Proceedings of the 2nd International Conference of Science and Technology for the Internet of Things, ICSTI 2019, September 3rd 2019, Yogyakarta, Indonesia

Research Article

The Implementation Of Left Corner Parsing In Indonesian Language

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  • @INPROCEEDINGS{10.4108/eai.20-9-2019.2292090,
        author={Dewi  Soyusiawaty and Andri  Pranolo},
        title={The Implementation Of Left Corner Parsing In Indonesian Language },
        proceedings={Proceedings of the 2nd International Conference of Science and Technology for the Internet of Things, ICSTI 2019, September 3rd 2019, Yogyakarta, Indonesia},
        publisher={EAI},
        proceedings_a={ICSTI},
        year={2020},
        month={3},
        keywords={parsing left corner indonesian language},
        doi={10.4108/eai.20-9-2019.2292090}
    }
    
  • Dewi Soyusiawaty
    Andri Pranolo
    Year: 2020
    The Implementation Of Left Corner Parsing In Indonesian Language
    ICSTI
    EAI
    DOI: 10.4108/eai.20-9-2019.2292090
Dewi Soyusiawaty1,*, Andri Pranolo1
  • 1: Informatics Department, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
*Contact email: dewi.soyusiawaty@tif.uad.ac.id

Abstract

Indonesian language is a national language spoken not only by Indonesian citizens but also foreign citizens when they are in Indonesia. The communication is carried out through a lot of media both written and orally. Computer based translator applications now not only rely on written input but also spoken one. Whereas, it’s not sure whether the inputted sentence is grammatically correct or not. When the inputted sentence is incorrect, it will influence the result given by the translator application. One method to know whether the input is correct or not is by checking the sentence pattern. This research explains left corner parsing applied on sentence pattern tracking. Left corner parsing is a combination of top down and bottom up parsing by taking top down prediction and bottom up tracking. From the two tracking techniques, the sentence will be parsed to be token per token and then the grammar rule which is previously determined is searched. With the tracking and prediction, a parser to parse the sentence will be gotten, so the sentence pattern will be identified. This research discusses and makes an auxiliary tool which function is to identify the pattern of Indonesian language sentences. As a result, it can be identified whether the pattern of the inputted sentence is correct or not based on the stored grammar rule in the application.