Mohamad Farhan Mohamad Mohsin

• Bsc (IT), Master (IT), PhD (IT)
• Lecturer at Northern University of Malaysia

Dendrite cell algorithm needs appropriates feature to represents its specific input signals. Although there are many feature selection algorithms have been used in identifying appropriate features for dendrite cell signals, there are algorithms that never been investigated and limited work to compare performance among them. In this study, six featu...

The characteristics of early outbreak signal which are weak and behaved under uncertainties has brought to the development of outbreak detection model based on dendrite cell algorithm. Although the algorithm is proven can improve detection performance, it relies on several parameters which need to be defined before mining. In this study, the most a...

tIn outbreak detection, one of the key issues is the need to deal with the weakness of early outbreak signalsbecause this causes the detection model to have has less capability in terms of robustness when unseenoutbreak patterns vary from those in the trained model. As a result, an imbalance between high detec-tion rate and low false alarm rate occ...

The aim of outbreak detection model is to obtain high detection rate but at the same time maintaining the low false alarm rate. However, because of the weakness of early outbreak signal that behaves under uncertainties, it causes imbalance result between detection rate and false alarm rate. In this study, an early review of danger theory, an approa...

Digital imaging has become an essential element in every medical institution. Therefore, medical image retrieval such as chest X-ray (CXR) must be improved via novel feature extraction and annotation activities before they are stored into image databases. To date, many methods have been introduced to annotate medical images using spatial relationsh...

Dengue is a virus that is spreading quickly and poses a severe threat in Malaysia. It is essential to have an accurate early detection systemthat can trigger prompt response, reducing deaths and morbidity. Nevertheless, uncertainties in the dengue outbreak dataset reducethe robustness of existing detection models, which require a training phase and...

Multi-label classification is a general type of classification that has attracted many researchers in the last two decades due to its applicability to many modern domains, such as scene classification, bioinformatics and text classification, among others. This type of classification allows instances to be associated with more than one class label a...

The purpose of this study is to enhance the exploration capability of conventional Salp Swarm Algorithm (SSA) with the inducing of Levy Flight. With such modification, it will assist the SSA from trapping in local optimum. The proposed approach, which is later known as an improved SSA (iSSA) is employed in monthly dengue outbreak prediction. For th...

Meta-heuristic algorithms have been significantly applied in addressing various real-world prediction problem, including in disease prediction. Having a reliable disease prediction model benefits many parties in providing proper preparation for prevention purposes. Hence, the number of cases can be reduced. In this study, a relatively new meta-heur...

New Multi-label Ranking Method

Dengue disease is the most common type of disease caused by mosquitoes. It is reported that dengue fever was first recognized in Thailand and Philippines in 1950. According to World Health Organization (WHO), dengue is a viral disease that spread in public environment where the number of dengue cases reported enlarge within 5 years by 1 million fro...

p>This paper discusses a unique business model of eatery recommender system based on local knowledge using mobile platform. The business model is developed to define the business concept of the innovation which is a rural innovation involving multiple entities (locals, eatery owners and users who are searching for eatery). The innovation highlights...

The ability to predict the financial market is beneficial not only to the individual but also to the organization and country. It is not only beneficial in terms of financial but also in terms of making a short-term and long-term decision. This paper presents an experimental study to perform univariate financial time series prediction using a clona...

Online newspaper is a valuable resource of information for decision making. To extract relevant information from them is a challenging process when their volume is massive, and its knowledge is in an unstructured form that is scattered on every page. This situation becomes more complicated when different news providers have different styles of jour...

Multi-Label Classification (MLC) is a general type of classification that has attracted many researchers in the last few years. Two common approaches are being used to solve the problem of MLC: Problem Transformation Methods (PTMs) and Algorithm Adaptation Methods (AAMs). This Paper is more interested in the first approach; since it is more general...

span>CSR UUMWiFi is a CSR project under Universiti Utara Malaysia (UUM) that provides unlimited free internet connection for the Changlun community. Launched in 2015, the service has accumulated a huge number of users with diverse background and interest. This paper aims to uncover interesting service users’ behavior by mining the usage data. To ac...

Online newspaper is a valuable resource of information for decision making. To extract relevant information from them is a challenging process when their volume is massive, and its knowledge is in an unstructured form that is scattered on every page. This situation becomes more complicated when different news providers have different styles of jour...

