A knowledge diagnostic system for product defects

The need to fulfill customer satisfaction and increase product quality has motivated many manufacturing firms to investigate and diagnose their product failure. To gain a correct and accurate diagnostic, the entire processing root must be recorded and controlled in every step of the manufacturing process. In this research, a prototype system has been developed for a tile manufacturing company to diagnose tile defects and to recommend actions for improvement. This system consists of two main components, the knowledge base and inference engine. The knowledge base has been developed by capturing data and information that are related to tile defects, such as symptoms, probable causes, types of defects, processes, sub processes, tile classifications, etc. On the other hand, the inference engine has been built by implementing the forward chaining and depth first searching methods to search for the causes of defects. The analysis proves that this system can help the workers in the company to diagnose tile defects and solve the problems. Besides this, the system can also help to share and transfer knowledge among the knowledge workers in the company

The Classification of Children Gadget Addiction: The Employment of Learning Vector Quantization 3

The addiction of children to gadgets has a massive influence on their social growth. Thus, it is essential to note earlier on the addiction of children to such technologies. This study employed the learning vector quantization series 3 to classify the severity of gadget addiction due to the nature of this algorithm as one of the supervised artificial neural network methods. By analyzing the literature and interviewing child psychologists, this study highlighted 34 signs of schizophrenia with 2 level classifications. In order to obtain a sample of training and test data, 135 questionnaires were administered to parents as the target respondents. The learning rate parameter (α) used for classification is 0.1, 0.2, 0.3 with window (Ɛ) is 0.2, 0.3, 0.4, and the epsilon values (m) are 0.1, 0.2, 0.3. The confusion matrix revealed that the highest performance of this classification was found in the value of 0.2 learning rate, 0.01 learning rate reduction, window 0.3, and 80:20 of ratio data simulation. This outcome demonstrated the beneficial consequences of Learning Vector Quantization (LVQ) series 3 in the detection of children's gadget addiction

The Success Factors in Measuring the Millennial Generation’s Energy-Saving Behavior Toward the Smart Campus

The millennial generation has a pivotal role in leading the industrial digital revolution. Energy-saving behavior and millennials’ awareness of energy consumption for educational context become crucial in performing a smart campus. This study tries to identify the success factors in measuring the millennial generation’s energy-saving Behavior toward the smart campus. The measurement model considers two significant constructs, including energy-saving attitudes with energy-saving education (organizational saving climate); energy-saving education and environment knowledge (personal saving climate); and energy-saving information publicity as sub-indicators, and construct energy-saving Behavior viz sub-indicators Behavior regarding energy and behavior control. In order to determine the preference level of each indicator and sub-indicator, the Fuzzy Analytical Hierarchy Process (Fuzzy-AHP) approach was executed by disseminating the questionnaire to 100 respondents from energy practitioners, students, and academicians in Indonesia. The calculation reveals that the energy-saving behavior construct has a higher priority value (0.94) than the energy-saving attitude (0.06). Meanwhile, energy-saving education and environment knowledge (personal saving climate) have been analyzed at the cutting-edge sub-indicator, followed by energy-saving information publicity and education (organizational saving climate). In addition, the sub-indicator for behaviors regarding energy becomes more demanding compared to behavioral control. As a novelty, the priority analysis of this Model aids the management of the campus and government in developing smart campus policies and governance. This Model can be used as a guideline for the management level to execute the smart campus practices. Thus, the effectiveness and optimization of smart campus transformation can be cultivated and accelerated. Besides, the potential coming of risks can be avoidable

The enhancement of collaborative learning through integrated knowledge management systems: E-learning model

