Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
This paper aims to evaluate and measure human capital in commercial banks based on different criteria using multi-decision-making techniques, and rank the banks according to value (Quality of HC) to identify banks that need to develop human capital. Numerous studies have been conducted in term of intellectual capital and its effect on the firm’s performance. Wherein, this term referred to the intangible asset that consist of the components are human capital, structural capital and relational capital. The banks under investigation will be ranked using MCDM techniques, namely the integrated Analytic Hierarchy Process (AHP) and Vlsekriterijumska Optimizacija Kompromisno Resenje (VIKOR). Moreover, this study used standard deviations to ensure banks ranking which performs in order to validate the objective of this study systematically. The results indicated the integration of AHP and VIKOR in solving the problems of human capital in measuring base of multi criteria and banks ranking according to the value of human capital for each bank. In conclusion, this paper provides indications from the literature with practical evidences on the impact of human capital into a growing global body of researches on the nature, size and characteristics of intellectual capitals
New Normal is a New order that can adapt to COVID-19. Indonesian people must maintain productivity in the midst of the COVID-19 corona virus pandemic. To realize the new normal scenario, the Indonesian Government and experts have formulated a protocol or Standard Operational Procedure (SOP) to ensure that people can return to their activities, but remain safe from COVID-19. One of the health protocols is to require people to wear masks. Several previous studies have designed a facial pattern recognition system, but to detect facial patterns using masks has not been the optimal solution. Therefore, this study has tried to design and analyze a facial pattern recognition system using masks using the Viola Jones method with the Haar Cascade Classifier. The Haar Cascade Classifier method is used to recognize facial patterns based on haar wavelets. The haar-like feature method is made easier with the cascade classifier adaboost. Meanwhile, the Viola Jones method is used for object detection methods by combining Haar Like Feature and has high accuracy and better performance than other eigen faces algorithms. The purpose of this study is to help the performance of the level of security in selecting facial patterns into a room that has complied with health protocols in the new normal era or not. From the test results with 50 face samples, the accuracy percentage is 92.3% and it takes a relatively short time to recognize faces using masks, which is an average of 15 seconds per sample tested
