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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. 2 (2020): IJAIR : November" : 5 Documents clear
Comparison of Clustering K-Means, Fuzzy C-Means, and Linkage for Nasa Active Fire Dataset Kurniawan, Muchamad; Muhima, Rani Rotul; Agustini, Siti
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 2 (2020): IJAIR : November
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.
Switching Systems Designing Based on IoT Sani, Dian Ahkam; Fijriyah, Immilda Lailatul
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 2 (2020): IJAIR : November
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.
Message Security Using Rivest-Shamir-Adleman Cryptography and Least Significant Bit Steganography with Video Platform Muhammad, Widad; Sulaksono, Danang Haryo; Agustini, Siti
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 2 (2020): IJAIR : November
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.
Automatic Garden Umbrella Prototype with Light and Rain Sensor Based on Arduino Uno Microcontroller Chandra, Yudi Irawan; Riastuti, Marti; Kosdiana, Kosdiana; Nugroho, Edo Prasetiyo
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 2 (2020): IJAIR : November
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.
Traffic Light Automation with Camera Tracker and Microphone to Recognize Ambulance Using the HAAR Cascade Classifier Method Putra, Eldha Nur Ramadhana; Prihartono, Edi; Santoso, Budi
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 2 No. 2 (2020): IJAIR : November
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2519.988 KB) | DOI: 10.25139/ijair.v2i2.3194

Abstract

Lack of knowledge by road users regarding these priorities, especially when there is a passing ambulance that is often stuck in traffic at a crossroads due to accumulated vehicles and the traffic light is still red. The purpose of this paper is to simulate traffic light automation by giving a green light every time an ambulance passes by using the HAAR and Computer Vision methods. The HAAR method is used for training data from less sharp images as part of the Ambulance object classification process. The Computer Vision method is used as a tool in image processing objects to processing the image captured by the Camera. Hardware through the microphone performs pattern recognition to pick up ambulance sirens. The test result at the average frequency caught by the microphone is 1.3 kHz. The test results of the System to capture ambulance objects received a precision value of 75%, a recall of 100%, and an accuracy of 75%.

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