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All Journal JAIS (Journal of Applied Intelligent System) Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Wisnu Agastya
Universitas Dian Nuswantoro
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Journal : Jurnal Nasional Teknik Elektro dan Teknologi Informasi

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Pemetaan Emosi Dominan pada Kalimat Majemuk Bahasa Indonesia Menggunakan Multinomial Naïve Bayes Wisnu Agastya; Aripin
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 2: Mei 2020
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1248.65 KB) | DOI: 10.22146/jnteti.v9i2.157

Abstract

This study aimed at mapping Indonesian sentences into emotion classes based on the classification process in those sentences. The results of emotion mapping can be applied in various fields, such as production of animated films and games, analysis of facial expressions, human-computer interactions, and development of other expressive virtual characters, specifically to produce facial expressions that match the spoken sentences. The method used for the emotion mapping process was the text classification using multinomial naïve Bayes model that was accompanied by dominant boundary equation. Multinomial naïve Bayes model in the text classification is used to determine the types and the emotional intensity of Indonesian sentences, whereas dominant boundary equation iss used to determine the threshold in order to identify the dominant classes. The emotion classes used as references are six basic emotion classes according to Paul Ekman, i.e., happiness, sadness, anger, fear, disgust, and surprise. The experiment on the process of mapping emotions used Indonesian single and compound sentences. The experimental results show that the text classification using multinomial naïve Bayes model accompanied by dominant boundary equation can map compound sentences into several classes of dominant emotions.
Ekstraksi Emosi Majemuk Kalimat Bahasa Indonesia Menggunakan Convolutional Neural Network Aripin; Wisnu Agastya; Hanny Haryanto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1359.277 KB) | DOI: 10.22146/jnteti.v10i2.1051

Abstract

Facial expressions can strengthen the information conveyed in interactive communication. In the field of developing virtual characters specifically for facial characters, facial expressions are needed to animate a facial virtual character to make it look natural like a human. One type of emotional expression is a compound emotional expression, which is a combination of two or more basic emotions. For example, the expression of disappointed emotions is a combination of anger and sadness. Facial expressions can appear due to emotional stimulation, one of which is the meaning of the sentence. This research aims to extract emotional data from Indonesian sentences using the multi-label classification process of the CNN model so as to produce compound facial expressions that are applied in virtual character animation. The basic emotion classes used in the classification process are anger, disgust, fear, happiness, sadness, and surprise. Based on the experimental results, the CNN model can produce an accuracy of 94.5% with the composition of training data and test data is 8: 2. The classification process result shows that each sentence can produce more than one basic emotion class that forms compound expressions. The results of the visualization of compound expressions for each sentence can represent compound expressions.
Co-Authors Aripin Hanny Haryanto