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International Journal of Artificial Intelligence and Robotics (IJAIR)

ijair
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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 60 Documents

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An Efficient Technique for Automation of The NFT (Nutrient Film Technique) Hydroponic System Using Arduino Wibisono, Vicky; Kristyawan, Yudi
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 1 (2021): IJAIR : May
Publisher : Informatics Department-Universitas Dr. Soetomo

Hydroponic Nutrient Film Technique (NFT) is most widely applied on a home and industrial scale. One of the drawbacks of the NFT hydroponic system is that it is very dependent on electricity for 24 hours to power the water pump. The basic principle of the NFT hydroponic system is to flow nutrients to plant roots with a shallow and circulating nutrient layer so that plants get enough water, nutrients, and oxygen. Therefore, the role of the water pump in the hydroponic NFT system is crucial. This research makes the automation of the NFT hydroponic system more efficient using Arduino. There are two main parts to this automation system: the control of pH levels and nutrient distribution. The pH sensor is used to control the pH level of nutrients, and the ultrasonic sensor is used for nutrient distribution. Efficiency is emphasized more on the distribution of nutrients because it absorbs more electrical energy. The method used is to flow the nutrients in the reservoir to a storage tank that is located higher than the plant using a water pump with a large discharge. Nutrients are transported to each plant using the force of gravity. The nutrient volume is controlled automatically using an ultrasonic sensor in the storage tank. The water pump is only activated by the ultrasonic sensor readings on the storage tank. So that the need for electricity to turn on the water pump is reduced, based on tests carried out on the use of a 220-volt AC / 50 Hz / 125-watt water pump and the use of a 250-liter nutrient storage tank, it can be concluded that the system that has been created can save 70% of electricity consumption.

Design Of 4DOF 3D Robotic Arm to Separate the Objects Using a Camera Fahruzi, Akhmad; Agomo, Bimo Satyo; Prabowo, Yulianto Agung
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 1 (2021): IJAIR : May
Publisher : Informatics Department-Universitas Dr. Soetomo

Nowadays robotic arm is widely used in various industries, especially those engaged in manufacturing. Robotic arms are usually used to perform jobs such as picking up and moving goods from their place of origin to the location desired by the operator. In this study, a 3d 4 DOF (Degree of Freedom) robotic arm. The prototype was made to move goods with random coordinates to places or boxes whose coordinates were determined in advance. The robot can know the coordinates of the object to be taken or moved. The arm robot prototype design is completed with a camera connected to a computer, where the camera is installed statically (fixed position) above the robot's work area. The camera functions like image processing to detect the object's position by taking the coordinates of the object. Then the object coordinates will be input into inverse kinematics that will produce an angle in every point of the servo arm so that the position of the end effector on the robot arm can be founded and reach the intended object. From the results of testing and analysis, it was found that the error in the webcam test to detect object coordinates was 2.58%, the error in the servo motion test was 12.68%, and the error in the inverse kinematics test was 7.85% on the x-axis, the error was 6.31% on the y-axis and an error of 12.77% on the z-axis. The reliability of the whole system is 66.66%.

Bezier Curve Collision-Free Route Planning Using Meta-Heuristic Optimization Machmudah, Affiani; Parman, Setyamartana
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 1 (2021): IJAIR : May
Publisher : Informatics Department-Universitas Dr. Soetomo

A collision-free route is very important for achieving sustainability in a manufacturing process and vehicle robot trajectories that commonly operate in a hazardous environment surrounded by obstacles. This paper presents a collision avoidance algorithm using a Bezier curve as a route path. The route planning is modeled as an optimization problem with the objective optimization is to minimize the route length considering an avoiding collision constraint. The collision-avoidance algorithm based on curve point analysis is developed incorporating metaheuristic optimizations, namely a Genetic Algorithm (GA) and a Grey Wolf Optimizer (GWO). In the collision avoidance algorithm, checking of curve point's position is important to evaluate the individual fitness value. The curve points are analyzed in such a way so that only the paths which are outside the obstacle area are selected. In this case, besides the minimum length as a fitness function, the constraint is the position of curve points from an obstacle. With the help of meta-heuristic optimization, the developed collision avoidance algorithm has been applied successfully to different types of obstacle geometries. The optimization problem is converted to the maximization problem so that the highest fitness value is used to measure the performance of the GA and GWO. In general, results show that the GWO outperforms the GA, where it exhibits the highest fitness value. However, the GA has shown better performance for the narrow passage problem than that of the GWO. Thus, for future research, implementing the hybrid technique combining the GA and the GWO to solve the advanced path planning is essential.

