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INDONESIA
Zero : Jurnal Sains, Matematika, dan Terapan
Published by Universitas Islam Negeri Sumatera Utara
ISSN : 2580569X     EISSN : 25805754     DOI : 10.30829
Core Subject : Science, Education, Agriculture,
Agriculture, Biological Sciences & Forestry Chemistry Mathematics Physics
Arjuna Subject : -
Articles 222 Documents
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ResNet-18 Citrus Classification with Augmentation: Peel Color Associations with pH and Vitamin C Dewi, Titin Afrina Priani; Surono, Sugiyarto; Thobirin, Aris
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i3.27199

Abstract

Limes and lemons are widely consumed, but field quality assessment is often subjective. This study built a ResNet-18 citrus classifier using transfer learning and data augmentation, and evaluated it with stratified 5-fold cross-validation on 80 images (40 limes, 40 lemons). All analyses were conducted per fold to reduce optimistic bias. The model reached 98.75% mean validation accuracy, misclassifying one lime image while correctly recognizing all lemons. For interpretation, peel regions were quantified using NDYI and CIELab (L*, a*, b*), and related to pH and vitamin C using Spearman correlation. Uncertainty was quantified with bootstrap-based 95% confidence intervals for each correlation. Peel color features were more consistently associated with pH (especially in limes), whereas correlations with vitamin C were weak and non-significant for both fruits. Results indicate strong performance under controlled imaging, but using peel color as a vitamin C proxy requires broader data and external validation across cameras and lighting.
Determinants of Fishermen and Fish Farmers Exchange Rate: A Panel Data Regression Approach Handayani, Vitri Aprilla; Sabarinsyah, Sabarinsyah; Arrafi, Adamsyam; Sunarsono, Hery; Anggraeni, Andini Setyo
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i3.26642

Abstract

This study examines the impact of key economic variables on the exchange rate of fishermen and fish farmers using monthly panel data by subsector/province for the period 2022-2024 sourced from BPS. The price index received by farmers (Y) is explicitly defined as the dependent variable. A panel data regression model was employed using three independent variables: Farmers' Paid Price Index ( ), the Fishermen and Fish Farmers Exchange Rate ( ), and the Fishermen's Business Exchange Rate ( ). The results showed that both and had a significant positive effect (α < 0.05) on Y, with exhibiting a stronger influence than . These findings suggest that policies aimed at controlling input prices and stabilizing exchange rates can effectively improve the welfare of fishermen and fish farmers. Furthermore, the regression model developed in this study provides a practical analytical framework for supporting data-driven policy decisions related to price dynamics and welfare enhancement in the fisheries sector.

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