Jupiter
Vol 13 No 2 (2021): JUPITER Edisi Oktober 2021

Komparasi Metode Machine Learning dan Deep Learning untuk Deteksi Emosi pada Text di Sosial Media

Rona Nisa Sofia Amriza (Institut Teknologi Telkom Purwokerto)
Didi Supriyadi (Institut Teknologi Telkom Purwokerto)

Article Info

Publish Date
25 Oct 2021

Abstract

Emotion Detection is the process of human emotions recognition, it extracting emotions such as happy, sad, and angry, which are obtained from human natural language. Linguistic Style has a wide range, emotional representations occur to millions of people and makes it difficult to infer a person's emotion in a concrete way. Multilabel datasets are also a challenge to deal in emotion detection. Therefore, an in-depth study of the appropriate method for emotional detection is needed. This study performs a comparative analysis between machine learning methods and deep learning methods. The machine learning methods used are Naïve Bayes, Random Forest, SVM, Gradient Boosting and Logistic Regression. The deep learning methods used in this study include LSTM, CNN, MLP, GRU and RNN. This research discovered that Deep learning has a better performance than machine learning, it seen from the accuracy values ​​of LSTM, CNN, MLP, GRU and RNN which exceed the accuracy values ​​of Naïve Bayes, SVM, Logistic Regression, Gradient Boosting and Random Forest.

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Journal Info
Jupiter
Website

Abbrev

jupiter

Publisher

Politeknik Negeri Sriwijaya

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science

Description

Tentang Jurnal Ini Fokus dan Ruang Lingkup Bidang kajian yang dapat dimuat pada jurnal Jupiter meliputi dan tidak terbatas pada: Mobile Computing Image Processing Computer Graphic Artificial Intelligence Information Retrieval Computer Vision Algorithm & Complexity Data Mining Information System ...