Optimization Design of Coal Dryer Using Genetic Algorithm in Power Plant Luluk Karlina, Diyajeng; Bintang, Ilham
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 1 (2021): IJAIR : May
Publisher : Informatics Department-Universitas Dr. Soetomo

Coal that is often used in Steam Power Plants is a type of Low Rank Coal (Low Rank Coal) which has a caloric value of 4200 kcal / kg with a moisture content of 40%. Coal with water content that reaches 40% can cause the efficiency process of the plant to be not optimal. Low efficiency values will cause the use of electricity to increase and the combustion process to be incomplete so that it can cause many losses to the Steam Power Plant. From this problem, there needs to be a process of drying coal in order to reduce water content, the technology used in the process of drying coal is coal dryer. Design of coal dryer required source of steam or heat for drying process. Steam Power Plant there is steam waste extraction from turbines that can be used as a heat source to heat coal. If this extraction vapor is utilized, it can reduce the load from the condenser. The amount of turbine extraction steam that can be received by the coal dryer depends on the design of the coal dryer, because the design process of the coal dryer will affect the availability of energy in the coal dryer. This paper will discuss about optimization calculation with genetic algorithm method, to obtain the best design of coal dryer so that the heat received can be maximized so that the drying process becomes faster.

Emotion Detection in Twitter Social Media Using Long Short-Term Memory (LSTM) and Fast Text Riza, M Alfa; Charibaldi, Novrido
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 1 (2021): IJAIR : May
Publisher : Informatics Department-Universitas Dr. Soetomo

Emotion detection is important in various fields such as education, business, employee recruitment. In this study, emotions will be detected with text that comes from Twitter because social media makes users tend to express emotions through text posts. One of the social media that has the highest user growth rate in Indonesia is Twitter. This study will use the LSTM method because this method is proven to be better than previous studies. Word embedding fast text will also be used in this study to improve Word2Vec and GloVe that cannot handle the problem of out of vocabulary (OOV). This research produces the best accuracy for each word embedding as follows, Word2Vec produces an accuracy of 73,15%, GloVe produces an accuracy of 60,10%, fast text produces an accuracy of 73,15%. The conclusion in this study is the best accuracy was obtained by Word2Vec and fast text. The fast text has the advantage of handling the problem of out of vocabulary (OOV), but in this study, it cannot improve the accuracy of word 2vec. This study has not been able to produce very good accuracy. This is because of the data used. In future works, to get even better results, it is expected to apply other deep learning methods, such as CNN, BiLSTM, etc. It is hoped that more data will be used in future studies.

Recognition of Korean Alphabet (Hangul) Handwriting into Latin Characters Using Backpropagation Method Widodo, Anang Aris; Izza Mahendra, Muchammad Yuska; Zoqi Sarwani, Mohammad
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 2 (2021): IJAIR : November
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v3i2.4210

The popularity of Korean culture today attracts many people to learn everything about Korea, especially in learning the Korean language. To learn Korean, you must first know Korean letters (Hangul), which are non-Latin characters. Therefore, a digital approach is needed to recognize handwritten Korean (Hangul) words easily. Handwritten character recognition has a vital role in pattern recognition and image processing for handwritten Character Recognition (HCR). The backpropagation method trains the network to balance the network's ability to recognize the patterns used during training and the network's ability to respond correctly to input patterns that are similar but not the same as the patterns used during training. This principle is used for character recognition of Korean characters (Hangul), a sub-topic in fairly complex pattern recognition. The results of the calculation of the backpropagation artificial neural network with MATLAB in this study have succeeded in identifying 576 image training data and 384 Korean letter testing data (Hangul) quite well and obtaining a percentage result of 80.83% with an accuracy rate of all data testing carried out on letters. Korean (Hangul).

Optimization of Breadth-First Search Algorithm for Path Solutions in Mazyin Games Indriyono, Bonifacius Vicky; Widyatmoko, Widyatmoko
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 2 (2021): IJAIR : November
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v3i2.4256

A game containing elements of artificial intelligence, of course, requires an algorithm in its application. One example of a game that includes elements of artificial intelligence is the Labyrinth game. Maze is a simple educational game. This game is known as finding a way out of the maze to arrive at a predetermined goal. The labyrinth encounters numerous obstacles along the way, such as dead ends and parapets, to reach the target location. In this game, players are required to think logically about how to find the right maze path. The obstacle faced in this game is that sometimes players have difficulty finding a way out, especially if the game level has reached a high level in the process of finding a way out. To solve this problem, a graph tracing technique is needed. The Breadth-First Search (BFS) strategy can be used in conjunction with various graph search algorithms. An example of a broad search method is the Breadth-First Search Algorithm, which works by visiting nodes at level n first before moving on to nodes at level n+1. The advantage of the Breadth-First Search algorithm is that it can find a solution as the shortest path and find the minimum solution if there is more than one solution. This study will discuss how to find a path for the Labyrinth using the BFS algorithm. The result of applying this BFS algorithm is the shortest route solution raised so that the Labyrinth can arrive at the destination point through the route provided.

