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All Journal International Journal of Artificial Intelligence International Journal of Education, Science, Technology, and Engineering (IJESTE) International Journal of Recent Technology and Applied Science (IJORTAS) Journal of Engineering, Technology, and Applied Science (JETAS)
Saad, Ahmad Fadli
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Physics

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Journal : International Journal of Artificial Intelligence

 1 
Online Student Performance System integrating Multidimensional Data Visualization and Chatbot for Primary School Mohamad Ghazali, Nor Diyana Syafiqah; Saad, Ahmad Fadli
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-0902.457

Abstract

Today's technology has improved to the point that it can be utilized to execute many activities in daily life with minimum effort, and the world has acknowledged the worth of education in one's life. The schools have to analyze student performance manually, which requires a lot of time and effort from teachers to work on. However, the increasing amount of student data becomes difficult to analyze using traditional statistical techniques and database data management tools. The objective of this project is to study the current problems in the online student performance system. A preliminary survey of 30 respondents was conducted in order to gather information based on previous user experiences with the online student performance system. The next objective is to develop an Online Student Performance System integrating Multidimensional Data Visualization and Chatbot for Primary School using Web Development Life Cycle that can visualize student performance systems to assist teachers and parents. Following that, this project employed a tool based on Multidimensional Data Visualization techniques. Google Charts and Dialogflow were used in this project to visualize the dashboard and construct a chatbot for the system. The last objective is to evaluate the usability of the system. There are three experts to test the project usability using the Post-Study System Usability Questionnaire (PSSUQ). The findings of the project can be used as a guideline to improve the system in the future. Overall, this project will assist teachers and parents in obtaining information about their students’ academic performance. The data about the students' performance can be displayed in the dashboard as a chart, graph, or diagram, and they can also communicate with the chatbot if they require assistance or guidance in using the system and obtaining their students' performance.
Dietry Monitoring System Using Decision Tree to Control Human Obesity Mat Baseri, Mohamad Faiz; Saad, Ahmad Fadli
International Journal of Artificial Intelligence Vol 10 No 1: June 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-01001.485

Abstract

Nowadays, obesity is one of the dangerous diseases in the world. Lack of dietary monitoring system will make it difficult for people with obesity to reduce their weight problems. The main objective of this project is to develop a dietary monitoring system that can be used by everybody especially for obesity’s people. The method used in this study is to identify the strength and weaknesses of the existing system which involves reviewing some articles, journals, magazines, and books. The survey was conducted which involves 10 people answering the questionnaire. Respondent answered was used to improve the quality of the system. Next method is utilizing a waterfall model as a method to develop a dietary monitoring system. The system applied the decision tree technique to a classified food calorie. Therefore, the decision tree technique was used in developing this system. The last method used in this study involves the participation of three respondents to evaluate the usability of the system. Respondents need to answer whether they satisfied with the system or they can give suggestions for future improvement. The results of this study show that obesity is a public health issue that is rapidly increasing and must be addressed seriously by developing the system. Significant by developed this system such as helping obesity’s people to diet by giving them the guideline. In conclusion, this system will help people to diet using the decision tree technique for classifying food calories.
Career Finder System using Rule-Based Filtering for University Student Candidates Amir Hamzah, Fikri Nur Izzudin; Saad, Ahmad Fadli; Panessai, Ismail Yusuf
International Journal of Artificial Intelligence Vol 10 No 1: June 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-01001.539

Abstract

As a current reality, students are frequently questioned about a suitable career path for the future, but they are unaware of the jobs offered by current industries. Moreover, students seeking university admission frequently encounter difficulties selecting courses and educational programs, and they are confronted with a variety of available courses. This research aims to make a mobile application for students to obtain employment career options appropriate to their educational qualifications because student is often asked about a suitable career for their future but have no idea about the available career path that appropriate. The methodology that implements in this research is Mobile Application Development Life Cycle (MADLC) that have four phases which is identification, design, development, and testing. The Visual Studio Code with Flutter plugin is used to develop the mobile application and its function. Firebase is used to get the database to store all the data and works as backend function of the application. The finished system was tested accordingly based on the functionality that listed all available function of the system. The system considers students' educational qualifications and academic achievements to provide personalized recommendations. This system can assist students in making career decisions and pursuing the right career path, saving them time, and reducing the risk of making wrong choices. This research indicates understanding the importance of career decision-making for students before continuing their university studies. In conclusion, this research seeks to enhance the ability of students to make decision of the available career path provided through recommendation system.
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.
Drone Based Fire Detection System Based on Convolutional Neural Network Rahman, Hanif Ikmal; Saad, Ahmad Fadli; Yani, Achmad
International Journal of Artificial Intelligence Vol 11 No 1: June 2024
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-01101.669

