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PARALLEL PROCESSING FOR STEMMING AND POS-TAGGING IN INDONESIAN TEXT

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307000825	T86639	T866392023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T866392023

Publisher

Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022

Collation

xiv, 91 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004. 07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Jurusan Teknik Informatika
teknik komputer informatika

Specific Detail Info

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Statement of Responsibility

SEPTA

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