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International Journal of Artificial Intelligence and Robotics (IJAIR)
Published by Universitas Dr. Soetomo Surabaya
ISSN : -     EISSN : 26866269     DOI : 10.25139
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
International Journal of Artificial Intelligence & Robotics (IJAIR) is One of the journals published by Informatics Department, Universitas Dr Soetomo, was established in November 2019. IJAIR a double-blind peer-reviewed journal, the aim of this journal is to publish high-quality articles dedicated to the field of information and communication technology, Published 2 times a year in November and May. Focus and Scope: Machine Learning & Soft Computing, Data Mining & Big Data, Computer Vision & Pattern Recognition dan Robotics.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
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Search results for , issue "Vol. 2 No. 1 (2020): IJAIR : May" : 5 Documents clear
The prototype of A Forklift Robot Based on AGV System and Android Wireless Controlled for Stacked Shelves Suryowinoto, Andy; Wijayanto, Martian
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 1 (2020): IJAIR : May
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (195.922 KB) | DOI: 10.25139/ijair.v2i1.2621

Abstract

The paper aims to build a prototype of an automatic forklift robot that can collect and place goods in the stacking shelves, that are monitored remotely using an Android-based device. The method used is AGV (Automated Guided Vehicle) on this forklift robot prototype to adjust its positions, by following a line that preset trajectory for stacking shelf positions, where this forklift robot can collect and place goods.  The robot navigation system uses a photodiode for the line follower system, and for storage of goods, it uses the proximity sensors detecting the presence of goods on miniature stacking goods and decide where it can store a good or not on that designated cell of the stacking shelf. The miniature of stacking shelves is two by three cells. The control of the robot has two input controllers. One is on a robot itself. The other was on handheld based on Android operating systems, which control remotely using the wireless system with Bluetooth protocol. The results of the discussion on paper, the forklift robot could manage the task given as the predefined line to a followed parameter of stacking shelves with two by three-stack configuration for collect and place goods into their positions, the average time for the robot to collecting and placing goods on stacking from standing still position to stacking shelf then back to the robot origin position. It resulted in the shortest processing time around 43 seconds and the longest time around 45,3 seconds from the start position to stacking shelf position.
A LOF K-Means Clustering on Hotspot Data Muhima, Rani Rotul; Kurniawan, Muchamad; Pambudi, Oktavian Tegar
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 1 (2020): IJAIR : May
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (556.964 KB) | DOI: 10.25139/ijair.v2i1.2634

Abstract

K-Means is the most popular of clustering method, but its drawback is sensitivity to outliers. This paper discusses the addition of the outlier removal method to the K-Means method to improve the performance of clustering. The outlier removal method was added to the Local Outlier Factor (LOF). LOF is the representative outlier’s detection algorithm based on density. In this research, the method is called LOF K-Means. The first applying clustering by using the K-Means method on hotspot data and then finding outliers using the LOF method.  The object detected outliers are then removed.  Then new centroid for each group is obtained using the K-Means method again. This dataset was taken from the FIRM are provided by the National Aeronautics and Space Administration (NASA).  Clustering was done by varying the number of clusters (k = 10, 15, 20, 25, 30, 35, 40, 45 and 50) with cluster optimal is k = 20. The result based on the value of Sum of Squared Error (SSE) shown the LOF K-Means method was better than the K-Means method. 
Knowing Personality Traits on Facebook Status Using the Naïve Bayes Classifier Sarwani, Mohammad Zoqi; Salafudin, Muhammad Shubkhan; Sani, Dian Ahkam
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 1 (2020): IJAIR : May
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 Sani, Dian Ahkam; Sarwani, Mohammad Zoqi; Setiawan, Muhamad Agus
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 1 (2020): IJAIR : May
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.
An Automatic Sliding Doors Using RFID and Arduino Kristyawan, Yudi; Rizhaldi, Achmad Dicky
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 1 (2020): IJAIR : May
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3232.856 KB) | DOI: 10.25139/ijair.v2i1.2706

Abstract

 The door is an important component in a building as security. It is used as access in and out of a room. People in the modern era now want everyday life that is completely automated, so that the work can be done easily without wasting energy and can shorten the time. Along with the rapid development, the need for effectiveness and efficiency is prioritized in various fields. The purpose of this paper is to design an automatic sliding door that only detects one Radio Frequency Identification (RFID) card to open and close. The use of RFID systems can strengthen the security level of building access. This study uses a data processing method in the form of an ID number generated from a tag. Specifications in the discussion of the results in this study include a motor that uses a 12-volt DC motor, a maximum door weight of 5 kg, can only detect one RFID to open and close the door, and the sliding door used is one door. The results of system testing are obtained to open a door that is without load, and the door can move 14 cm from the distance of the door hole so that it opens. Doors with a load of 1-1.5 kg also move 14 cm from the distance of the door opening when open. Doors with a load of 2-3 kg only move 12.5-9.5 cm from the distance of the door so that it opens. When the door gets heavier 3.5-4 kg, the door moves only 7.5-3 cm from the distance the door hole remains closed.

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