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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 8 No 2: December 2021" : 5 Documents clear
Early Detection of Alzheimer’s Disease using Convolutional Neural Network Architecture Deepthi Kamath; Misba Firdose Fathima; Monica K. P; Kusuma Mohanchandra
International Journal of Artificial Intelligence Vol 8 No 2: December 2021
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-0802.232

Abstract

Alzheimer's disease is an extremely popular cause of dementia which leads to memory loss, problem-solving and other thinking abilities that are severe enough to interfere with daily life. Detection of Alzheimer’s at a prior stage is crucial as it can prevent significant damage to the patient’s brain. In this paper, a method to detect Alzheimer’s Disease from Brain MRI images is proposed. The proposed approach extracts shape features and texture of the Hippocampus region from the MRI scans and a Neural Network is used as a Multi-Class Classifier for detection of AD. The proposed approach is implemented and it gives better accuracy as compared to conventional approaches. In this paper, Convolutional Neural Network is the Neural Network approach used for the detection of AD at a prodromal stage.
Mr. Dr. Health-Assistant Chatbot Md Meem Hossain; Salini Krishna Pillai; Sholestica Elmie Dansy; Aldrin Aran Bilong; Ismail Yusuf Panessai
International Journal of Artificial Intelligence Vol 8 No 2: December 2021
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-0802.301

Abstract

Research says 60% of visits to a doctor are for simple small-scale diseases, 80% of which can be diagnosed at home using simple check-up. These diseases mostly include common cold and cough, headache, abdominal pains etc. Whereas, chat-bots in healthcare are highly in demand, which functioning can offer various services from symptom checking and appointment scheduling. Therefore, the purpose of the research aims to design, develop and evaluate a health-assistant Chat-bot Application entitled “MR.Dr.” that helps users to ask any personal query related to healthcare without physically available to the hospital. MR.Dr. is evaluated in term of usability. 30 respondents attended the survey of usability evaluation. In the system usability scale MR.Dr. achieved 87.6 % rating which means Grade A (excellent). User's feedback level was pretty satisfying where 24/7 service is the highest one.
A Genetic-Fuzzy System Algorithm Method for the Breast Cancer Diagnosis Problem Normalisa
International Journal of Artificial Intelligence Vol 8 No 2: December 2021
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-0802.302

Abstract

Breast cancer is an important medical problem, especially for women, computer-aided medical diagnosis is very important in terms of prevention and early detection. This paper presents early detection of breast cancer using two methods, namely genetic algorithm and fuzzy inference system which will be used for early detection of breast cancer which will be used by doctors with computer assistance to obtain medical diagnosis of breast cancer in Indonesia. Our research shows that the diagnosis of breast cancer using these two methods has a high level of accuracy.
WeRoute: Route Optimization Web-Based System and Driver Mobile Application Ang Pei Ying; Justtina Anantha Jothi; Nursakirah ARM
International Journal of Artificial Intelligence Vol 8 No 2: December 2021
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-0802.314

Abstract

This paper intends to conceptualise an optimisation solution for vehicle routing that can get the best routing result and release the most optimal route to the driver, namely WeRoute. The objectives of the paper are to manage the data efficiently, save time, reduce cost, enhance customer satisfaction, and decrease the emission of carbon. Moreover, this is also known as the vehicle routing problem, which deals with a range of variables, including drivers, stops, roads, and customers. The method, Genetic algorithm, was developed to improve the efficiency of generating feasible routes for a project. A team of drivers and several stops are needed to generate the solution of optimising the vehicle routing. It can be said that the more drivers or stops, the more complicated the problem becomes, such as cost controls and vehicle limitations. Thus, a route optimisation tool slowly becomes the key to ensuring the delivery business as efficiently as possible.
Development of Attendance Monitoring System with Artificial Intelligence Optimization in Cloud Mohamad Fakir Naen; Muhamad Hariz Muhamad Adnan; Nurul Adilah Yazi; Chee Ken Nee
International Journal of Artificial Intelligence Vol 8 No 2: December 2021
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-0802.315

Abstract

The creation of an attendance management system based on biometrics is proposed in this research. Keeping track of student attendance during lecture periods has proven to be a difficult task. Because human calculating creates errors and wastes a lot of time, the capacity to compute the attendance percentage becomes a key challenge. For this reason, a biometric-based attendance management system is being developed. This system uses a fingerprint device to take attendance electronically, and the attendance records are kept in a database. Following student identification, attendance is recorded. Artificial intelligence is also proposed as a component of the system. The system will aid in the reduction of errors and the more effective compilation of attendance data.

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