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All Journal Jurnal Teknik Informatika (JUTIF) Sejahtera: Jurnal Inspirasi Mengabdi Untuk Negeri Pelayanan Unggulan: Jurnal Pengabdian Masyarakat Terapan
Sinta Bella Agustina
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Social Sciences

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Taman Kota Punti Kayu sebagai Ruang Hijau Kota : Edukasi Manfaat bagi Kesehatan Fisik dan Mental Bagi Masyarakat Kota Palembang Sinta Bella Agustina; M Bambang Purwanto
Sejahtera: Jurnal Inspirasi Mengabdi Untuk Negeri Vol. 4 No. 1 (2025): Sejahtera: Jurnal Inspirasi Mengabdi Untuk Negeri
Publisher : Universitas Maritim AMNI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/sejahtera.v4i1.3090

Abstract

Punti Kayu City Park in Palembang has a strategic role as the lungs of the city and an ecotourism-based economic center for the surrounding community. However, challenges such as suboptimal environmental management, low public awareness of park conservation, and economic utilization that has not been maximized are still obstacles. This community service activity aims to improve the sustainability of the park through environmental education, empowerment of local MSMEs, and revitalization of park facilities. The methods used include initial observation, coordination with related parties, workshops and seminars, creative economy training, and 3R-based reforestation and waste management programs (Reduce, Reuse, Recycle). The results of the activity showed an increase in public awareness of the importance of city parks, increasing the skills of MSME actors in digital marketing, and improving park infrastructure to support educational tourism. The implication of this program is the formation of a sustainable park management model based on community participation, which can be used as an example for other green areas. It is hoped that this program will continue through long-term mentoring and cross-sector collaboration so that the benefits are wider.
Pelatihan Dasar Analisis Data Menggunakan Google Colab dan Python Untuk Siswa SMA di Wilayah Saboking-king Palembang Sinta Bella Agustina; Sherly Malini; Ilsa Palingga Ninditama; Yike Diana Putri
Pelayanan Unggulan : Jurnal Pengabdian Masyarakat Terapan Vol. 2 No. 2 (2025): Mei : Pelayanan Unggulan : Jurnal Pengabdian Masyarakat Terapan
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/unggulan.v2i2.1397

Abstract

This training program is designed to strengthen digital literacy and basic skills in data analysis for high school students in the Saboking-king area, Palembang, by introducing the Python programming language and the use of Google Colab as a cloud-based programming platform. The approach applied is project-based learning and hands-on experience, which includes planning, implementation, and evaluation stages. Based on the implementation results, the majority of participants showed a good understanding of Python basics and successfully completed the mini-project assignments. The final evaluation revealed an increase in students' motivation and interest to explore programming further. The success of this program confirms that the learning methods and media used are able to support students' understanding of the basic concepts of data analysis. Similar activities are recommended to be implemented in other areas that have limited access to technology.
BLOOD VESSEL SEGMENTATION IN RETINAL IMAGES USING CONVOLUTIONAL NEURAL NETWORK VV-NET METHOD Sinta Bella Agustina; Erwin, Erwin; Desiani, Anita; Saputra, Tommy
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 1 (2024): JUTIF Volume 5, Number 1, February 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.1.1723

Abstract

The retina is susceptible to various diseases that can be fatal if not treated quickly. Image processing is currently very helpful for doctors to detect retinal diseases faster so that retinal diseases can be treated immediately. The first step in image processing is to improve the quality of retinal images affected by noise, aiming to increase accuracy in the process of segmentation and image extraction. accurate segmentation of retinal blood vessels is the first step in disease detection. The process of segmentation and analysis of retinal blood vessels has an important role in assisting medical professionals in identifying the severity of a disease. Image quality improvement steps in preprocessing use grayscale, median filter (denoising), and clahe. The method used for blood vessel segmentation is CNN VV-Net. Evaluation of the results of applying image quality enhancement and segmentation techniques using the VV-Net method was performed on the DRIVE, STARE, and CHASEDB_1 datasets at both stages, training and testing. The measurement results of blood vessel segmentation using the CNN VV-net method on the DRIVE dataset (accuracy 96.27%, sensitivity 84.38%, precission 75.95%, and jaccard score 66.28%), STARE dataset (accuracy 96.58%, sensitivity 82.78%, precission 76.73%, and jaccard score 65.38%), and CHASEDB_1 dataset (accuracy 97.04%, sensitivity 83.55%, precission 76.72%, and jaccard score 66.40%). From the three datasets used, the CHASEDB_1 dataset obtained better results than the DRIVE and STARE datasets.
Co-Authors Anita Desiani Erwin Erwin Ilsa Palingga Ninditama M Bambang Purwanto Saputra, Tommy Sherly Malini Yike Diana Putri