Attempts to adopt the network data massively from the social media refer to provide the particular means in extracting the value from information space such as message, conversation, transaction and others, where the sources of structured data come from enterprise resources data and sources of unstructured data come from audio and video. It can be achieved to expand the process of extracting the value from social network to pattern the data sources to fulfil the organisation goal. This paper aims to reveal the way of big data approach in extracting data value from data complexity involving variety and velocity into the volume. This study was conducted using contents analysis by reviewing some literatures in peer-reviewed journals, chapters, books and proceedings in developing prototype using data analytics associated from the topic, users and time analytics. The findings reveal that big data emerging technology with analytic process provides particular advantages to transform the pattern of information fitted into the innovative environment of online learning resources (OLR) to enhance in developing the learning resources. Both prototype and model of data extraction value could be enhanced to facilitate the learning environment in supporting implementations with ease and convenience. This study is expected to contribute to improve the learning environment and outcomes with performance and achievement by enhancing students' learning process development to provide online resources in higher education context.

Background and Objective: Educational entrance examination refers to the extent in selecting the student to enroll through admission into educational institution. It has an entire procedure administered to achieve from primary to higher education. However, not many researches were conducted using mathematical theory of evidence. This study aims to investigate the examination process about the admission into educational institutions using mathematical theory of evidence. Materials and Methods: The assessment on student's entrance examination through the effectiveness of Dempster-Shafer theory can be viewed with its significant contribution by combining the previous measure of evidence. Eight student's entrance examination results were proposed. Results: The result reveals that there were some significant findings in assessing the student's entrance examination using mathematical theory of evidence. Those were obtained degrees of belief of Computer Science with 76.4% for student 1, Computer Science with 64.2% for student 2, Computer Science with 75.4% for student 3, Computer Science with 80.3% for student 4, Computer Science with 67.4% for student 5, Computer Science with 57.1% for student 6, Islamic Studies with 26.3% for student 7, Computer Science with 62.5% for student 8. Conclusion: In this research, mathematical theory of evidence has been successfully developed to assess student's entrance examination and displaying the result of identification process. � 2017 Andino Maseleno et al.

The problem faced in the medical world is that decision makers to determine the disease still use manual method by doctor, even though doctor as human has a natural weakness, namely fatigue and limited physical consequences, it can be misdiagnosed, slow, sometimes uncertain, as well as transmissible disease of humans. To solve this problem, the writer conducted research for decision makers to determine transmissible disease of human using the forward chaining method in determining the initial prediction of a disease after the patient enters the symptoms. Then from the prediction of the initial disease, the software used backward chaining method in asking for other symptoms that the patient had not entered. This software was created by using the Fuzzy Set method in processing data on a knowledge-based system. Fuzzy method recognized the truth partially, this is very useful so that the system made has intelligence like human. � 2018, Advanced Scientific Research. All rights reserved.

The recent reviews indicated learning expertise level could be enhanced with skills, creativity and preferences. This stage should be taken at the first stage combined highly with providing the framework in underlying the learning expertise. This paper attempts to propose the model of Hau-Kashyap used to describe in yielding the robust results to measure the learning expertise level. This approach was selected to give an insight with a more accurate by examining twelve items of questionnaire applied among the students at tertiary level to explore the representation of wide range of knowledge and skills. The results found that the stage level of belief that ranges combined from the level of expertise 1–12 was indicated that Hau-Kashyap approach can be determined to measure the learners’ expertise more fairly and easily. This method is supposed to contribute providing the purposeful rule in combining the learning expertise constructed into a single and more informative hint with related concern of the measurement.

Clean air is a necessity for human. Human needs clean and healthy air without being contaminated by vehicle smoke that can endanger human health. vehicle smoke contains harmful substances for human including carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx) and lead metal (Pb). This can make air quality worse and can cause human be suffered of diseases including ARI (Acute Respiratory Infection), shortness of breath, sore eyes, coughing, brain damage and mental disability in children. Decision Support System (DSS) is a system to support Managerial decision makers in semi-structured decision situations and in this research author made a study of the DSS model to determine the level of danger of vehicle smoke, this study uses the Fuzzy Multiple Attribute Decision Making method (FMADM) where this method is a way to find optimal alternative from a number of alternatives with certain criteria, from very low things that was from 0-0.25, medium from 0.3-0.50, to the most dangerous thing that was from 0.8-1. Hopefully with the existence of this research later it can be useful for the community, especially for public health. � 2018, Advanced Scientific Research. All rights reserved.