cover
Contact Name
Anik Vega Vitianingsih
Contact Email
vega@unitomo.ac.id
Phone
+6281332765765
Journal Mail Official
ijair@unitomo.ac.id
Editorial Address
Jl. Semolowaru no 84, Surabaya, 60118
Location
Kota surabaya,
Jawa timur
INDONESIA
International Journal of Artificial Intelligence and Robotics (IJAIR)
ISSN : -     EISSN : 26866269     DOI : 10.25139
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.
Articles 60 Documents
Comparison of Clustering K-Means, Fuzzy C-Means, and Linkage for Nasa Active Fire Dataset 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 (2292.074 KB) | DOI: 10.25139/ijair.v2i2.3030

Abstract

One of the causes of forest fires is the lack of speed of handling when a fire occurs. This can be anticipated by determining how many extinguishing units are in the center of the hot spot. To get hotspots, NASA has provided an active fire dataset. The clustering method is used to get the most optimal centroid point. The clustering methods we use are K-Means, Fuzzy C-Means (FCM), and Average Linkage. The reason for using K-means is a simple method and has been applied in various areas. FCM is a partition-based clustering algorithm which is a development of the K-means method. The hierarchical based clustering method is represented by the Average Linkage method.  The measurement technique that uses is the sum of the internal distance of each cluster. Elbow evaluation is used to evaluate the optimal cluster. The results obtained after conducting the K-Means trial obtained the best results with a total distance of 145.35 km, and the best clusters from this method were 4 clusters. Meanwhile, the total distance values obtained from the FCM and Linkage methods were 154.13 km and 266.61 km.
The prototype of A Forklift Robot Based on AGV System and Android Wireless Controlled for Stacked Shelves 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 (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.
Genetic Algorithm for Optimizing Traveling Salesman Problems with Time Windows (TSP-TW) 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 (570.738 KB) | DOI: 10.25139/ijair.v1i1.2024

Abstract

The concept of Traveling Salesman Problem (TSP) used in the discussion of this paper is the Traveling Salesman Problem with Time Windows (TSP-TW), where the time variable considered is the time of availability of attractions for tourists to visit. The algorithm used for optimizing the solution of Traveling Salesman Problem with Time Windows (TSP-TW) is a genetic algorithm. The search for a solution for determining the best route begins with the formation of an initial population that contains a collection of individuals. Each individual has a combination of different tourist sequence. Then it is processed by genetic operators, namely crossover with Partially Mapped Crossover (PMX) method, mutation using reciprocal exchange method, and selection using ranked-based fitness method. The research method used is GRAPPLE. Based on tests conducted, the optimal generation size results obtained in solving the TSP-TW problem on the tourist route in the Province of DIY using genetic algorithms is 700, population size is 40, and the combination of crossover rate and mutation rate is 0.70 and 0.30 There is a tolerance time of 5 seconds between the process of requesting distance and travel time and the process of forming a tourist route for the genetic algorithm process.
Automatic Garden Umbrella Prototype with Light and Rain Sensor Based on Arduino Uno Microcontroller 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 (2810.471 KB) | DOI: 10.25139/ijair.v2i2.3152

Abstract

Park is a green open space widely used by the community to carry out various activities ranging from recreation, playing, sports, and other passive activities. Current weather conditions are often uncertain. This makes people inconvenient when it rains suddenly, especially when outdoors such as in parks. Because if they don't immediately take shelter when it rains, it can make the body sick, besides that, rainwater can damage the non-waterproof gadgets they carry. In other conditions, when the weather is bright, and the sun is shining hot, it can make people feel hot and lazy to do outdoor activities in the park. Therefore, an automatic umbrella tool was made that functions as a shelter in the garden. In this tool, there is a light sensor module and also a rain sensor, which is controlled with the Arduino Uno microcontroller as an input data processor and an L298N motor driver, which functions to regulate the speed and direction of the DC motor rotation (to the right and left) as an umbrella drive. When the motor rotates to the right, the umbrella will open, while when the motor rotates to the left, the umbrella will close again.
An Automatic Sliding Doors Using RFID and Arduino 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 (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.
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%.
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.
A LOF K-Means Clustering on Hotspot Data 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 (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. 
Indonesian Sign Language API (OpenSIBI API) as The Gateway Services for Myo Armband 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 (757.419 KB) | DOI: 10.25139/ijair.v1i1.2026

Abstract

We create an API (Application Programming Interface) for Indonesian Sign Language (Sistem Isyarat Bahasa Indonesia/SIBI) which is called OpenSIBI. In this case study, we use the Myo Armband device to capture hand gesture data movement. It uses five sensors: Accelerometer, Gyroscope, Orientation, Orientation-Euler, and EMG. First, we record, convert and save those data into JSON dataset in the server as data learning. Then, every data request (trial data) from the client will compare them using k-NN Normalization process. OpenSIBI API works as the middleware which integrated to RabbitMQ as the queue request arranger. Every service request from the client will automatically spread to the server with the queue process. As the media observation, we create a client data request by SIBI Words and Alphabeth Game, which allows the user to answer several stages of puzzle-game with Indonesian Sign Language hand gesture. Game-player must use the Myo armband as an interactive device that reads the hand movement and its fingers for answering the questions given. Thus, the data will be classified and normalized by the k-NN algorithm, which will be processed on the server. In this process, data will pass OpenAPI SIBI (which connected to RabbitMQ) to queue every incoming data-request. So, the obtained data will be processed one by one and sent it back to the client as the answer.
Message Security Using Rivest-Shamir-Adleman Cryptography and Least Significant Bit Steganography with Video Platform 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 (2176.307 KB) | DOI: 10.25139/ijair.v2i2.3150

Abstract

All over the world, information technology has developed into a critical communication medium. One of them is digital messaging. We can connect and share information in real-time using digital messages. Without us knowing it, advances in message delivery are not only followed by kindness. Message security threats are also growing. Many unauthorized parties try to intercept critical information sent for the benefit of certain parties. As a countermeasure, various message security techniques exist to protect the messages we send. One of them is cryptography and steganography. Cryptography is useful for converting our messages into coded text so that unauthorized parties cannot read them. Meanwhile, steganography is useful for hiding our encrypted messages into several media, such as videos. This research will convert messages into ciphertext using the Rivest-Shamir-Adleman method and then insert them into video media using the Least Significant Bit method. There are four types of messages tested with different sizes. All messages will be encrypted and embedding using the Python programming language. Then the video will be tested using the MSE, PSNR, and Histogram methods. So we get a value that shows which message gets the best results. So that the message sent is more guaranteed authenticity and reduces the possibility of message leakage.