They reported that the performance of classification could be enhanced when they customize the parameter within the algorithm to gain a maximum result. The following methods are examples of the detection algorithm based on classification and clustering, which means classifying like Support Vector Machine (SVM), Naïve Bayes, K-Nearest Neighbors (KNN), Decision Tree and many others. Until today, there have been at least ten machine learning algorithms which can be used for both classification and clustering. The detection is part of a data mining process, namely classification, and clustering. Detection of human emotion is potential to render the development of diverse aspects of life such as entertainment, learning, and other elements.

This phenomenon is real, considering that emotion as a human expression implies activities done by human beings and their excitement can be detected based on the data measured from them: voice, face, body, and physiology. INTRODUCTION Currently, human emotion is an important thing and has become a concern in various fields of research, including computer science. All rights reserved.Ĭorresponding Author: Djoko Budiyanto Setyohadi, Magister Teknik Informatika, UniversitasAtma Jaya Yogyakarta, Jl. Received Jun 12th, 201x Revised Aug 20th, 201x Accepted Aug 26th, 201x Keyword: Emotion detection Support Vector Machine Galvanic Skin ResponseĬopyright © 201x Institute of Advanced Engineering and Science. It means that the emotion detection can be done satisfactorily and well performed. Our method shows that the accuracy is about 75.65% while ROC is about 0.8019. To validate the proposed approach, Receiver Operating Characteristic (ROC) curve, and accuracy measurement are used. Furthermore, Support Vector Machine and a correct preprocessing are performed to classify the GSR data. We used the Positive and Negative Affect Schedule (PANAS) method to get a good data training. This paper describes a method on detection emotion using Galvanic Skin Response (GSR) data.

The process involves the experimental research in psychological experiment and classification methods. Universitas Atma Jaya Yogyakarta, Yogyakarta 55281, Indonesia ** Psychology Department, Universitas Gajah Mada, Yogyakarta, Indonesia *** Faculty of Computing and Information Technology, King Abdulaziz University, Rabigh 21911, Saudi ArabiaĮmotion detection is a very exhausting job and needs a complicated process moreover, these processes also require the proper data training and appropriate algorithm. Galvanic Skin Response Data Classification for Emotion Detection DjokoBudiyantoSetyohadi*, Sri Kusrohmaniah**, Sebastian Bagya Gunawan*, Pranowo*, Anton Satria Prabuwono***, *Departement of Informatics Engineering. International Journal of Electrical and Computer Engineering (IJECE) Vol.8, No.5, October 2018, pp. International Journal of Electrical and Computer Engineering (IJECE), 8(6). Galvanic Skin Response Data Classification for Emotion Detection.

Galvanic skin response graph