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Abdul Hafid Hasim
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International Journal of Environment, Engineering, and Education
Published by Three E Science Institute
ISSN : -     EISSN : 26568039     DOI : https://doi.org/10.55151/ijeedu
Core Subject : Science, Education, Social, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Engineering Environmental Science
The International Journal of Environment, Engineering, and Education [e-ISSN: 2656-8039] is a peer-reviewed, open-access journal that is published three times a year [in April, August, and December]; this journal provides the right platform for authors to update their knowledge, information, and share their research results with the more significant scientific community publishing research articles explaining the ecological, technical, and educational impact of research from various disciplines publishing research articles explaining the environmental, technical, and educational implications of research from multiple disciplines publishing research As an interdisciplinary scientific publication, this journal encourages collaboration between researchers, academics, practitioners, and policymakers in various sectors to develop sustainable solutions to address environmental, engineering, and educational problems and promote sustainable development.
Arjuna Subject : Umum - Umum
Articles 5 Documents
 1 
Search results for , issue "Vol 5 No 1 (2023)" : 5 Documents clear
Awareness of Generation Z Students about The Plaf (Plastic Flamingo) and Other Campaigns Concerning Plastics in Online Shopping Mary Grace C. Manucom; Kimberly P. Alcaraz; Rica Pearl S. Alejo; Karen Celine M. Gaddi; Kate Eleonore P. Recio; Reika G. Yamaguchi
International Journal of Environment, Engineering and Education Vol 5 No 1 (2023)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v5i1.78

Abstract

Environmental awareness is crucial in addressing the issues of plastic waste and pollution, which have a significant impact on our environment and our health. The study aimed to analyze the awareness of Bulacan State University College of Science Generation Z students regarding PLAF (Plastic Flamingo) and other campaigns related to plastics in online shopping. The researchers used a descriptive research design to achieve this goal and collected data from 350 samples of Generation Z students through a standardized questionnaire distributed via Google Forms. The findings revealed that Shopee is the most commonly used online shopping application by students, and they tend to purchase items online when needed. Bubble wrap emerged as the most frequently used parcel packaging material. The results also indicated that the students are highly aware of the different impacts of parcel packaging, as evidenced by the mean score of 4.02. However, their awareness of environmental campaigns related to plastic was only average, with a mean score of 2.93. In particular, the understanding of PLAF (Plastic Flamingo) was low, with a cumulative mean score of 2.13. The findings suggest the need to improve Generation Z students' awareness of environmental campaigns and promote ecological practices and involvement in addressing plastic waste and pollution issues. Educating and engaging students through various campaigns and initiatives can help raise their awareness of the environmental impacts of plastic waste and encourage them to adopt sustainable practices in their daily lives.
The Implementation of the Mangrove Quality Index: A Way to Overcome Overestimation and Classification Concerns in Detecting Mangrove Forest Cover W. T. S. Harshana; M. D. K. L. Gunathilaka
International Journal of Environment, Engineering and Education Vol 5 No 1 (2023)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v5i1.85

Abstract

The increasing applications of Geographic Information Systems (GIS) and Remote Sensing (RS) for mapping, predicting, and monitoring are practical for sustainable mangrove ecosystem management. This study evaluated various geospatial techniques for detecting healthy mangroves on the eastern coast of Sri Lanka, including single spectral indices, supervised/unsupervised classification, and developed methods using Landsat data. The use of medium-resolution satellite data and the uniqueness of the mangrove ecosystem are generally involved in discriminating healthy mangroves from non-mangrove areas. This study focused on detecting degraded narrow patches of mangroves on the Eastern coast of Sri Lanka using Landsat 8 remote sensing data and five vegetation indices. The accuracy of the results was assessed using randomly generated points. The study used ArcGIS Desktop software for processing, analyzing, and integrating spatial data to meet the research objectives. The mangroves were detected using Landsat 8 OLI satellite images from 2018 and 2021. The results showed high overestimation/underestimation and misclassification of mangroves, thus applying Mangrove Quality Index (MQI). Findings of MQI provide insights into overall mangrove health and identify three degradation classes of mangroves on the Eastern coast of Sri Lanka. The application of MQI in well-developed and degraded mangrove ecosystems merits further investigations, which provide reliable information for conservation priorities.
The SAVI Learning Model and the 21st Century Skills: Developing Critical Thinking, Collaboration, and Creativity in Students Vocational High School Taufiq Natsir; A. Ramli Rasyid; Samuel Akpan Bassey
International Journal of Environment, Engineering and Education Vol 5 No 1 (2023)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v5i1.96