Abstract

Open fires are happening more and more throughout Malaysia. It is either intentional or accidental fire. The most dangerous is an accidental fire because it may not be detected by anyone until it becomes large. Detecting a fire is not an easy task. People may not see an ongoing fire because it may be too far away, or the fire may be too small. The objective of this project is to build a fire detection system. Fire detecting systems are developed to ensure more accurate fire detection. To ensure accurate fire detection, this project uses a waterfall methodology. This project uses drones as a tool to help with fire detection. Using a Convolutional Neural Network (CNN), this project implements the use of the PyTorch framework in detecting fires. The testing was done with a distance of 2 meters from the fire and a height of 2 meter from the ground. Edited images were used and uploaded to the system. Accuracy results of 80% can ensure accurate fire detection. To evaluate the system, edited fire images are used to ensure the accuracy of the system. Therefore, CNN is a good tool for detecting fires.
Development of a Student Expense Tracking System Using Optical Character Recognition Shaharudin, Muhammad Hairil; Saad, Ahmad Fadli; Yani, Achmad; Manaf, Abdi
International Journal of Artificial Intelligence Vol 12 No 1: June 2025
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-01201.741

Abstract

Personal financial literacy is a vital skill for university students, yet many struggle to track their daily expenses due to time constraints and low awareness. This study aims to design and develop a web-based Student Expense Tracking System using Optical Character Recognition (OCR) technology to address this issue. The system allows users to automatically extract and record spending information from receipt images, reducing manual input and improving financial awareness. The development followed the Web Development Life Cycle (WDLC) using the Waterfall model, comprising planning, design, development, and testing phases. Visual Studio Code, Python 3, and Tesseract OCR were employed in system implementation. Wireframes and mockups guided the interface design, while backend development focused on data storage and OCR integration. Functionality testing showed a 100% pass rate across ten scenarios, validating the system's performance in image processing, budget management, and spending visualization. Usability testing using the Post-Study System Usability Questionnaire (PSSUQ) with 30 participants yielded a mean score of 4.45 out of 5, indicating a high level of user satisfaction. The system scored highest on ease of use (4.6), visual design (4.7), and recommendation likelihood (4.8), confirming its intuitive interface and appeal. Slightly lower scores in user confidence (4.1) and data organization (4.2) point to opportunities for interface refinement and improved user guidance. This research concludes that OCR can effectively support financial tracking for students. Future enhancements with NLP and machine learning are recommended to automate expense categorization and improve analytical capabilities.
Student Expense Tracking System Using OCR Saad, Ahmad Fadli; Shaharudin, Muhammad Hairil; Yani, Achmad; Manaf, Abdi; Ismail, Andi Almeira Zocha; Ismail, Andi Regina Acacia
International Journal of Artificial Intelligence Vol 12 No 2: December 2025
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-01202.929

Abstract

Nowadays student schedules are packed with their academic and curricular activities. Therefore, Students are no longer tracking their expenses because it is so hard to keep track with their expenses when they a have busy life. The aim of this research is to help students easily track their expenses by automating the process of extracting information from receipts. This research presents a student tracking expenses system using Optical Character Recognition (OCR) technology. The method that was used to develop the system was Website Development Life Cycle (WDLC). The system also uses Image Processing that implements OCR into the system. The system has been tested with a set of sample receipts, and the results show that it is able to accurately extract the relevant information with a high level of efficiency. The initial of this research involved designing the system, which was achieved through the creation of a detailed mockup and wireframe to establish a clear vision for its design. Then, it focused on developing the system, incorporating OCR technology to extract text from receipts. Thorough functional testing ensured that all system features, including user identification, image upload and OCR processing, expenditure management, budget setting, and data visualization, functioned as intended. The system offers users accurate and dependable capabilities for spending pattern analysis, budget management, and expense monitoring. Furthermore, the usability testing was conducted using the Post-Study System Usability Questionnaire (PSSUQ) from 30 students. The mean score of the System Usefulness, Information Quality and Overall Satisfaction is above 4 which indicates that it was appreciated by the students or respondents. Therefore, this system can be a valuable tool for students to manage their finances and make informed decisions about their spending.
Co-Authors Abdul Latiff, Muhammad Nazirul Mubin Amir Hamzah, Fikri Nur Izzudin Haris, Muhammad Akmal Husaini Ismail, Andi Almeira Zocha Ismail, Andi Regina Acacia Manaf, Abdi Mat Baseri, Mohamad Faiz Mohamad Ghazali, Nor Diyana Syafiqah Mohamad Roslan, Aini Khadijah Muhaiyuddin, Arina Syakirah Nur Iksan Panessai, Ismail Yusuf Rahman, Hanif Ikmal Roslan, Naim Najmi Shaharudin, Muhammad Hairil Yani, Achmad Zainal, Nisa Athirah