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All Journal Jurnal technoscientia JURNAL TEKNOLOGI TECHNOSCIENTIA
Naniek Widyastuti
Teknik Informatika, Institut Sains & Teknologi AKPRIND Yogakarta
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Earth & Planetary Sciences Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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APLIKASI OPINION MINING DAN SENTIMENT ANALYSIS UNTUK MERANCANG MESIN PENCARI OPINI PADA KUESENER MAHASISWA Amir Hamzah; Naniek Widyastuti
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 9 No 1 Agustus 2016
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1268.121 KB) | DOI: 10.34151/technoscientia.v9i1.143

Abstract

The measurement of academic services using questionnaires with multiple choice answers generally provide comments and advice columns. In the data analysis results, comments and suggestions made by the thousands of students can not be utilitized due to the lack of analysis tools. Whereas comments and suggestions can actually contain student opinions on various things, such as facilities, faculty, library and others. Opinion mining and sentiment analysis as a new tool in text mining can be applied to the data to utilitize comments and suggestions. This research applied HMM-POS Tagger to give automatically POS TAG to the sentence based on training POS TAG data by using the Hidden Markov Model. By implementing POS TAG pattern the comments can then be determined whether it was opinion or not. Morever if it were opinion it can be determinied its target and also the orientation of the opinion whether it is positive or negative. The data used was 1,000 comments given POS-TAG manually and 1,000 comments as test data. Sentiment analysis is applied using four methods of classification, namely SVM, NBC, ME and KM-Clustering. The result showed that the accuracy of POS-Tagger was 0.95 and the avarage of accuracy of four classification method was 0.85.
APLIKASI OPINION MINING DAN SENTIMENT ANALYSIS UNTUK MERANCANG MESIN PENCARI OPINI PADA KUESENER MAHASISWA Amir Hamzah; Naniek Widyastuti
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 9 No 1 Agustus 2016
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/technoscientia.v9i1.143

Abstract

The measurement of academic services using questionnaires with multiple choice answers generally provide comments and advice columns. In the data analysis results, comments and suggestions made by the thousands of students can not be utilitized due to the lack of analysis tools. Whereas comments and suggestions can actually contain student opinions on various things, such as facilities, faculty, library and others. Opinion mining and sentiment analysis as a new tool in text mining can be applied to the data to utilitize comments and suggestions. This research applied HMM-POS Tagger to give automatically POS TAG to the sentence based on training POS TAG data by using the Hidden Markov Model. By implementing POS TAG pattern the comments can then be determined whether it was opinion or not. Morever if it were opinion it can be determinied its target and also the orientation of the opinion whether it is positive or negative. The data used was 1,000 comments given POS-TAG manually and 1,000 comments as test data. Sentiment analysis is applied using four methods of classification, namely SVM, NBC, ME and KM-Clustering. The result showed that the accuracy of POS-Tagger was 0.95 and the avarage of accuracy of four classification method was 0.85.
Co-Authors Amir Hamzah