Abstract

The use of the SAVI learning model offers a more effective alternative in improving student learning outcomes by understanding individual learning preferences and providing learning strategies that follow the objectives of this study, namely to evaluate the use of the SAVI learning model for vocational high school students. The research approach used in this study is quantitative, using numbers and statistical analysis. The research design used was pre-experimental in a one-group pretest-posttest design. The present research study focused on the student population enrolled in vocational high schools in Makassar, Indonesia. Purposive sampling was used to select the most suitable sample for achieving the research objectives. The sample size consisted of 30 students, 25 of whom were male and five females. The SPSS Program enters data, performs statistical analysis, and visualizes the research results. The hypothesis test is tested at a significance level of 5% or 0.05. The results of testing the hypothesis using the SPSS application with the paired sample t-test data analysis technique obtained a significance of 0.000 where 0.000 < 0.05, which means that H0 is rejected and H1 is accepted. The analysis results prove that student learning outcomes (post-test) have increased compared to (pre-test). The SAVI learning model is more efficacious than traditional learning approaches, as it affords students a more engaging, enjoyable, and enduring educational encounter. It can serve as a pragmatic substitute for enhancing the caliber of education and students' academic achievements.
Analysis of Land Surface Temperature Distribution in Response to Land Use Land Cover Change in Agroforestry Dominated Area, Gedeo Zone, Southern Ethiopia Wendwesen Taddesse Sahile; Gashaw Kibret Goshem; Seid Ali Shifaw; Muh. Rais Abidin
International Journal of Environment, Engineering and Education Vol 5 No 1 (2023)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v5i1.98

Abstract

This study examined LST distribution in Ethiopia's agroforestry-dominated Gedeo Zone due to Land Use Land Cover change. For 2005, 2011, 2017, and 2022, 10 m Sentinel 2A and 30 m Landsat images were used to extract and map LST and LULC distribution. The DOS1 method corrected atmospheric errors in all satellite images. LULC change was detected using SVM image classification. The study result revealed that the Agroforestry and Built-up coverage has increased by 1520 sq. km and 2600 sq. km, respectively, from 2005 to 2022. The Bare Land and Farm Land coverage decreased by 1554 sq. km and 2565 sq. km, respectively, in the same period. The LST result has shown that there has been a remarkable variation in the spatial pattern of the LST between 2005 and 2022. The average LST in Agroforestry, Bare Land, Farm Land, and Built-up area has progressively increased over the years, from 19.6°C, 26.0°C, 20.2°C, and 25.58°C in 2005 to 25°C, 32.16°C, 28.23°C, and 30.62 °C in 2022, respectively. While in 2005, the maximum recorded LST did not exceed 37.3°C, by 2022, it had increased by close to 3°C, reaching 40.6°C. The overall result revealed that the average LST in °C has increased from 2005 to 2022. From the result, it was concluded that agroforestry had contributed a lot to LST distribution. LST may not depend on the local LULC change only; other factors like urbanization and global warming could play a significant role in changing LST locally and globally.
Classification of Sentiment Analysis and Community Opinion Modeling Topics for Application of ICT in Government Operations Andi Akram Nur Risal; Fathahillah Fathahillah; Dwi Rezky Anandari Sulaiman
International Journal of Environment, Engineering and Education Vol 5 No 1 (2023)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v5i1.99

Abstract

Utilizing information systems is very useful in the current era. Digitizing administration in the Village is beneficial in the service process to the public. This is seen as a change in service that can make it easier or more difficult for the people of Sanrobone Village to take care of administration at the village office. This study aims to analyze public opinion regarding the use of e-government, predict public opinion regarding the use of e-government, and analyze modeling topics related to the use of e-government. This research applies a text mining algorithm with a sentiment analysis method to see positive, negative, and neutral public perceptions and also uses topic modeling to get the most frequently appearing topics in the data. Stages in this study include Data Collection, Text Pre-processing, Sentiment Analysis, Topic Modelling, Classification, and Evaluation. The results obtained are the ten words that appear most often in the responses of the Village community: easy 122, help 96, village 80, accessed 80, letter 80, permit 77, resident 73, manage 60, service 52, and the person with 52 words. The sentiment analysis is positive, with 411 opinions, 37 negative opinions, and 152 neutral opinions. Finally, the performance of the Nave Bayes algorithm in predicting classification results is excellent, with an accuracy rate of 98 percent.

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