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All Journal Al-Jabar : Jurnal Pendidikan Matematika Equiva
Ziaulhaq, Muhammad Haikal
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Computer Science & IT Education Mathematics

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Pengoptimalan Biaya Distribusi Bahan Material Keramik Menggunakan Metode Least Cost Ziaulhaq, Muhammad Haikal; Affandi, Aisyah; Aritonang, Sovian
Equiva Journal Vol 2 No 2 (2024):
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

PT. Indah Bangunan is a ceramic distributor company located in Palu City. This study aims to determine the optimal transportation costs for ceramic distribution to improve operational efficiency. The steps taken include developing a transportation model based on actual data, determining an initial solution using the Least Cost method, and refining the solution with the Stepping Stone method to achieve optimal results. Based on the analysis, the initial solution obtained using the Least Cost method produced the same results as the optimal solution obtained through the Stepping Stone method, demonstrating that this approach is effective in minimizing transportation costs.
Analisis Komprehensif Pengaruh Faktor Sosial Terhadap Jumlah Kematian Pasien HIV : Analisis Regresi Poissson Dan Regresi Binomial Negatif Ziaulhaq, Muhammad Haikal; Affandi, Aisyah
Equiva Journal Vol 2 No 2 (2024):
Publisher : Jurusan Matematika dan Teknologi Informasi

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The Human Immunodeficiency Virus (HIV) poses a significant challenge for every country and remains one of the primary issues in global health, requiring serious attention. HIV is a virus that attacks the human immune system, weakening the body’s ability to combat infections. This study aims to analyze the influence of various social factors on the mortality rate of HIV patients in Indonesia using Poisson regression and Negative Binomial regression. These models are chosen because they are well-suited for count data, such as mortality rates. The research data includes information on the number of HIV-related deaths across various provinces in Indonesia, with social variables as predictors, such as population density, the percentage of elderly population, inadequate sanitation access, education levels, and unemployment rates.
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.
Co-Authors Abdurrazzaq, Achmad Affandi, Aisyah Aritonang, Sovian Azzahra, Army Kanaya Harits, Jiyaad Muhamad Sugiarto, Wahyu Nurmedica