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Siti Mutiah
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Class Management Strategies In Increasing Achievement Study Nur Wahyuni; Muhammad Dekar; Siti Mutiah
International Journal For Advanced Research Vol. 1 No. 1: June 2024
Publisher : Outline Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61730/asdeh196

Abstract

Education is an important part for humans, if someone gets an education they will be able to develop the potential and talents that exist within them. The purpose of education is not only aimed at making someone literate, knowledgeable, or looking for a job. Learning activities affect the development and mindset of students, to achieve educational goals, teachers must be able to organize and manage classes so as to create a learning environment that allows students to learn well. This research uses the method of literature study. The research results are based on data from each article, the topic of which is classroom management strategies in improving learning achievement. As a class manager, the teacher has a strategic role including planning and carrying out activities with subjects and objects being students, determining and making decisions about strategies to be used for various activities, and providing alternative solutions to class problems and difficulties, cooperation skills are very important in education, both inside and outside of school. In explaining learning material, the teacher's voice must be in intonation, volume, pitch, and speed.
AI-Based Green Supply Chain Management Strategy in the Manufacturing Industry in Malaysia Siti Mutiah
International Journal For Advanced Research Vol. 2 No. 5: February 2026
Publisher : Outline Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61730/h50jjb89

Abstract

Global environmental pressures have pushed the manufacturing sector to adopt sustainable operations. This study investigated the integration of Artificial Intelligence into Green Supply Chain Management strategies in the manufacturing industry in Malaysia. Researchers applied a quantitative explanatory design to collect primary data from managers in medium and large companies. The research team distributed structured questionnaires to evaluate the impact of smart technology on green procurement, green manufacturing, and green logistics. Data analysis used structural equation modeling tools to test the causal relationships between variables. The research findings showed that the implementation of Artificial Intelligence significantly improved the effectiveness of all sustainable supply chain practices. Field data has proven that predictive algorithms and analytical systems optimize the search for environmentally friendly materials, minimize production emissions, and streamline reverse logistics cycles. This series of optimized practices has been shown to substantially improve companies' environmental and operational performance. This empirical investigation has concluded that mastery of advanced analytical technology serves as a crucial technical prerequisite for achieving ecological sustainability targets without sacrificing profitability. This research has provided empirical evidence that data-driven supply chain ecosystems empower the manufacturing sector to meet stringent environmental standards while maintaining increased efficiency and market competitiveness.
Co-Authors Muhammad Dekar Nur Wahyuni