In the last few years, multi label classification has attracted many scholars and researchers; due to the increasing number of modern domains that are applicable to this general type of classification. Recently, it has been believed by many researchers that the best way to handle the problem of multi label classification is by exploiting the correl...

In this paper, a comparative analysis between the three main approaches that are being used to solve the problem of Multi Label Classification (MLC) have been conducted. The goal of doing this comparative analysis is to evaluate the performance of the three main approaches, and decide which approach to use with respect to the characteristics of the...

This paper describes the design and development of data retrieval system using near field communication (NFC) protocol to read and transfer data from the device storage panel located at the recycle bin. In existing systems, data are manually collected from the storage device using the SD card and sent for upload to regional workstation of the data...

In dendrite cell algorithm (DCA), the abnormality of a data point is determined by comparing the multi-context antigen value (MCAV) with anomaly threshold. The limitation of the existing threshold is that the value needs to be determined before mining based on previous information and the existing MCAV is inefficient when exposed to extreme values....

News websites produce thousands of articles and the number is growing. To publish up to date breaking news, each news providers apply different styles of journalism and as consequent readers may find different words and concepts used although when reporting a similar event. In this study, we examined the Malaysian online newspaper in order to seek...

In dendrite cell algorithm (DCA), the abnormality of a data point is determined by comparing the multi-context antigen value (MCAV) with anomaly threshold. The limitation of the existing threshold is that the value needs to be determined before mining based on previous information and the existing MCAV is inefficient when exposed to extreme values....

Change-point analysis has proven to be an efficient tool in understanding the essential information contained in meteorological data, such as rainfall, ozone level, and carbon dioxide concentration. In this study, change-point analysis was used to discover potential significant changes in the annual means of total rainfall, temperature and relative...

The dendrite cell algorithm (DCA) relies on the multi-context antigen value (MCAV) to determine the abnormality of a record by comparing it with anomaly threshold. In practice, the threshold is predetermined before mining based on previous information and the existing MCAV is inefficient when expose to extreme values. This causes the DCA fails to d...

Evaluating a novel or enhanced algorithm is compulsory in data mining studies in order to measure it has superior performance than its previous version. In practice, most of studies apply a straightforward approach for evaluation where appropriate performance metrics such as classification accuracy is selected, computes the mean and its variance ov...

Evaluating a novel or enhanced algorithm is compulsory in data mining studies in order to measure it has superior performance than its previous version. In practice, most of studies apply a straightforward approach for evaluation where appropriate performance metrics such as classification accuracy is selected, computes the mean and its variance ov...

Signal normalization is a part of signal formalization which is a vital data pre-processing constraint required for the functioning of the dendritic cell algorithm. In existing applications, most normalization algorithms are developed purposely for a specific application with drawing on human domain expertise and very few algorithms are designed fo...

The aim of outbreak detection model is to obtain high detection rate but at the same time maintaining the low false alarm rate. However, because of the weakness of early outbreak signal that behaves under uncertainties, it causes imbalance result between detection rate and false alarm rate. In this study, an early review of danger theory, an approa...

The dendritic cell algorithm is an effective technique to detect anomalies in time series applications. However, the algorithm is less effective when it mines a general classification dataset because the items are not organized in an orderly event-driven manner. Ideally, for they need to be arranged in sequence by sorting them according to decision...

The preliminary information of data being normalized into 0 and 1 is essential for an accurate data mining result including real value negative selection algorithm. As one class classification, only the self sample is available during normalization; therefore there is less confidence it fully represents the whole problem when the non-self sample is...

The outbreak sign exits when the monitored data starts to spike and abnormally behave. Labeled under the anomaly detection task, the outbreak detection model aims to detect the outbreak sign with good detection rate. In this paper, we discuss the issues related to outbreak and what makes outbreak detection distinct with other detection based proble...

Face recognition is one of the most interesting applications in the image processing field. To build a model to recognize the face of different people, we need to do several processes on the image to obtain the most efficient features. In this research a face recognition model is developed. The dataset used is of different face images. Neural Netwo...

Training programs for teacher's development in Malaysia are organized ever year. The selection of teachers to attend trainings is currently done randomly, by rotation and not based on their work performance. This poses a problem in selecting the right teacher to attend the right course. Up until now, there is no intelligent model to assist the scho...

Face recognition is one of the most interesting applications in the image processing field. To build a model to recognize the face of different people, we need to do several processes on the image to obtain the most efficient features. In this research a face recognition model is developed. The data set used is of different face images. Neural Netw...

