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Anik Vega Vitianingsih
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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. 5 No. 1 (2023): May 2023" : 5 Documents clear
The Analysis of Underwater Imagery System for Armor Unit Monitoring Application Sari, Dewi Mutiara; Marta, Bayu Sandi; Amin A, Muhammad; Dwito Armono, Haryo
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 5 No. 1 (2023): May 2023
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (527.168 KB) | DOI: 10.25139/ijair.v5i1.5918

Abstract

The placement of armor units for breakwaters in Indonesia is still done manually, which depends on divers in each placement of the armor unit. The use of divers is less effective due to limited communication between divers and excavator operators, making divers in the water take a long time. This makes the diver's job risky and expensive. This research presents a vision system to reduce the diver's role in adjusting the position of each armor unit. This vision system is built with two cameras connected to a mini-computer. This system has an image improvement process by comparing three methods. The results obtained are an average frame per second is 20.71 without applying the method, 0.45 fps for using the multi-scale retinex with color restoration method, 16.75 fps for applying the Contrast Limited Adaptive Histogram Equalization method, 16.17 fps for applying the Histogram Equalization method. The image quality evaluation uses the underwater color quality evaluation with 48 data points. The method that has experienced the most improvement in image quality is multi-scale retinex with color restoration. Forty data have improved image quality with an average of 14,131, or 83.33%. The number of images that experienced the highest image quality improvement was using the multi-scale retinex with color restoration method. Meanwhile, for image quality analysis based on Underwater Image Quality Measures, out of a total of 48 images, the method with the highest value for image quality is the contrast limited adaptive histogram equalization method. 100% of images have the highest image matrix value with an average value is 33.014.
Implementation of PSO algorithm on MPPT PV System using Arduino Uno under PSC Wirateruna, Efendi S; Afroni , Mohammad Jasa; Ayu, Annisa Fitri
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 5 No. 1 (2023): May 2023
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v5i1.6029

Abstract

The availability of fossil energy sources decreases as consumers' demand for electrical energy increases rapidly. Currently, the utilization of renewable energy sources is crucial. PV is a renewable energy source that converts photon energy into DC current. Maximum power point tracker (MPPT) control technology for photovoltaics has advanced significantly. PV is unique in that its P-V characteristic curve is non-linear. Conditions of partial shading can cause the P-V curve to have multiple peaks. This research will design MPPT PV using the Particle Swarm Optimization (PSO) algorithm in partially shaded conditions with an Arduino Uno and boost converter. Conventional algorithms, incremental conductance (IC), and Perturb and Observe (P&O) are implemented as a comparison. The purpose of implementing the PSO algorithm is to find the global peak of power to minimize power losses of PV. It leads to optimal power in case of partial shading conditions. Two PV modules are arranged in series for MPPT in a partially shaded environment. The examination was conducted in a darkened room with spotlights. The mean absolute percentage error of the current sensor, INA219, and the voltage sensor, voltage divider, was less than 1% during testing. The MPPT PV system test results indicate that the PSO algorithm can extract approximately 1.64 Watts of average power. In contrast, the IC and P&O algorithms can extract about 1.25 Watts and 1.41 Watts, respectively. When no algorithm exists in the control system, the extracted power is approximately 1.13 watts. Thus, the PSO algorithm tracks global or optimal power under partial shading conditions.
Utilizing Virtual Humans as Campus Virtual Receptionists Zikky, Moh.; Suhardiman, Marvel Natanael; Fathoni, Kholid
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 5 No. 1 (2023): May 2023
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v5i1.6175

Abstract

To imitate human-like behavior is one of the greatest feats a computer software could achieve. Computers can produce close-to-realism avatars with similar looks and behaviors in this modern era. One of the works that computer software could achieve now is conveying information in a place that a receptionist usually does. Therefore a computer software capable of that is called a Virtual Receptionist. This paper aims to explore the use of virtual humans as virtual receptionists and compare it to human receptionists to find both advantages and disadvantages. This research utilizes a virtual human model that imitates the behavior of a human receptionist. Its movements are based on real-life movements recorded with motion capture. It could also communicate with users by processing the voice input using speech-to-text technology recorded by a microphone. The recorded input will then be analyzed to determine whether it contains information stored in a database. The virtual human will then show the user the answer to their question accordingly. Utilizing virtual humans can make the process more interactive and exciting because of its futuristic feel. This way, campuses can have appealing introductory media and support campuses to be more open to the public in the future. However, the agent can only respond with prepared answers and not generate its own when necessary. Transcribed text will be analyzed for words that indicate the user's required information. In this case, the information would be the information of research laboratories in the post-graduate building of the EEPIS campus.
Classification Appropriateness Recipient Help Non-Cash Food Using Learning Vector Quantization (LVQ) Method Lestari, Ayu; Aris Widodo, Anang; Martyan Anggadimas, Nanda
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 5 No. 1 (2023): May 2023
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v5i1.6287

Abstract

Help Non-Cash Food is a program from the Government that is used to overcome poverty. The program is not functioning as well as it could because the procedure of receiving aid is not uniform, and individuals responsible for making choices are having trouble determining which families are qualified to receive the assistance. To overcome this problem, a classification system is needed to classify the eligibility of Non-Cash Food Assistance recipients so that the results are more efficient and accurate. This research uses the Learning Vector Quantization (LVQ) method with Python. This research aims to implement the LVQ method for the eligibility classification of non-cash food assistance recipients. System design is a stage that contains the process from start to finish of running this system which is described in the form of a flowchart, including system requirements that support this research, both software and hardware. In the process of analyzing the results and tests that are used as evaluation material in the process of finding a solution to a problem and making decisions in the process of planning activities, it is necessary to assess whether or not the LVQ approach is practicable to apply based on the findings of the research. In this study, 200 datasets were used with three epoch values and a learning rate of 0.1. The data set was randomly divided into a training portion of 80% and a testing portion of 20%. So that the results of this research using the LVQ method on the eligibility classification of recipients of Non-Cash Food Assistance obtain an accuracy of 97.5%.
Comparative Analysis of the Performance Testing Results of the Backtracking and Genetics Algorithm in Solving Sudoku Games Indriyono, Bonifacius; Pamungkas, Natalinda; Pratama, Zudha; Mintorini, Ery; Dimentieva, Imelda; Mellati, Pita
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 5 No. 1 (2023): May 2023
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v5i1.6501

Abstract

Games that hone thinking skills and logical accuracy have recently been very popular. One of them is the game Sudoku. Sudoku is a game that hones logic through puzzles arranged in rows and columns. Sudoku is also defined as a puzzle game that aims to arrange several numbers in a grid from one to nine on a grid consisting of 9x9 squares. The concept of this Sudoku game is to enter numbers into the rows and columns provided. The rule of this game is that the numbers arranged on the board cannot be the same in every row, column, and 3x3 square in the grid. In another sense, each number entered must appear once in each row and column. When running Sudoku, several numbers are already instructions for players to fill in the next boxes. The number of clues at the beginning of the game determines the difficulty level players face. The fewer clues, the more difficult the Sudoku is to solve. This study aims to compare how to solve Sudoku using genetic algorithms, backtracking, and the completion time needed. The tests' results show that the genetic and backtracking algorithms can solve Sudoku games quickly. Still, the backtracking algorithm has the advantage of being relatively shorter, and the process is not so complicated that the backtracking algorithm can be an alternative solution to solving Sudoku logic games.

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