cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Juhari
Contact Email
juhari@uin-malang.ac.id
Phone
+6281336397956
Journal Mail Official
cauchy@uin-malang.ac.id
Editorial Address
Jalan Gajayana 50 Malang, Jawa Timur, Indonesia 65144 Faximile (+62) 341 558933
Location
Kota malang,
Jawa timur
INDONESIA
CAUCHY: Jurnal Matematika Murni dan Aplikasi
Published by Universitas Islam Negeri Maulana Malik Ibrahim Malang
ISSN : 20860382     EISSN : 24773344     DOI : 10.18860
Core Subject : Education,
Mathematics
Jurnal CAUCHY secara berkala terbit dua (2) kali dalam setahun. Redaksi menerima tulisan ilmiah hasil penelitian, kajian kepustakaan, analisis dan pemecahan permasalahan di bidang Matematika (Aljabar, Analisis, Statistika, Komputasi, dan Terapan). Naskah yang diterima akan dikilas (review) oleh Mitra Bestari (reviewer) untuk dinilai substansi kelayakan naskah. Redaksi berhak mengedit naskah sejauh tidak mengubah substansi inti, hal ini dimaksudkan untuk keseragaman format dan gaya penulisan.
Arjuna Subject : -
Articles 476 Documents
 44   45   46   47   48 
Short- and Long-Run Relationships Between Observed and Model 1 Output Rainfall Data in Majalengka Regency Nurdiati, Sri; Najib, Mohamad Khoirun; Rahmaisty, Fathia
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.40902

Abstract

This study examines the short-run and long-run relationships between observed monthly rainfall and CMIP6 climate model projections in Majalengka Regency, Indonesia. Monthly rainfall observations from the BMKG Kertajati Meteorological Station are analyzed using the Autoregressive Distributed Lag (ARDL) framework, which enables simultaneous assessment of short-term dynamics and long-term equilibrium relationships. Stationarity and cointegration are evaluated using the Augmented Dickey–Fuller test and ARDL bounds testing, respectively, while model performance is assessed through out-of-sample validation for the period 2015–2017 under three CMIP6 emission scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. The results indicate a positive and statistically significant short-run relationship between observed rainfall and CMIP6 projections across all scenarios, suggesting that climate models capture local scale monthly rainfall variability reasonably well. In contrast, the long-run relationship is weak and negative, highlighting limitations in representing long-term local rainfall dynamics. Model performance is highest under the low-emission SSP1-2.6 scenario and decreases under higher-emission scenarios. These findings suggest that CMIP6 outputs are more reliable for short-term rainfall analysis than for long-term local assessments without bias correction or downscaling.
A Review of Pompeiu-Hausdorff Metric Differentiability and Its Relation to Generalized Hukuhara Differentiability Putra, William Surya; Muslikh, Mohamad
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37820

Abstract

The Pompeiu-Hausdorff distance/Pompeiu-Hausdorff metric is a concept in analysis that measures the distance between two subsets of a metric space, one of its important applications being the Hausdorff metric differentiability of set-valued functions . This article reviews the definition and properties of Pompeiu-Hausdorff distance differentiability on the space of compact and convex subsets of the Euclidean space with dimension n. We also present concepts about the generalized Hukuhara difference and its differentiability. By studying both topics, we discuss the established relationship between Pompeiu-Hausdorff metric differentiability and generalized Hukuhara differentiability
Modification of Norms on the Sequence Space ℓp Salsabilla, Rikha Syahda; Idris, Mochammad
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37178

Abstract

In this article, we explore sequence spaces by introducing a newly defined norm. We construct the Orlicz sequence space and demonstrate that the norm in this space is equivalent to the norm in the ℓp space. As a result, the fundamental properties of the ℓp space are carried over to the Orlicz sequence space through the equivalence of norms. One significant implication of this result is that Hölder's inequality, which holds in ℓp spaces, can also be applied to the Orlicz sequence space with different positive constants.
Comparison Of Vector Autoregressive and Multiresponse Fourier Series for Cryptocurrency Prediction Post-Bitcoin Halving 2024 Amelia, Dita; Rahayu, Rizky Dwi Kurnia; Syahputra, Bimo Okta
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37720