There are still a few educational platforms that apply a Knowledge Management System (KMS) concept in conducting its operational work. In addition, several obstacles associated with e-learning implementation trigger the in-effectiveness of collaborative learning. However, the concept of Knowledge Management (KM) from a Sharia perspective has significant implications for education systems. This research, therefore, explored the relevance of the Learning Management System (LMS), KM theory, and Sharia education perspective on the development of the Integrated Knowledge Management System (IKMS) Framework. The IKMS components and structures are literature reviewed and then qualitatively justified through the focus group discussion which involved some students, lectures, and experts from two Sharia-based Universities in Indonesia. To verify and test the framework, an IKMS-Edu system was developed by focusing on the adoption of a controlling agent system in the online discussion. Herein, filtering and summarization technology was embedded into IKMS-Edu towards a smart controlling agent. This agent adopted the operational work of IKMS-Edu framework leveraging in four constructs activities viz., knowledge creation and knowledge acquisition (construct 1), knowledge organization and knowledge storage (construct 2), knowledge dissemination and knowledge retrieval (construct 3), and knowledge evaluation and feedback (construct 4). To date, the statistical evaluation of the IKMS-Edu system’s acceptance is conducted by disseminating the questionnaires. The mean scores revealed 40.45% of the respondents strongly agreed, and 42.18% agreed on the proposed framework and prototype system thus the framework aided in performing the IKMS during the collaborative learning activities. As such, this evidence provides the strong support that IKMS-Edu significantly enhanced the effectiveness of collaborative learning by considering the Sharia values of trust, knowledge, virtue, psychosocial, and civilization development into knowledge management activities

Profile of Single Mode Fiber Coupler Combining with Bragg Grating

This paper describes a numerical experiment of design and operation of a fiber coupler between single mode fiber and fiber Bragg grating (FBG). Both components are coupled depending with optical waveguide and source parameters. A characterization of fiber coupler is simulated by varying long grating of 10 mm to 60 mm using transfer matrix method based on coupled mode equation. The wave peak, transmission, and dispersion parameters are analyzed to determine the performance of the fiber coupler. The transmission spectrum showed the wave peaks rise to any increase in the grating length on channel 1 and channel 2. Transmission on channel 1 and channel 2 decreased from the wavelength range of 1.45μm–1.55μm and rised in the range of 1,55μm–1,65μm for each increment in length of grating. The dispersion showed the zero dispersion at specific wavelength for each increase in length of grating. This component can be applied for controlling information signal in wide range communication

Smart Performance Measurement Tool in Measuring The Readiness of Lean Higher Education Institution

The development of autonomy University drives management innovation to increase the alternative sources of income with the purpose of the efficiency improvement and productivity of the institution. One of a management model that leads to increase productivity through cost reduction is Lean service. The implementation of Lean Higher Education Institution (LHEI) requires total involvement of organization maneuver, including social culture, infrastructure, and leadership support. Therefore, the readiness of the institution in welcoming Lean concepts becomes significant. This article tried to develop a prototype of an intelligent performance measurement tool by analyzing the readiness indicators using the Analytical Hierarchy Process (AHP) method. This tool provided the classification of organizational readiness into five performances level. The measurement performed as a Decision Support System (DSS) to recommend University management level in making a decision and correcting action towards the optimal execution of Lean service. As a case study, this prototype system has been tested with Black Box and User Acceptance Test (UAT) in Indonesia Islamic Higher Education Institution. The finding reveals that the prototype system can be used as a performance measurement tool in measuring the readiness of Lean's service in Islamic Higher Education Institution

The Prediction of Earthquake Building Structure Strength: Modified K-Nearest Neighbour Employment

The earthquake damage brings significant effects. The resilience of buildings against the earthquake and the destruction’s location is not an efficient outcome from previous research. This study applied the Modified K-Nearest Neighbor (MK-NN) in predicting the concrete structures’ performance despite the earthquakes. The 2-story building prediction covered earthquake history, time, concrete quality, displacement, velocity, and acceleration. The analysis of MK-NN provided the values of Euclidean, distance calculation, validity, and weight voting towards the classification of damages as “Safe” or “Immediate Occupancy” (IO).  The K values exploited were 1, 3, 5, 7, 9, and 11, and simulation data training at 10:90, 20:80, 30:70. This study revealed the highest degree of accuracy at 98.85% with K=1 and a ratio of 30:70. Simultaneously, the lowest error rate was 1.15% at a similar K value and ratio. Herein, MK-NN significantly exceeds the accuracy and error rate of KNN up to 1.02% and 0.69%, respectively. To date, the automatic calculation prototyping software was then successfully developed. Ensuring the application’s accuracy, the Confusion Matrix, the Black box, and User Acceptance Test (UAT) have been performed. In a nutshell, this study provides a significant contribution to planning and information analysis of earthquake-resistant construction