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Waste-Wise Education: Impact on Zero Waste Awareness and Practices Dina, Dina -; Fillaeli, Annisa; Jayanti, Asti Aulia
Jurnal Pendidikan Matematika dan Sains Vol. 11 No. 2 (2023): December 2023
Publisher : Faculty of Mathematics and Natural Sciences, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpms.v11i2.67346

Abstract

This study aimed to determine how waste-aware education affected the zero-waste consciousness and behaviors of chemical education students. A one-group, pretest-posttest design was implemented using a sample of 70 first-year students enrolled at Yogyakarta State University. The students were provided with workshop materials about waste management at temporary storage sites (TPS) and final processing sites (TPA) in Yogyakarta, as well as waste issues that have arisen with the advancement of science and technology. After completing two meetings of the workshop, they were assigned a series of consultations and a final project. In order to gather information, questionnaires, and portfolios were utilized. The findings of the study indicated that waste-aware education can enhance students' zero-waste awareness and practices. The sig value of 0.000 for the Wilcoxon test on zero waste awareness indicated a substantial increase. Similarly, the t-test conducted on zero waste practices yielded a significance value of 0.000, indicating that the provision of waste-aware education had a noteworthy impact. Students were, on the whole, enthusiastic about spreading the zero-waste philosophy throughout society.
Literature Review: Computational Methods for Designing Thermostable, Efficient, and Cost-Effective Enzymes for Industrial Applications Prisca Caesa Moneteringtyas; Nahzim Rahmat; Inten Pangestika; Sri Rahayu Widya Ningrum; Annisa Fillaeli; Aliyah Aliyah
Sustainable in Energy Science and Technology Vol. 1 No. 1 (2025): Sustainable in Energy and Science Technology
Publisher : Politeknik Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51510/siest.v1i1.2578

Abstract

Enzymes play a vital role as biocatalysts in various industrial applications due to their high specificity and efficiency under mild conditions. However, their limited thermostability significantly constrains their operational lifespan and effectiveness at elevated temperatures. This review examines recent advancements in computational methods aimed at enhancing enzyme thermostability, focusing on structure-based rational design, machine learning, and hybrid approaches. Key findings highlight the effectiveness of structure-based methods, in optimizing enzyme structures, while machine learning approaches demonstrated potential in predicting stabilizing mutations. This review identifies key research gaps and proposes directions for future studies to facilitate the industrial adoption of thermostable enzymes.