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INDONESIA
'ADALAH
Published by Universitas Islam Negeri Syarif Hidayatullah Jakarta
ISSN : -     EISSN : -     DOI : -
Core Subject : Social,
Law, Crime, Criminology & Criminal Justice
ADALAH is “one of the ten most influential law journals in the world, based on research influence and impact factors,” in the Journal Citation Reports. ADALAH also publishes student-written work.Adalah publishes pieces on recent developments in law and reviews of new books in the field. Past student work has been awarded the International Law Students Association’s Francis Deak Prize for the top student-written article published in a student-edited international law journal.
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Articles 2 Documents
 1 
Search results for , issue "Vol 9, No 6 (2025)" : 2 Documents clear
Dynamics of CO2 Emission Flux from the Vegetation Canopy Percentage in the Suropati City Park Ecosystem Elvira, Ade Irma; Ramadhani, Muhammad Reza; Patria, Mufti Petala; Nurdin, Erwin; Vasenev, Ivan Ivanovich
ADALAH Vol 9, No 6 (2025)
Publisher : UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/adalah.v9i6.44821

Abstract

In recent years, fossil fuel usage and industrial activities have significantly increased, leading to higher greenhouse gas emissions and impacting global temperature, contributing to global warming and climate change. The carbon footprint measures these emissions through carbon flux rates, influenced by climate conditions, soil and water uptake, organic matter, and microbial activities. The experiment used a gas analyzer and gas chromatograph to measure samples under three conditions. The highest average flux rate was in fully enclosed vegetation (4.04 g CO2/m²/day), followed by not enclosed vegetation (4.01 g CO2/m²/day), and the lowest was 3.91 g CO2/m²/day. Results indicate that vegetation and urban parks reduce CO2 emission fluxes, with each area's vegetation state affecting soil and air temperature, pH content, and soil moisture. However, many aspects such as soil type and climate cognition can influence fluctuation of carbon fluxes in each condition.
Retinal Blood Vessel Segmentation Based on Encoder and Decoder Networks Using Weighted Cross Entropy Loss Function Qomariah, Dinial Utami Nurul; Tjandrasa, Handayani; Elvira, Ade Irma
ADALAH Vol 9, No 6 (2025)
Publisher : UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/adalah.v9i6.44857

Abstract

Retinal disease that has a major impact on human vision is diabetic retinopathy. Diabetic retinopathy is a disease caused by advanced diabetic mellitus. Early detection of the disease is very importance. An automated system that can recognize retinal blood vessel abnormalities is very useful for providing quick information to prevent further damage to the retina. In this study, we propose an automated system for segmenting the blood vessels in retinal fundus images using semantic segmentation based on pre-trained from VGG transfer learning and using median frequency balancing weights for the cross entropy loss function. The median frequency weights are to balance the importance of blood vessel and background pixels to get more accurate training results. The integration of encoder and decoder networks utilizing VGG transfer learning and semantic segmentation can segment retinal blood vessels with a sensitivity value of 85.48% using the DRIVE and STARE database.

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