Dengue fever (DF) and the potentially fatal dengue haemorrhagic fever (DHF) are continue to be a crucial public health concern in Malaysia. This paper proposes a prediction model that incorporates Support Vector Machine (SVM) in predicting future dengue outbreak. Datasets used in the undertaken study includes data on dengue cases provided by the Health Department in Kelantan, Malaysia. Data scaling were applied to normalize the range of features before being fed into the training model. In this regard, SVM models built on the basis of three different kernel functions including Gaussian radial basis function (RBF), polynomial function and linear function. The SVM with RBF kernel function was superior to the other techniques because it obtains the highest prediction accuracy of 85%. The polynomial is an alternative model that can achieve a high prediction performance in terms of sensitivity (76%) and specificity (87%).

This paper proposes a web-based application designed to help elementary school students who have difficulty learning online independently and also their parents who are currently having difficulty teaching their children to study at home online, especially at this time of difficulty with a pandemic outbreak like COVID-19; this time does not allow for physical meetings for the learning process in primary schools. In this paper, we only focus on mathematics because based on several other studies, it is very difficult and important to learn mathematics at the beginning of educational activities such as at the elementary school level. In this paper, the system is modeled using the Unified Modeling Language (UML) tool in the form of a use case diagram which is used to describe the proposed business process and uses class diagrams to describe the database model diagram. In this case, the class diagram is used to describe the data in the class diagram where each class refers to a table in the database. The web-based application user interface is shown at the end to show the communication between users and applications, where this web-based application is implemented using Personal Home Pages (PHP) as server programming and using MySQL to store database model designs. Moreover, for the Intelligent Tutoring System (ITS), content was created using the Cognitive Tutor Authoring Tools (CTAT) which is an authoring tool for learning mathematics created by Carnegie Mellon University. In the end, this web-based application is expected to be used and support teachers as a complement to online mathematics learning, especially during difficult times such as during the COVID-19 pandemic.

Generalization of the Fuzzy set and Intuitionistic Fuzzy set concept is called as Neutrosophic set which is a powerful general formal framework. The components in Neutrosophic set has a degree of truth (T), indeterminacy (I) and falsity (F). The value of this components are between [0,1], respectively. A Neutrosphic set has a general formal framework for analysing uncertainty in data set or undetermined information. Not only uncertainty, Neutrosophic set can also analyse large information sets or big data sets as well. Single Valued Neutrosophioc sets (SVNs) was introduce to be used expediently to deal with real problems and it is appropriate in solving data mining problem and make a decision for the problem. In this paper, Single Valued Neutrosophic set (SVNs) was proposed to measuring factors impact on student engagement and attitude in mathematics achievement based on Trends in International Mathematics and Science Study TIMSS 2015 for ASEAN countries and use the data to illustrate the applicability of the proposed factors similarity measures in decision making. The result shows that the factor which is Confidence in Mathematics include in highly acceptable zone in students’ engagement and attitude in Mathematics Achievement for ASEAN countries.