Papers by Sofianita (Dr) Mutalib
Communications in computer and information science, 2017
There are many factors and ways to increase the quality and quantity of paddy yields. One of the ... more There are many factors and ways to increase the quality and quantity of paddy yields. One of the factors that can affect the quality of paddy is the amount of fertilizer used. The optimum amount of fertilizer for any field in any year cannot be determined with absolute certainty, thus in this project, we aim to find the optimum amount of nitrogen fertilizer required in paddy fields. Problems that are characterized by uncertainty can be solved by using fuzzy expert system. We develop fuzzy expert system prototype that utilizes Mamdani-style inference where the combination of nitrogen fertilizer data contain factors and rules, would produce results based on user's input. The data which were in form of paddy fields images were captured by an Unmanned Aerial Vehicle (UAV) or commonly known as drone and variables applied in fuzzy rules are obtained from a thorough analysis made with team of agriculture experts from Malaysian Agricultural Research and Development Institute (MARDI).
International Journal of Information Engineering and Electronic Business, Feb 8, 2021
In early 2020, the world was shocked by the outbreak of COVID-19. World Health Organization (WHO)... more In early 2020, the world was shocked by the outbreak of COVID-19. World Health Organization (WHO) urged people to stay indoors to avoid the risk of infection. Thus, more people started to shop online, significantly increasing the number of e-commerce users. After some time, users noticed that a few irresponsible online retailers misled customers by hiking product prices before and during the sale, then applying huge discounts. Unfortunately, the "discounted" prices were found to be similar or only slightly lower than standard pricing. This problem occurs because users were unable to monitor product pricing due to time restrictions. This study proposes a Web application named PriceCop to help customers' monitor product pricing. PriceCop is a significant application because it offers price prediction features to help users analyse product pricing within the next day; thus, it can help users to plan before making purchases. The price prediction model is developed by using Linear Regression (LR) technique. LR is commonly used to determine outcomes and used as predictors. Least Squares Support Vector Machine (LSSVM) and Artificial Bee Colony (ABC) are used as a comparison to evaluate the accuracy of the LR technique. LSSVM-ABC was initially proposed for stock market price predictions. The results show the accuracy of pricing prediction using LSSVM-ABC is 84%, while it is 62% when LR is employed. ABC is integrated into SVM to optimize the solution and is responsible for the best solution in every iteration. Even though LSSVM-ABC predicts product pricing more accurately than LR, this technique is best trained using at least a year's worth of product prices, and the data is limited for this purpose. In the future, the dataset can be collected daily and trained for accuracy.
IOP Conference Series: Earth and Environmental Science
Plants are essential in the Earth, as it supplies the oxygen needed by human beings and animals, ... more Plants are essential in the Earth, as it supplies the oxygen needed by human beings and animals, and becomes the source of foods and medical treatments. Many medicinal plants can treat diseases and it is also called herbal plants. Traditionally, these plants are processed and transformed as traditional medicines to cure any diseases. Nowadays, there are still practices that use medicinal plants. However, it is quite challenging to find herbal plants and these herbal plants come with different features such as size, shape, and colour. Therefore, this paper presents a machine learning approach, namely clustering, to classify the herbal plant species through images. We focused on six herbal plants in Malaysia which are Peacock Fern, Misai Adam, Mempisang, Tapak Sulaiman, Pandan Serapat and Kacip Fatimah. These species were collected from Taman Negara Pahang, Kuala Keniam, Malaysia. The k-means algorithm was employed by experimenting with several numbers of clusters in the range of two,...
