PARALLEL PROCESSING FOR STEMMING AND POS-TAGGING IN INDONESIAN TEXT

RAHMADANI, MUHAMMAD WAHYU and Abdiansah, Abdiansah and Marieska, Mastura Diana (2022) PARALLEL PROCESSING FOR STEMMING AND POS-TAGGING IN INDONESIAN TEXT. Undergraduate thesis, Sriwijaya University.

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Abstract

Stemming and POS-Tagging is part of the pre-processing of raw text data in the natural language processing field which aims to produce more structured data and as an initial step that greatly affects processing performance before being processed at a further stage. In its application for Indonesian text, the efficiency level of process performance for these two stages is still low, especially for large data sizes. Parallel processing method using the python multiprocessing module was applied in this study to see the reduction in processing time for the Stemming and POS Tagging process and also to observe the impact of implementing this parallel processing method on the devices used. Results showed that the highest reduction was 78.26% for the POS-Tagging process using test data size range of 10 MB – 70 MB and 63.28% for the Stemming process using test data size range of 7 MB – 25 MB. Processor allocation in parallel processing and data size affect device performance in terms of increasing device temperature and memory consumption.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	parallel processing, Stemming, POS-Tagging. Indonesian text
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76 Computer software Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.76.I58.A3115 Computer science. Computers. Intelligent agents (Computer software) Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.E94 Computer system performance. Computer Communication Networks. Computer science. Logic design. Operating systems (Computers). Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.Z55 Apache Hadoop (Computer file) Electronic data processing--Distributed processing. File organization (Computer science) Data mining. Streaming technology (Telecommunications)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	S.Kom Muhammad Wahyu Rahmadani
Date Deposited:	19 Jan 2023 05:19
Last Modified:	19 Jan 2023 05:19
URI:	http://repository.unsri.ac.id/id/eprint/86639

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