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All Journal Coreid Journal Tafani
Firdaus, Muhammad Rihap
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Implementasi Teknik Ecoprint Sebagai Strategi Peningkatan Kesadaran Lingkungan pada Siswa Sekolah Dasar Nurpazriah, Mainawati; Firdaus, Muhammad Rihap; Fakhira, Nisrina Lulu; Nurjanah, Tiya
TAFANI: Jurnal Pengabdian Masyarakat Vol 4 No 1 (2025): TAFANI
Publisher : LP2M UIN Sultan Aji Muhammad Idris Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21093/tafani.v4i1.9175

Abstract

The 2024 Community Service Program (KKN) used the Sisdamas model (Community Empowerment-Based Community Service), with the theme "Implementation of Ecoprint Techniques as a Strategy to Increase Environmental Awareness Among Elementary School Students." The author designed several programs to support this theme, including: (1) assessing the community's and students' awareness of utilizing natural materials, (2) enhancing children's creativity in using natural resources, (3) socializing the ecoprint technique to students, and (4) facilitating free ecoprint workshops. This activity aimed to raise environmental awareness among students at SD Negeri Buah Batu through a participatory approach. The program was implemented on August 15, 2024, involving 5th-grade students actively in every phase, from the introduction of the ecoprint concept to hands-on practice using the pounding technique with leaves as the primary material. The results showed an increase in students' understanding and skills in using natural materials to create eco-friendly artistic products while also reinforcing their awareness of environmental preservation. This program proved effective in integrating environmental education values with creative, hands-on practices, encouraging students to care more about the environment through enjoyable and meaningful activities.
GreenEye: Plant Classification Using MobileNet V2 Hamami, Muhammad Syamil; Firdaus, Muhammad Rihap; Pasha, Pancadrya Yashod; Firdaus, Muhammad Raihan; Sugiarto, Awang
CoreID Journal Vol. 3 No. 3 (2025): November 2025
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v3i3.138

Abstract

Biodiversity in Indonesia includes more than 30,000 species of plantsand mushrooms, but public knowledge about these plants is still limited. The research aims to develop a mobile application called GreenEye that uses machine learning to detect and classify plants based on images. The model used is based on the MobileNet V2 architecture, a type of Convolutional Neural Network (CNN) designed for high-efficiency image classification tasks. Research data collected from PlantNet and Google Images, consisting of 2800 images covering seven plant species: Ananas comosus, Artocarpus heterophyllus, Carica papaya, Cocos nucifera, Musa spp, Nephelium lappaceum, and Salacca zalacca. Each species is categorized into four plant parts: fruit, flower, leaf, and habit. (habitus). This data is then processed through various preprocessing stages such as data cleaning, format conversion, resizing, cropping, and image augmentation. The results showed that the MobileNet V2 model was able to classify parts of plants with high accuracy, especially on fruits and leaves with accurations above 90%. However, the accuration was slightly lower for flowers and habits, which is about 70%. Classification errors occurred mainly in species with high visual similarities. To improve the performance of the model, it is recommended that further research increase the quantity and diversity of datasets.
Co-Authors Fakhira, Nisrina Lulu Firdaus, Muhammad Raihan Hamami, Muhammad Syamil Nurjanah, Tiya Nurpazriah, Mainawati Pasha, Pancadrya Yashod Pasha, Pancadrya Yashoda Sugiarto, Awang