FEATURE EXTRACTION MENGGUNAKAN LEXICON PADA DATASET PENGENALAN EMOSI TEKS BERBAHASA INDONESIA

Nurkasanah, Aprilia (2022) FEATURE EXTRACTION MENGGUNAKAN LEXICON PADA DATASET PENGENALAN EMOSI TEKS BERBAHASA INDONESIA. S1 - Sarjana thesis, Universitas AMIKOM Yogyakarta.

[img] Text (ISI BAB)
Skripsi 18.11.1913 Aprilia Nurkasanah.pdf
Download (782kB)
[img] Archive (SOURCE CODE)
Source Code 18.11.1913 Aprilia Nurkasanah.zip
Restricted to Repository staff only
Download (1MB)

Abstract

Text mining is a part of Neural Language Processing (NLP), also known as text analytics. Text mining includes sentiment analysis and emotion analysis which are often used to analyse social media, news, or other media in written form. The emotional breakdown is a level of sentiment analysis that categorises text into negative, neutral, and positive sentiments. Emotion is organized into several classes. This study categorized emotion into anger, fear, happiness, l;ove, and sadness. This study proposed feature extraction using Lexicon and TF-IDF on the emotion recognition dataset of Indonesian texts. InSet Lexicon Dictionary is used as the corpus in performing the feature exstraction. Therefore, InSet Lexicon was chosen as the dictionary to perform feature extraction in this study. The results show that InSet Lexicon has poor performance in feature extraction by showing an accuracy of 30%, while TF-IDF is 62%.

Item Type: Thesis (S1 - Sarjana)
Contributor:
Pembimbing
Hayaty, Mardhiya
Uncontrolled Keywords: Emotion Recognition text, Lexicon, LexiconInSet, Feature Extraction, Random Forest
Subjects: 000 - Komputer, Informasi dan Referensi Umum > 000 Ilmu komputer, ilmu pengetahuan dan sistem-sistem > 000 Ilmu komputer, informasi dan pekerjaan umum
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: RC Universitas AMIKOM Yogyakarta
Date Deposited: 19 Aug 2022 04:05
Last Modified: 19 Aug 2022 04:10
URI: http://eprints.amikom.ac.id/id/eprint/5923

Actions (login required)

View Item View Item