Online shopping has become one of the popular mediums for people to use online transactions due t... more Online shopping has become one of the popular mediums for people to use online transactions due to its economical and easiness.It is more convenient to those who simply do not have time to shop physically and prefer delivery service. However, the courier services nowadays are unable to keep up with the increasing consumer demand. The problem is caused by the delivery process that is not synchronized due to the problem of finding the best route of distribution. Distributors are unable to plan their distribution path with the minimal distance.Furthermore distributors are only able to reach each district distribution centre once a day and revisit the distribution centre will increase the time spent and operation cost. This study developed Courier Delivery Services Visualisor (CDSV) that is able to visualize the best route to be taken by distributor, so that the courier service can arrive on time.CDSV employed Genetic Algorithm (GA) and Astar Algorithm (A*) that integrates with Geograph...
2023 4th International Conference on Artificial Intelligence and Data Sciences (AiDAS)
Atmosphere, Mar 29, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Lecture Notes in Computer Science, 2012
ABSTRACT
Designing the algorithm to extract features in signature is a challenging task due to complex hum... more Designing the algorithm to extract features in signature is a challenging task due to complex human behavior which is developed through repetition. Features such as direction, slant, baseline, pressure, speed and numbers of pen ups and downs are some of the dynamic information signature that can be extracted from an online method. However, the variables for identifying the features is rarely discussed and notified. Therefore, this paper presents the variables that involve in designing the algorithm for extracting the slant features. Both local and global slant characteristics are considered in extracting the features. Local slant is the longest slant among the detected slant while the global slant represents the highest quantity of classified slant whether the slant are leftward, upright or rightward. Signature Extraction Features System (SEFS) is used to extract the slant features in signature automatically for analysis purposes. The images created by SEFS are used as samples for the questionnaire to identify the slant features and to be given to human expert for evaluation. The results from the SEFS are compared with the result from the questionnaire. The results demonstrate a competitive performance with 85% accuracy.
This study presents pre-processing methods for detecting lane detection using camera and Light De... more This study presents pre-processing methods for detecting lane detection using camera and Light Detection and Ranging (LiDAR) sensor technologies. Standard image processing methods are not suitable for complicated roads with various sign on the ground. Thus, determining the right techniques for pre-processing such data would be a challenge. The objectives of this study are to pre-process the scanned images and apply the image recognition algorithm for lane detection. The study employed Canny Edge Detection and Hough Transform algorithms on several sets of images. A different region of interest was experimented to find the optimal one. The experimental results showed that the proposed algorithms could be practical in terms of effectively detecting road lines and generate lane detection
This study presents pre-processing methods for detecting lane detection using camera and Light De... more This study presents pre-processing methods for detecting lane detection using camera and Light Detection and Ranging (LiDAR) sensor technologies. Standard image processing methods are not suitable for complicated roads with various sign on the ground. Thus, determining the right techniques for pre-processing such data would be a challenge. The objectives of this study are to pre-process the scanned images and apply the image recognition algorithm for lane detection. The study employed Canny Edge Detection and Hough Transform algorithms on several sets of images. A different region of interest was experimented to find the optimal one. The experimental results showed that the proposed algorithms could be practical in terms of effectively detecting road lines and generate lane detection
Nowadays, the history of Batu Aceh has been forgotten through the centuries. If this happens, fut... more Nowadays, the history of Batu Aceh has been forgotten through the centuries. If this happens, future generations will not know the absence of this creative heritage. Even to an expert, it takes time for them to recognize and memorize each type easily. To solve this difficulty, a prototype is devised to guide future generation to appreciate these precious cultural heritage artifacts in the Islamic-Malay civilization. A neural network approach is employed for supervised classification of this Batu Aceh object images. In this research, back propagation algorithm is applied. In order to classify the type, several images of each type of Batu Aceh are used as training samples. The image samples would be processed to extract useful information to be fed into each type of Batu Aceh. The network will be trained first with data samples that have been converted into binary forms. Then, network parameters such as momentum value, learning rate and number of hidden neuron will be set to ensure the performance of the system. After several experiments were conducted, 0.04 learning rate value with 40 hidden neurons in the hidden layer was found to be the optimal parameter values for the neural network. The learning curve is smooth and the performance goal is met.
