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International Journal of Artificial Intelligence
Published by Lamintang Education & Training Centre
ISSN : 24077275     EISSN : 26863251     DOI : https://doi.org/10.36079/lamintang.ijai
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
The aim is to publish high-quality articles dedicated to Artificial Intelligence. IJAI published in biannual, and in Indonesian, Malay and English.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol 10 No 2: December 2023" : 5 Documents clear
Cardiovascular Disease Prediction Using Machine Learning Agrawal, Atharva Mangeshkumar
International Journal of Artificial Intelligence Vol 10 No 2: December 2023
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-01002.542

Abstract

Heart disease-related deaths have become a big issue in today's world, with one person dying from the disease every minute. It considers both male and female groups, and the ratio varies by location. It is also used for the 25-69 age group. This isn't to say that people of all ages will be affected by heart disease. This condition could start in the early stages of life, and predicting the source and sickness is currently a huge challenge. Heart disease is one of the world's most fatal problems, one that cannot be seen with the naked eye and manifests itself as soon as it reaches its limits. As a result, precise diagnosis at the right moment is necessary. Every day, the health-care business generates massive amounts of patient and illness-related data. Researchers and practitioners, on the other hand, do not make appropriate use of this data. Despite its lack of knowledge, the healthcare business now has a wealth of data. In data mining and machine learning, there are a variety of approaches and tools for extracting usable information from databases and using that information to make more accurate diagnoses and decisions. So, in order to detect such disorders in time for adequate treatment, a reliable, precise, and feasible approach is required. In the realm of medicine, machine learning algorithms and approaches have been used to process enormous data sets. Researchers employ a variety of data mining and machine learning approaches to analyse large data sets and aid in the accurate prediction of cardiac illnesses. This research compares and contrasts the Nave Bayes, Help Vector Machine, Random Forest, and supervised learning models to find the most successful algorithm. When compared to other algorithms, Random Forest has95.08 per cent more precision.
Mobile Disinfectant Spraying Robot and its Implementation Components for Virus Outbreak: Case Study of COVID-19 Udoka, Eze Val Hyginus; Edozie, Enerst; Davis, Musika; Dickens, Twijuke; Janat, Wantimba; Wisdom, Okafor; Umaru, Kalyankolo; Nafuna, Ritah; Yudaya, Nansukusa
International Journal of Artificial Intelligence Vol 10 No 2: December 2023
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-01002.551

Abstract

The virus pandemic COVID-19 outbreak brought a huge pressure to the public healthcare system worldwide, especially in developing African countries like Uganda. The Educational system and institutions were put on a standstill due to no quick countermeasures to make the environment clean and safe for normal activities to continue. This paper successfully and comprehensively reviewed the Bluetooth and smart disinfectant spraying robot that successfully controlled the spread of the deadly virus. It also detailed different components that made up the complete spraying robot systems and from this it was observed that spraying robot systems are made up of almost the same components for implementations but differs on program that is embedded on the microcontroller due to different functions. This programing differs based on the functions that the designer/programmer wants the robot to do despite using almost the same components. This research review paper will act as guide for future researchers when designing and implementing a mobile spraying robot.
Point of Sale System Using Convolutional Neural Network for Image Recognition in Grocery Store Roslan, Naim Najmi; Saad, Ahmad Fadli
International Journal of Artificial Intelligence Vol 10 No 2: December 2023
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-01002.553

Abstract

The history of point of sale already has been told from a long time ago. The business nowadays is opting for the point-of-sale transactions because it was easy to sell the item to people face to face. This will build some trust between the cashier and the customer. The popular store that always customer need was the grocery store. However, the grocery store nowadays still not has a good feature for the point-of-sale system. The cashier still needs to scan the item through barcode scanner. This idea was led to make the point-of-sale transactions easier in the grocery store by applying the machine learning to the system. The problem for this project is the customer wait for a long time for their point-of-sale transactions to finish when bought the grocery items. The aim of this project is to detect the grocery items with convolutional neural network model for image recognition through camera within the main user interface. The Agile Development Life Cycle (ADLC) method is used in the development of Point-of-Sale System using Machine Learning for Image Recognition in Grocery Store. Moreover, this project is to evaluate the usability of the system using Post-Study System Usability Questionnaire (PSSUQ) approach. The PSSUQ evaluation is evaluated by the users of the system. The results of PSSUQ stated that the users satisfied with the system. The future research for this project is to make the point-of-sale system with a better model in the future. In conclusion, the system is works well and machine learning image recognition model also can detect the grocery item clearly.
A Deep Reinforcement Learning Agent for Snake Game Hossain, Md Meem; Fakokunde, Akinwumi; Olaolu, Omololu Isaac
International Journal of Artificial Intelligence Vol 10 No 2: December 2023
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-01002.565

Abstract

After watching AlphaGo a Netflix documentary which presents how AlphaGo is an AI computer game developed by deep-mind technologies based on deep reinforcement learning (DRL). Since then, my interest in reinforcement learning has been growing. In this project, I will apply reinforcement learning to develop an agent to play snake game. Where Deep learning will implement a neural Network to help the agent (snake) to learn what action must take to get a state. If we describe deep reinforcement learning (DRL) model where agent interacts with an environment and chooses an action. Based on action, agents receive feedback from the environment as states (or perceives) and rewards. A state = an array with 11 input values, each input values represent a neural network that provides an output of 3 values, each one represents three possible actions the agent (snake) can take (Straight, Right Turn and Left Turn).
A Review of Cross-Platform Document File Reader Using Speech Synthesis Chukwudi, Ogenyi Fabian; Eze, Val Hyginus Udoka; Chinyere, Ugwu
International Journal of Artificial Intelligence Vol 10 No 2: December 2023
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-01002.569

Abstract

Document files are files used to store documents on storage devices primarily for computer use. Software is used to view these files, displaying their text content in a legible way. However, it is essential to have programs for transforming electronic files into versions usable by those who suffer from specific disabilities. This paper reviewed fifteen published articles in the field of document file reading. It was observed from the review that various attempts have been made by different researchers in order to develop a software cable for converting document files that consist of text to an audio format. Text may now be easily translated into natural-sounding voice across many platforms using different software. It was observed from the systematic review that the use of AI such as the GPT-3.5 and GPT-4 Turbo Large Language Model (LLM) technologies has the best performance because it does not end at producing a vocal sound that is similar to human own, but it also translates different languages. In conclusion, cross-platform document file reader (text-to-speech) synthesis has improved user experiences in a variety of applications such as language learning, audiobooks and virtual assistants.

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