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All Journal Al-Jabar : Jurnal Pendidikan Matematika AKSIOMA : Jurnal Sains Ekonomi dan Edukasi
Harits, Jiyaad Muhamad
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

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Central tendency approach: A modified recursive filter for impulse noise removal in SAR and optical satellite images Sugiarto, Wahyu Nurmedica; Abdurrazzaq, Achmad; Azzahra, Army Kanaya; Harits, Jiyaad Muhamad; Ziaulhaq, Muhammad Haikal
Al-Jabar: Jurnal Pendidikan Matematika Vol 16 No 1 (2025): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v16i1.24244

Abstract

Puspose: This study aims to develop a modified Conditional Random Recursive Central Tendency Filter (CRRCTF) with a fixed-size window to effectively address the challenges of salt-and-pepper impulse noise, particularly under high noise density conditions, while preserving critical image details.Method: The proposed approach is divided into three main phases: (1) detecting noisy pixels through a statistical thresholding mechanism, (2) applying pre-edge filtering to retain edge details, and (3) restoring noisy pixels using a central tendency-based recursive process. Quantitative evaluations were conducted using standard image datasets as well as SAR and optical satellite images to assess the method's robustness.Findings: Experimental results demonstrate the superior performance of the proposed filter, achieving average PSNR and SSIM values of 31.88 and 0.896, respectively, across noise densities ranging from 10 percent to 90 percent. For satellite images, the method achieved PSNR and SSIM values of 29.37 and 0.8096 for SAR images and 19.51 and 0.605 for optical images at an 80 percent noise density.Significance: The proposed CRRCTF method outperforms existing denoising algorithms in terms of image restoration quality, particularly under extreme noise conditions, making it a valuable tool for image preprocessing applications in both research and practical scenarios.
Pemodelan Spasial: Analisis Pengaruh Indikator Sosio-Ekonomi terhadap Pesebaran Industri Kecil dan Mikro di Indonesia Harits, Jiyaad Muhamad; Argyanti, Talitha; Sianipar, Alexcandro Hibertus
AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Vol. 2 No. 2 (2025): AKSIOMA : Jurnal Sains, Ekonomi dan Edukasi
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/aksioma.v2i2.917

Abstract

This study examines the influence of socio-economic indicators on the distribution of small and micro industries (SMI) in Indonesia using spatial modelling. The research employs a Bayesian approach with the Integrated Nested Laplace Approximation (INLA) method to analyse spatial dependencies and heterogeneity across regions. Data were obtained from the Central Bureau of Statistics (BPS), focusing on variables such as Gross Domestic Product (GDP), unemployment rate, Human Development Index (HDI), and poverty rate. The results indicate that HDI has a significant positive impact on the distribution of SMI, suggesting that improvements in education, health, and living standards foster the growth of small and micro enterprises. Spatial analysis reveals regional variations in SMI potential, with Yogyakarta, Gorontalo, and Maluku showing the highest relative potential. Conversely, regions like Papua and West Papua face significant challenges due to infrastructure and socio-economic limitations. The findings provide valuable insights for policymakers to design targeted interventions to support SMI development in different regions.
Co-Authors Abdurrazzaq, Achmad Argyanti, Talitha Azzahra, Army Kanaya Sianipar, Alexcandro Hibertus Sugiarto, Wahyu Nurmedica Ziaulhaq, Muhammad Haikal