Data mining is one of the most important steps of the knowledge discovery in databases process and is considered as significant subfield in knowledge management. Research in data mining continues growing in business and in learning organization over coming decades. This review paper explores the applications of data mining techniques which have been developed to support knowledge management process. The journal articles indexed in ScienceDirect Database from 2007 to 2012 are analyzed and classified. The discussion on the findings is divided into 4 topics: (i) knowledge resource; (ii) knowledge types and/or knowledge datasets; (iii) data mining tasks; and (iv) data mining techniques and applications used in knowledge management. The article first briefly describes the definition of data mining and data mining functionality. Then the knowledge management rationale and major knowledge management tools integrated in knowledge management cycle are described. Finally, the applications of data mining techniques in the process of knowledge management are summarized and discussed.

/pdf/data-mining-and-its-applications-for-knowledge-management-a-4kuld0r5gk.pdf

Data Mining and Its Applications for Knowledge Management: A Literature Review from 2007 to 2012

Air pollution poses a substantial threat to society and is considered one of the greatest environmental hazards for human beings. It is of great importance to develop air pollution early warning systems to alleviate the urgency and necessity of air quality monitoring and analysis. However, current early warning systems rarely focus on mining of pollutant characteristics and their corresponding scientific evaluation. In this study, we investigate an innovative hybrid air quality early warning system that comprises characteristics estimation, prediction, and evaluation. First, four different distribution functions with two estimation methods were applied for quarrying the characteristics of pollutants; Afterward, a hybrid forecasting model was proposed combined with an advanced data processing technique—a neural network and a new heuristic algorithm. For further mining the features of pollutants, two interval approaches as well as Extenics evaluation were utilized as indispensable components of the developed system. Simulation of pollutants series, including PM 2.5 , SO2, NO2, CO, and O3 are in line with lognormal distribution using certain parameters, and forecasting results are in good accordance with the empirical data using multiple criterion systems, i.e., MAE, MSE, RMSE, MAPE, MdAPE, FB, DA, and R 2 for deterministic forecasting and with IFCP and IFNAW for interval forecasting. Eight deterministic forecasting criterion for pollutants forecasting measurement indicate that the developed early warning system can achieve good performance in terms of its accuracy and effectiveness. Additionally, the positive interval forecasting results and good precision of Extenics evaluation indicate the efficiency and scalability of the designed early warning system.

An innovative hybrid air pollution early-warning system based on pollutants forecasting and Extenics evaluation

Fikih Kebencanaan (Coping with Disaster) is a product of Muhammadiyah's ijtihad to respond to contemporary problems, especially geological and non-geological disasters, which later become the normative foundation for the mitigation of health disasters such as the Covid-19 pandemic. The paradigm of the present research is a transdisciplinary qualitative type with a phenomenological approach. The research analyzed the reasoning of Fikih Kebencanaan and its actualization in Covid-19 mitigation, the medical health movement and the reconstruction of fiqh of worship during an emergency in particular, and how to deal with the disaster theologically in general. The results showed that the reasoning of Fikih Kebencanaan was expanded in terms of medical, theological, and educational movements. Medical movement is a health movement in the form of providing 74 Covid-19 Standby Hospitals capable of accommodating 3917 patients or 36.15% of the total number of cases in Indonesia, followed by the distribution of masks, gloves, and foods to 401,209 Covid-19 affected victims. The theological movement was in the form of religious provision in which Muhammadiyah attempted to reconstruct classical Islamic jurisprudence of the rule of worship to adapt to an emergency. In contrast, the Indonesian Council of Ulema (MUI) applied zoning. The educative movement was a preventive effort to counter narration stemming from micro-celebrity Da'i (Islamic preacher) & Influencers (religious preachers) tried to circumvent religious provisions with their viral statements on social media. This effort was realized by developing neuroscience Islamic education with learning media in visualization that combined modern comics and contemporary cartoons with cinematic narratives. The neuroscience Islamic education movement tried not to use the dogmatic-monolithic approach as in classical education.

The fiqh of disaster: The mitigation of Covid-19 in the perspective of Islamic education-neuroscience.

Model-based testing using UML activity diagrams: A systematic mapping study

Innovation in the workplace has been claimed to be a key factor in organizational survival and success. As future workers, university students are a major source of future innovations in organizational settings. Before they enter the labour market, it is in the context of Higher Education that they start developing some of their long-term behaviours, such as innovation behaviours. This study aims to explore the main determinants of university students’ innovation behaviours from a longitudinal perspective. The sample comprised 78 students of Psychology, Management, Fine Arts and Education. The results of this study show that previous innovation behaviours as freshmen, current levels of autonomy and cognitive demands are positively related to individual innovation among university students. Practical implications regarding how to foster innovation efforts in the context of Higher Education are discussed.

/pdf/determinants-of-students-innovation-in-higher-education-428fbva2xa.pdf

Determinants of students’ innovation in Higher Education

Study on Innovation Capability of College Students Based on Extenics and Theory of Creativity

Small and middle businesses (SMBs) are playing an increasingly important role, but their decision making process mostly relies on skilled employees which are usually inadequate. Based on information systems, data mining and Extension Theory (Extenics), we present a knowledge cultivating method and design a knowledge management platform for improve decision making quality. Through divergence analysis, correlation analysis, and implication analysis, a flow chart of knowledge cultivating algorithm has been designed, and an intelligent knowledge management platform has been developed. By collecting knowledge or information from conditions and the goal, we choose several knowledge as seed, then distribute it to all the department leaders, let them input relative knowledge including data mining knowledge to the platform. The platform then connects them into a knowledge tree with Human-Computer Interaction and enterprise ontology techniques intelligently. From the knowledge tree, we can find the problem solving map and guide the managers in SBMs to take actions by scanning all possible paths. The application in a food company proved its practicality value.

Xingsen Li

Papers

Study on Innovation Capability of College Students Based on Extenics and Theory of Creativity

Knowledge Cultivating for Intelligent Decision Making in Small & Middle Businesses

Extenics-based Test Case Generation for UML Activity Diagram☆

Study on the mechanism of improving creative thinking capability based on Extenics

Analysis on Test Cheating and its Solutions Based on Extenics and Information Technology