Quality Function Deployment or QFD is a flexible and comprehensive group decision making technique used in product or service development, brand marketing, and product management. QFD can strongly help an organization focuses on the critical characteristics of a new or existing product or service from the separate viewpoints of the customer markets...

Conference management system (CMS) is designed to help the conference committee manages a conference well. The CMS which is available in market nowadays provides a well managed pre-conference function such as paper reviewing, paper submission, and participant registration system. However, payment module is not given priority by the existing CMS. Th...

This paper presents a new way of online communications through mobile to web that helps students and lecturers to be always aware of appointments no matter where they are. It contributes to the teaching and learning process, in which communication is made easy using short messaging system (SMS) technology which is called Web-based Student Appointme...

The main objective of case retrieval is to scan and to map the most similar old cases in case basewith a new problem. Beside accurateness, the time taken to retrieve case is also important. Withthe increasing number of cases in case base, the retrieval task is becoming more challengingwhere faster retrieval time and good accuracy are the main aim....

A limited number of factors in critical areas are necessary to identify the sustainability of companies [30]. It was found that three factors were commonly used [2] and a maximum of seven factors was recommended [2]. In order to identify the optimal factors, we propose a method based on rough set theory that consisted of five main steps. These were...

Face recognition is one of the most interesting applications in the image processing field. To build a model to recognize the face of different people, we need to do several processes on the image to obtain the most efficient features. In this research a face recognition model is developed. The dataset used is of different face images. Neural Netwo...

The government has arranged many programs for teacher development however the training is organized to fit yearly calendar without considering the right teacher for the right training. The selection of teacher to attend training is done randomly, by rotation and not based on their work performance. This paper investigate the weakest integrity trait...

This paper proposed an intelligent model that is aimed at facilitating key workers select suitable trainees for a training program. The proposed model is initiated because it has been found that many motivational training programs fail to meet their objectives because there is a mismatch between the needs of training programs and the integrity leve...

One of the powerful data mining analysis is it can generates different set of knowledge when similar problem is presented to different data mining techniques. In this paper, a programming dataset was mined using rough set in order to investigate the significant factors that may influence students programming performance based on information from pr...

Case-based reasoning (CBR) considers previous experience in form of cases to overcome new problems. It requires many solved cases in case base in order to produce a quality decision. Since today, database technology has allowed CBR to use a huge case storage therefore the case retrieval process also reflects the final decision in CBR. Traditionally...

Monitoring laboratory equipment record is important to ensure every item is always in place. Generally, in and out equipment is handled manually by technician by writing down the equipment information, including time and date in equipment circulation form. To automate the process, Radio Frequency Identification (RFID) is one of the most practical a...

This paper describes an ongoing project for recording examination attendance using Radio Frequency Identification (RFID). The project is carried out to test in a university, where the system which is named Portable Examination Attendance System (PEAS) is integrated with the existing system for record extraction. The use of RFID technology enables t...

Web Usage Mining is an aspect of data mining that has received a lot of attention in recent year (Kerkhofs et al., 2001). Commercial companies as well as academic researchers have developed an extensive array of tools that perform several data mining algorithms on log files coming from web servers in order to identify user behaviour on a particular...

In Malaysia, flood is one of the most common disasters that happen especially in monsoon time at the end of the year; where it will cause death and property lost. Today the human activities is the major problem that contribute for this disaster such as uncontrolled development, obstruction in river, forest harvested that damage rain catchment area...

The widespread use of network requires specialized professionals to deal with issues related to network management, hardware failure, system administration as well as maintenance. Yet, professionals with the required expertise are difficult to find, leading to problems such as increasing maintenance cost, poor network performance as well as users’...

Web log file analysis began as a way for IT administrators to ensure adequate bandwidth and server capacity on their organizations website. Log file data can offer valuable insight into web site usage. It reflects actual usage in natural working condition, compared to the artificial setting of a usability lab. It represents the activity of many use...

This paper presents a comparative study of two rule based classifier; rough set (R c ) and decision tree (DT c ). Both techniques apply different approach to perform classification but produce same structure of output with comparable result. Theoretically, different classifiers will generate different sets of rules via knowledge even though they ar...

Knowledge based system need quality knowledge to provide an accurate decision. Due to irrelevant and incorrect information of expert during knowledge acquisition, the information extraction from data mining approach can reduce the biases and misconceptions of multiple experts. Moreover, the real world data which is huge and incomplete has made it c...