Advanced Science Letters, Nov 1, 2013
ABSTRACT
International Journal of Intelligent Systems and Applications in Engineering, Mar 31, 2022
The year 2020 has been a tough year with the global pandemic situation, and the utmost priority i... more The year 2020 has been a tough year with the global pandemic situation, and the utmost priority is to live in a clean, green, and safe environment. One of the areas that the governments are emphasizing for the readiness of our ecosystem is autonomous and contactless environments in adapting to the new norm. Thus, Autonomous Vehicle (AV) is a promising technology to bring forward. One of the critical aspects of Autonomous Navigation is object detection. Most AV use multiple sensors to detect objects, such as cameras, radar and Light Detection and Ranging sensor (LiDAR). Nowadays, the LiDAR sensor is widely implemented due to the ability to detect objects in the form of pulsed lasers, benefiting in low-light object detection. However, even with advanced technology, poor programming can affect the performance of object detection system. Thus, the study explores the state-of-the-art of You Only Look Once (YOLO) algorithms namely Tiny-YOLO and Complex-YOLO for object detection on KITTI dataset. Their performances were compared based on accuracy, precision, and recall metrics. The results showed that the Complex-YOLO has better performance as the mean average precision is higher than the Tiny-YOLO model when tested with equal parameters.
... S., Armand, M., Blumenstein, and V., Muthukkumarasamy, Off-Line Signature Verificatio based ... more ... S., Armand, M., Blumenstein, and V., Muthukkumarasamy, Off-Line Signature Verificatio based on the ... line Signature Verification and Recognition by Support Vector Machine, DissertationComputer Engineering Department ... [23] RC Eberhart and J. Kennedy, "A New Optimizer ...
Lecture Notes in Computer Science, 2012
With the availability of biological data and the power of sharing, it produces many opportunities... more With the availability of biological data and the power of sharing, it produces many opportunities for computer scientists to perform researches in bioinformatics. Generally the researches propose methods for different tasks, mainly to develop algorithms in diagnosing and identification of diseases. One of the primary studies that relevant to health and diseases is genome wide association studies (GWAS). Normally the studies are conducted in different populations to replicate the risk loci of specific disease and the number of groups are keep on progressing, including those from Asian country. Computer scientists should be involved in GWAS due to certain problems and the complexity of the processes involved. The problems and past studies related to GWAS are presented in this paper.
... Abdul-Rahman, Yap May Lin, Intelligent Systems SIG, Study Centre of Systems Science, Faculty ... more ... Abdul-Rahman, Yap May Lin, Intelligent Systems SIG, Study Centre of Systems Science, Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Shah Alam, Selangor, Malaysia {shuzlina, maylin}@fskm.uitm.edu.my Sofianita Mutalib, Azlinah Mohamed ...
International Journal of Advanced Computer Science and Applications, 2021
Tourism is among the significant source of income to Malaysia and Taman Negara Pahang is one of t... more Tourism is among the significant source of income to Malaysia and Taman Negara Pahang is one of the Malaysia's tourism spots and the heritage of Malaysia in achieving the Sustainable Development Goals (SDG). It has attracted many international and local tourists for its richness in flora and fauna. Currently, the information of tourists' visits is not properly analyzed. This study integrates the internal and public information to analyze the visits. The regression models used are multiple linear regression, support vector regression, and decision tree regression to predict the tourism demand for Taman Negara, Malaysia and the best model was deployed. Predictive analytics can support the decision-making process for tourism destinations management. When the management gets a head-up of the demand in the future, they can choose a strategic planning and be more aware about the factors influencing tourism demand, such as the tourists' web search engine behaviors for accommodation, facilities, and attractions. The factors affecting the tourism demand are determined as the first objective. The role of independent variable was set to the total number of visitors, subsequently being set as the target variable in the modeling process. A total of 30 models were generated by tuning the cross-validation parameters. This study concluded that the best model is the multiple linear regression due to lower root mean square error (RSME) value.
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Papers by Sofianita (Dr) Mutalib