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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Media A. Ayu
Sampoerna University
Computer Science & IT

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Quality Translation Enhancement Using Sequence Knowledge and Pruning in Statistical Machine Translation Media A. Ayu; Teddy Mantoro; Jelita Asean
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 2: April 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i2.8687

Abstract

Machine translation has two important parts, a learning process which followed by a translation process. Unfortunately, most of the translation process requires complex operations and in-depth knowledge of the languages in order to give a good quality translation. This study proposes a better approach, which does not require in-depth knowledge of the linguistic properties of the languages, but it produces a good quality translation. This study evaluated 28 different parameters in IRSTLM language modeling, which resulting 270 millions experiments, and proposes a sequence evaluation mechanism based on a maximum evaluation of each parameter in producing a good quality translation based on NIST and BLEU. The parallel corpus and statistical machine learning for English and Bahasa Indonesia were used in this study. The pruning process, user interface, and the personalization of translation have a very important role in implementing of this machine translation. The result is quite promising. It shows that pruning process increases of the translation process time. The particular sequence knowledge/value parameter in translation process has a better performance than the other method using in-depth linguistic knowledge approaches. All these processes, including the process of parsing from a stand-alone mode to an online mode, are also discussed in detail.
An automatic lexicon generation for indonesian news sentiment analysis: a case on governor elections in Indonesia Media A Ayu; Sony Surya Wijaya; Teddy Mantoro
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1555-1561

Abstract

Sentiment analysis has been popularly used in analyzing data from the internet.  One of the techniques used is lexicon based sentiment analysis.  Generating lexicon is not an easy process, and lexicon in Bahasa Indonesia is rarely available.  This paper proposes an automatic lexicon generation in Bahasa Indonesia for sentiment analysis purpose.  Experiments were performed using the generated lexicon for doing sentiment analysis on Indonesian political news about the 2018 governor election in three provinces in Indonesia. The conducted experiments show promising results where it can predict the candidate’s rank, the election winner, and the percentage of votes for each candidate with better accuracy than the previous work which used manually generated lexicon.
Co-Authors Jelita Asean Sony Surya Wijaya Teddy Mantoro