Improvement Of Query Speaking on The Indonesian to Madura Dictionary Using Levenshtein Distance Method Ubaidillah, M. Yahya; Kurniawan, Muchamad; Rosetya Wardhana, Septiyawan
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 2 (2021): IJAIR : November
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v3i2.4258

Men are distinguished from other living beings by their use of language, which becomes one of their most distinctive and humanistic qualities. Many different languages are spoken worldwide, including Indonesian, which has approximately 742 different dialects. Due to the unique language of Madura, which is located on a large island with numerous beach tourism destinations, tourists will have difficulty navigating the island. People outside Madura Island who come to visit or vacation will find it difficult to communicate with the locals during their stay or holiday. An Indonesian to Madurese translation dictionary is therefore required in this case. The Levenshtein Distance method was employed in this investigation. The algorithm in the dictionary is used to process the search for the closest distance (dif) between the words being inputted and the words that are already in the database. To provide a prototype for the use of dictionaries. Indonesian and Madurese data sets were used in the investigation by the researcher. According to the simulation results acquired after multiple trials, the error accuracy was 90 % for the first letter input, 84 % for the middle letter input, and 84 % for the last letter input for the first letter. As a result, according to the study's findings, the accuracy of this dictionary increased by 86 %. The first letter received 90 % of the votes, the middle letter received 84 %, and the last letter received 84 %. As a result, according to the study's findings, the accuracy of this dictionary increased by 86 %. The first letter received 90 % of the votes, the middle letter received 84 %, and the last letter received 84 %. As a result, according to the study's findings, the accuracy of this dictionary increased by 86 %.

Automation System for the Disposal of Feces and Urine in Rabbit Cages Using Arduino Kristyawan, Yudi; Yikwa, Atinus
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 2 (2021): IJAIR : November
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v3i2.4277

Farming rabbits in large numbers produce large amounts of feces and urine. A cage full of feces and urine can cause health problems for rabbits. This research aims to produce an automation system for the disposal of feces and urine in rabbit cages using an Arduino board and implemented in a prototype form. This system uses electronic devices including load cells, HX711 Module to make it easier to read load cells in measuring weight, real-time clock (RTC) for timing, ultrasonic sensor HC-SR04 to detect the presence of a certain object, dc motor, L298N motor driver module to control a dc motor, an LCD 16x2 module to display the weight and height of feces and urine, a buzzer as a notification of the status of the container if it is full, and an Arduino Uno as a controller of the entire system. The system operates so that the feces excreted by the rabbit fall onto the conveyor belt. At the same time, the urine passes via the conveyor belt and falls into the cross-section before being pumped into the urine collection container. The feces on the conveyor belt will be moved with a dc motor towards the stool container based on a certain time. Each stool and urine container is weighed with a load cell and ultrasonic sensor to detect when the container is full. Then the condition of the load cell and the ultrasonic sensor is displayed on an LCD 16x2. When one or both containers are full, a buzzer will sound as a notification. The method used in this research is an experimental method by manipulating or controlling natural situations into artificial conditions. The artificial condition is the provision of deliberate control over the object of study. The test results show that this system can remove waste based on the time using a belt conveyor and monitoring the weight and height of the dirt. If the dirt has met the specified limit, the system can activate an alarm as a notification.

Convolutional Neural Network Method for Classification of Syllables in Javanese Script Fauziah, Yuli; Aprilianta, Kevin; Heru Cahya Rustamaji
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 3 No. 2 (2021): IJAIR : November
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v3i2.4332

Javanese script is one of the languages which are a typical Javanese culture. Javanese script is seen in its use in writing the name of a particular agency or location that has historical and tourism value. The use of Javanese script in public places makes the existence of this script seen by many people, not only by the Javanese people. Some of them have difficulty recognizing the Javanese characters they encounter. One method of pattern recognition and image processing is Convolutional Neural Network (CNN). CNN is a method that uses convolution operations in performing feature extraction on images as a basis for classification. The process consists of initial data processing, classification, and syllable formation. The classification consists of 48 classes covering Javanese script types, namely basic letters (Carakan) and voice-modifying scripts (Sandhangan). It is tested with multi-class confusion matrix scenarios to determine the accuracy, precision, and recall of the built CNN model. The CNN architecture consists of three convolution layers with max-pooling operations. The training configuration includes a learning rate of 0.0001, and the number of filters for each convolution layer is 32, 64, and 128 filters. The dropout value used is 0.5, and the number of neurons in the fully-connected layer is 1,024 neurons. The average performance value of accuracy reached 87.65%, the average precision value was 88.01%, and the average recall value was 87.70%.

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

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

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

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