relation: https://digilib.uin-suka.ac.id/id/eprint/42689/
title: PART OF SPEECH TAGGING BAHASA INDONESIA MENGGUNAKAN ALGORITMA DECISION TREE
creator: Ahmad Ardiyanto, NIM.: 16650061
subject: Tehnik Informatika
subject: Bahasa Indonesia
description: This study aims to apply and analyze Indonesian Part of Speech Tagging  (POS Tagging) using the Decision Tree algorithm. The POS Tagging process can  use language dictionaries as a reference or assist in the provision of word classes  (tags), but there are some constraints such as the determination of word classes for  ambiguous words and words that are not in the dictionary, so a further POS Tagging  approach is needed to overcome this problem.   This study uses Indonesian Language Dictionary (KBBI) data and Indonesian  CNN online news data. The news data is then carried out the process of  preprocessing, feature extraction, and vectorization so as to produce a dataset of  40,071 which are then used as training data to build the Decision Tree model.  POS Tagging testing in this study obtained an accuracy of 95.3%, and a  percentage of success of 90.0% in tagging words that were not on KBBI and success  of 91.9% for tagging ambiguous words. The results of the implementation of the  POS Tagging application for Indonesian sentences are already good although not  yet at maximum.
date: 2020-07-17
type: Thesis
type: NonPeerReviewed
format: text
language: id
identifier: https://digilib.uin-suka.ac.id/id/eprint/42689/1/16650061_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf
format: text
language: id
identifier: https://digilib.uin-suka.ac.id/id/eprint/42689/2/16650061_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf
identifier:   Ahmad Ardiyanto, NIM.: 16650061  (2020) PART OF SPEECH TAGGING BAHASA INDONESIA MENGGUNAKAN ALGORITMA DECISION TREE.  Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.