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Journal : Bulletin of Electrical Engineering and Informatics

Key strategic issues pharmaceutical industry of SCM: A systematic literature review Erick Fernando; Meyliana Meyliana; Harco Leslie Hendric Spits Warnars; Edi Abdurachman
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (296.421 KB) | DOI: 10.11591/eei.v9i2.1264

Abstract

In this global era, making the competition in the pharmaceutical industry is very treacly. Implementation Supply chain management is the process of planning and managing all sourcing, procurement, distribution activities to increase value to customers and interested companies. Pharmaceutical companies are one that has a very complex supply chain. In this article will discuss the main issues that can improve industry strategic. This research is done by the systematic approach of literature to find things related to research. This study used 64 articles from search results. The results of this search are key issues in the pharmaceutical industry such as product and process development, capacity planning, factory and network design, e-business and IT applications, inventory management, outsourcing and reverse logistics, lean manufacturing, performance measures, people, and information technology. All of these findings are issues that improve the performance of supply chain management in the pharmaceutical industry.
The influence of data size on a high-performance computing memetic algorithm in fingerprint dataset Priati Assiroj; Harco Leslie Hendric Spits Warnars; Edi Abdurachman; Achmad Imam Kistijantoro; Antoine Doucet
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2760

Abstract

The fingerprint is one kind of biometric. This biometric unique data have to be processed well and secure. The problem gets more complicated as data grows. This work is conducted to process image fingerprint data with a memetic algorithm, a simple and reliable algorithm. In order to achieve the best result, we run this algorithm in a parallel environment by utilizing a multi-thread feature of the processor. We propose a high-performance computing memetic algorithm (HPCMA) to process a 7200 image fingerprint dataset which is divided into fifteen specimens based on its characteristics based on the image specification to get the detail of each image. A combination of each specimen generates a new data variation. This algorithm runs in two different operating systems, Windows 7 and Windows 10 then we measure the influence of data size on processing time, speed up, and efficiency of HPCMA with simple linear regression. The result shows data size is very influencing to processing time more than 90%, to speed up more than 30%, and to efficiency more than 19%.
Acceptance of augmented reality in video conference based learning during COVID-19 pandemic in higher education Sunardi Sunardi; Arief Ramadhan; Edi Abdurachman; Agung Trisetyarso; Muhammad Zarlis
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4035

Abstract

Three years after the COVID-19 pandemic emerged, we have adapted to the new normal, especially in the education field. Learning with video conferences has become our daily activity, and learning tools have gotten more prominent attention to gain student engagement, especially in emergency remote teaching (ERT). Since the trends of metaverse campaigns by meta, augmented reality (AR) has increased recognition in education contexts. However, very little research about the acceptance of augmented reality in video conferences, especially among university students. This paper aims to measure acceptance of AR in video conferences to motivate and inspire students to gain benefits and get impactful technology in the learning process. The research gathered data from a survey of 170 university students (from 5 majors in the study program and 17 different demographic areas) using unified theory of acceptance of technology 2 (UTAUT2). The result reveals that variables significantly impact acceptance: performance expectancy, hedonic motivation, and habit. The least significant but still positive effects are effort expectancy, social influence, and facilitating conditions. The study will provide helpful information on AR technology in video conferences and help top-level management in the university that provides online/distance learning in the early diffusion stage for metaverse in education.