Abstract

This study examines cryptocurrency price modeling after the 2024 Bitcoin halving by comparing two multivariate forecasting methods: the Vector Autoregressive (VAR) model and the cosine-based Multiresponse Fourier Series Estimator. The research aligns with SDGs 8 on Decent Work and Economic Growth, as accurate forecasting in digital asset markets can support financial stability and informed investment decisions. The novelty of this study lies in applying a Fourier-based multiresponse model for post-halving cryptocurrency prediction, an approach that remains limited in existing literature. The dataset consists of daily prices of Bitcoin, Ethereum, and Litecoin from April 2024 to August 2025 (t=480), obtained from investing.com, with 90% for data training and 10% for data testing. Prior to modeling, the Bartlett test produced p-value 0.000α, indicating significant correlations among cryptocurrencies, thereby validating the use of simultaneous multivariate analysis. The results show that the Fourier Series Estimator with five oscillation parameters (k=5) provides superior predictive accuracy, achieving a MAPE of 3.768%, compared to the VAR model’s MAPE of 8.503%. These findings demonstrate that the Fourier estimator more effectively captures cyclical and nonlinear patterns in digital assets and offers valuable contributions to financial statistics, providing practical insights for investors and policymakers in the highly volatile cryptocurrency market.
A Damped Hessian-Free Newton--Conjugate Gradient Method for Weighted Multiclass Neural Classification Irawan, Andy; Abidin, Zainal; Jamhuri, Mohammad
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.40243

Abstract

This study presents a deterministic damped Hessian-free Newton--CG method for weighted multiclass neural classification. The method is built from a weighted categorical cross-entropy objective, a damped local quadratic model, and a matrix-free curvature representation through Hessian--vector products. The search direction is computed by an inexact conjugate gradient solve, while Armijo backtracking and adaptive damping are used to improve stability. The method is implemented for the classification of academic predicate categories using preprocessed student data with mixed categorical and numerical features. Its numerical behavior is compared with SGD with momentum, RMSProp, and Adam under the same loss, initialization, and network architecture. The proposed method is computationally feasible, attains the best overall weighted test-set performance among the compared methods, and exhibits a distinct optimization trajectory driven by curvature-informed updates. These results show that a damped Hessian-free formulation provides a mathematically transparent, reproducible, and practically competitive framework for second-order optimization in multiclass neural classification.
Analysis of Color Space Transformations on MobileNetV2 Performance for Image Classification Vironica, Sherlyn; Surono, Sugiyarto; Thobirin, Aris
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.41353

Abstract

This study analyzes the effect of color space transformation on the performance of MobileNetV2 for rice leaf disease classification using RGB, HSV, CIELab, and their combinations. The RGB color space is used as the baseline representation, while HSV and CIELab are applied to provide alternative representations of color information. In addition, a dual-stream architecture is employed to combine different color spaces for feature extraction. The results show that the choice of color space influences classification performance. In the single color-space scenario, RGB achieves the highest accuracy of 91.42%, while in the combined scenario, the RGB+CIELab model achieves the best performance with an accuracy of 97.00%. These findings suggest that the use of multiple color spaces can provide richer feature representations and may improve classification performance. Furthermore, the results indicate that optimizing input representation plays an important role in improving model performance, particularly when using lightweight architectures such as MobileNetV2. This study shows that color space transformation can improve classification performance in the rice leaf disease dataset used in this study.

Page 48 of 48 | Total Record : 476

 44   45   46   47   48 

Filter by Year

2009 2026


Reset
Filter By Issues
All Issue Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 9, No 2 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 9, No 1 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 8, No 2 (2023): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 7, No 4 (2023): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 7, No 2 (2022): CAUCHY: Jurnal Matematika Murni dan Aplikasi (May 2022) (Issue in Progress) Vol 7, No 3 (2022): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 7, No 2 (2022): CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 7, No 1 (2021): CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 6, No 4 (2021): CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 6, No 3 (2020): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 6, No 2 (2020): CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 6, No 1 (2019): CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 5, No 4 (2019): CAUCHY Vol 5, No 4 (2019): CAUCHY Vol 5, No 3 (2018): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 5, No 3 (2018): CAUCHY Vol 5, No 2 (2018): CAUCHY Vol 5, No 1 (2017): CAUCHY Vol 4, No 4 (2017): CAUCHY Vol 4, No 3 (2016): CAUCHY Vol 4, No 2 (2016): CAUCHY Vol 4, No 1 (2015): CAUCHY Vol 3, No 4 (2015): CAUCHY Vol 3, No 3 (2014): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 3, No 3 (2014): CAUCHY Vol 3, No 2 (2014): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI Vol 3, No 2 (2014): CAUCHY Vol 3, No 1 (2013): Cauchy Vol 3, No 1 (2013): CAUCHY Vol 2, No 4 (2013): CAUCHY Vol 2, No 3 (2012): CAUCHY Vol 2, No 2 (2012): CAUCHY Vol 2, No 1 (2011): CAUCHY Vol 1, No 4 (2011): CAUCHY Vol 1, No 2 (2010): CAUCHY Vol 1, No 1 (2009): CAUCHY More Issue