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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 59 Documents
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Mr. Dr. Health-Assistant Chatbot Hossain, Md Meem; Krishna Pillai, Salini; Dansy, Sholestica Elmie; Bilong, Aldrin Aran; Panessai, Ismail Yusuf
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 Ying, Ang Pei; Jothi, Justtina Anantha; ARM, Nursakirah
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 Naen, Mohamad Fakir; Muhamad Adnan, Muhamad Hariz; Yazi, Nurul Adilah; Nee, Chee Ken
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.
The Different Techniques for Detection of Plant Leaves Diseases Kumar, Akshay; Singh, Ranvijay; Shashidhara; Neha; Thirukrishna
International Journal of Artificial Intelligence Vol 9 No 1: June 2022
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-0901.342

Abstract

As we know that Plant disease detection is an interesting field. Plants are the way to live. In our daily life we are completely dependent on plants. There by plants should be taken care. In most of the studies it is been shown that quality of agricultural products shall be reduced due to various components. The plant diseases are such as bacteria, viruses and fungi. The disease in plant leaf restricts the growth of the plant and also destroys its yield. Every time there is the need of expert to identify plant diseases but manual identification is expensive and also time consuming. So, automatic methods are necessary for detection of disease. Through this paper, we have presented a survey on the different methods of plant leaf disease detection.
Bayesian Network Approach in Educational Application Development: A Systematic Literature Review and Bibliometric Meta-Analysis Chanthiran, Maran; Ibrahim, Abu Bakar; Abdul Rahman, Mohd Hishamuddin; Mariappan , Punithavili
International Journal of Artificial Intelligence Vol 9 No 1: June 2022
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-0901.348

Abstract

Technological developments have brought about a paradigm shift in the world of education. The education system must be more open and flexible, where students can experience these opportunities according to their skill level. 21st-century education and the application of the elements of Revolution 4.0 Industry in education realize that initiative. The Bayesian Network approach is becoming one of the essential tools in the development of educational applications. Therefore, the persistence of this systematic review is to identify peer-reviewed literature on the Bayesian network approach in education. Scopus and Web of Science, and IEEE citation databases are used in the data-gathering phase. PRISMA approach and keyword search were obtained and analyzed. This bibliographic data of articles published in the journals over ten years were extracted. VOS viewer was used to analyzing the data contained in all journals and articles. This systematic review shows that the development in education can absorb the changes that occur in technology. The findings from 1160 articles extracted show that using the Bayesian approach in the development of educational applications improves the quality of use, especially from the point of students. The level of predictive accuracy generated through the Bayesian network approach improves the quality of educational application development. However, the study's findings indicate that there is scope for research related to the application and use of this approach in the development of educational applications.
Anxiety Assistance Mobile Apps Chatbot Using Cognitive Behavioural Therapy Sulaiman, Suliana; Mansor, Marzita; Abdul Wahid, Rohaizah; Nor Azhar, Nur Anis Alisa
International Journal of Artificial Intelligence Vol 9 No 1: June 2022
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-0901.349

Abstract

The current pandemic COVID-19 and lockdown have worsened patients' health, especially those who suffer from an anxiety disorder. However, anxiety disorders are treatable by undergoing different therapies treatment. This paper aims to develop an Anxiety Assistant Mobile Apps Chatbot (ANUVA) for university students using Cognitive Behavioural Therapy (CBT). Structured activities are used to motivate the user to question their thought distortions and change them back. The ANUVA chatbot is developed using Evolutionary Prototyping Model. The effectiveness of the ANUVA chatbot was tested using Confusion Matrix. The result indicates that the accuracy of the ANUVA chatbot is 75%, precision 85% and recall 88%. The System Usability Scale (SUS) test was used to measure the usability, and the score shows 86.75 for the result. For future work, all the chat records will link with the counselling unit system to enhance the efficiency of the therapies.
Privacy and Customization of Clusters with Application Development Pallavi; Chandana; Rekha Sahithi; Shwetha; Devi, Sumithra
International Journal of Artificial Intelligence Vol 9 No 1: June 2022
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-0901.357

Abstract

This paper presents a high level view of how clusters are being used in large number of domains for preserving and protecting the data. Because of these , clusters are being exposed to many attacks coming from open network.. Hence there are many methods to design a privacy preserving clusters. To ensure these preserving clusters, cluster validity measurements are done for different type of Data. Protocols are used to do the privacy preserving. The clusters analysis are used in banking sector for identification of the bank customer profile. Algorithms are used to find the Sensitive data before making the individual data into clusters of data .and then the privacy is applied only on these sensitive data.
Blockchain Based Framework for Secure Data Sharing of Medicine Supply Chain in Health Care System Sahana; Thejashwini; Kamath, Vagdevi; Lahari, Yaparla; Mohanchandra, Kusuma
International Journal of Artificial Intelligence Vol 9 No 1: June 2022
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-0901.358

Abstract

The potential for blockchain technology in the healthcare sector is summarize in this study. It covers a wide range of technology themes, including storing medical information in blockchains, patient personal data ownership, and patient outreach via mobile apps. Blockchain was created to safeguard digital money transactions, but it has since gained popularity in a variety of other industries, including tourism, real estate, voting, the stock market, and supply chain management. In the healthcare industry, blockchain technology is rapidly gaining traction. Threats to integrity as well as threats to threats to threats to threats to threats to threats to Data management and medicine traceability are two of the most well-known blockchain uses in healthcare. We've explored the problems with standard data processing and drug tracing approaches in this paper.
A Novel Sep-Unet Architecture of Convolutional Neural Networks to Improve Dermoscopic Image Segmentation by Training Parameters Reduction Sadeghi, Faezeh; Taheri, Mohammad; Rastgarpour, Maryam; Sharifi, Arash
International Journal of Artificial Intelligence Vol 9 No 2: December 2022
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-0902.405

Abstract

Nowadays, we use dermoscopic images as one of the imaging methods in diagnosis of skin lesions such as skin cancer. But due to the noise and other problems, including hair artifacts around the lesion, this issue requires automatic and reliable segmentation methods. The diversity in the color and structure of the skin lesions is a challenging reason for automatic skin lesion segmentation. In this study, we used convolutional neural networks (CNN) as an efficient method for dermoscopic image segmentation. The main goal of this research is to recommend a novel architecture of deep neural networks for the injured lesion in dermoscopic images which has been improved by the convolutional layers based on the separable layers. By convolutional layers and the specific operations on the kernel of them, the velocity of the algorithm increases and the training parameters decrease. Additionally, we used a suitable preprocessing method to enter the images into the neural network. Suitable structure of the convolutional layers, separable convolutional layers and transposed convolution in the down sampling and up sampling parts, have made the structure of the mentioned neural network. This algorithm is named Sep-unet and could segment the images with 98% dice coefficient.

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