarta Menggunakan Information Gain dan Modified K-Nearest Neighbor

Adella Ayu Paramitha (Fakultas Ilmu Komputer, Universitas Brawijaya)
Indriati Indriati (Fakultas Ilmu Komputer, Universitas Brawijaya)
Yuita Arum Sari (Fakultas Ilmu Komputer, Universitas Brawijaya)

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 4 No 4 (2020): April 2020

Mass Rapid Transit (MRT) is one of rail based public transportation that operates in DKI Jakarta. This transportation is expected to be able to reduce traffic congestion because of private car and motorcycle usage. Improvement on service quality is one of the way to attract people to use public transportation. Service quality improvement can be done by extracting positive and negative feedbacks from users using sentiment analysis. Methods used in this research are Modified K-Nearest Neighbor (MKNN) for classification and Information Gain for feature selection. Comment data will be carried out in the stages of pre-processing, vectorize, feature selection, term weighting using TF-IDF, and classification process. Based on evaluation result, we obtained accuracy value of 0,86769 and f-measure value of 0,86265 with k=3 and threshold-25% as parameter.