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Universitas Merdeka Pasuruan
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Personality Classification through Social Media Using Probabilistic Neural Network Algorithms 1
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 1 No. 1 (2019): November 2019
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (305.425 KB) | DOI: 10.25139/ijair.v1i1.2025

Abstract

Today the internet creates a new generation with modern culture that uses digital media. Social media is one of the popular digital media. Facebook is one of the social media that is quite liked by young people. They are accustomed to conveying their thoughts and expression through social media. Text mining analysis can be used to classify one's personality through social media with the probabilistic neural network algorithm. The text can be taken from the status that is on Facebook. In this study, there are three stages, namely text processing, weighting, and probabilistic neural networks for determining classification. Text processing consists of several processes, namely: tokenization, stopword, and steaming. The results of the text processing in the form of text are given a weight value to each word by using the Term Inverse Document Frequent (TF / IDF) method. In the final stage, the Probabilistic Neural Network Algorithm is used to classify personalities. This study uses 25 respondents, with 10 data as training data, and 15 data as testing data. The results of this study reached an accuracy of 60%.
Speech to Text Processing for Interactive Agent of Virtual Tour Navigation 1
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 1 No. 1 (2019): November 2019
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (271.812 KB) | DOI: 10.25139/ijair.v1i1.2030

Abstract

The development of science and technology is one way to replace the method of human interaction with computers, one of which is to provide voice input. Conversion of sound into text form with the Backpropagation method can be understood and realized through feature extraction, including the use of Linear Predictive Coding (LPC). Linear Predictive Coding is one way to represent the signal in obtaining the features of each sound pattern. In brief, the way this speech recognition system worked was by inputting human voice through a microphone (analog signal) which then sampled with a sampling speed of 8000 Hz so that it became a digital signal with the assistance of sound card on the computer. The digital signal from the sample then entered the initial process using LPC, so that several LPC coefficients were obtained. The LPC outputs were then trained using the Backpropagation learning method. The results of the learning were classified with a word and stored in a database afterwards. The results of the test were in the form of an introduction program that able display the voice plots. the results of speech recognition with voice recognition percentage of respondents in the database iss 80% of the 100 data in the test in Real Time
Knowing Personality Traits on Facebook Status Using the Naïve Bayes Classifier 1
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 1 (2020): May 2020
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2169.831 KB) | DOI: 10.25139/ijair.v2i1.2636

Abstract

With the development of social media trends among students by using Facebook social media, students can communicate and pour out everything that is felt in the form of status. Personality is the character or various characters of a person - therefore, how a person to adjust to the surrounding environment for the achievement of communication smoothly. In the personality category, many things classify a person's category in the psychologist theory. In this exercise, the Big Five, the psychologist theory, is described in five codes, namely Openness, Conscientiousness, Extraversion, Agreeables, Neuroticism. Naive Bayes Classifier is used to determine the highest probability value with the aim to determine the highest value. The data used are two namely training data and testing data obtained from the Facebook status of students. From the data obtained can be tested in the system that the accuracy value is 88%.
An Implementation of MMS Steganography With The LSB Method 1
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 1 (2020): May 2020
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1378.483 KB) | DOI: 10.25139/ijair.v2i1.2653

Abstract

Around the world, the internet (interconnection network) has developed into one of the most popular data communication media. With a variety of illegal information retrieval techniques that are developing, many people are trying to access information that is not their right. Various techniques to protect confidential information from unauthorized persons have been carried out to secure important data. Steganography is a science and art for writing hidden messages so that no other party knows the existence of the message. The three results of tests conducted by the LSB method can be used to hide messages into images. The first test was successful by writing a message that less than 31 characters stored in the picture, the second succeeded in writing a message equal to 31 characters stored in the picture, the third failed to write a message of more than 31 characters stored in the picture.
Switching Systems Designing Based on IoT 1
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 2 (2020): November 2020
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2039.464 KB) | DOI: 10.25139/ijair.v2i2.3138

Abstract

The development of technology has progressed very rapidly in a short period, as has technology that has recently been developed in various aspects of life, namely the Internet of Things. In the past, controlling household electrical appliances was usually done directly by pressing a button on the house's wall and was very ineffective when the house owner was out of town while the house was empty. With the Internet of Things technology, a system can be applied in everyday life, namely controlling household electrical appliances to turn off and remotely using internet communication via an android smartphone. In this system design, a control design using a series of microcontrollers and relays connected to a smartphone via the internet is used because the microcontroller already has a  Wireless Fidelity (WIFI) module. The results of controlled tests on household electrical appliances can run well. All components of the design of the device are well integrated with smartphones and the internet. Control can be done anywhere and anytime. System response during the day between 1-4 seconds and at night between 1-2 seconds.
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