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All Journal The Journal of Experimental Life Sciences (JELS) Jurnal Sosial Ekonomi Pertanian CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Mahasiswa Statistik Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer JURNAL ILMIAH MATEMATIKA DAN TERAPAN PERFORMA : Media Ilmiah Teknik Industri BAREKENG: Jurnal Ilmu Matematika dan Terapan Proceeding Simposium Nasional Kelautan dan Perikanan JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Pertanian Agros ComTech: Computer, Mathematics and Engineering Applications Inferensi MATHunesa: Jurnal Ilmiah Matematika Pakem : Jurnal Pengabdian Kepada Masyarakat Prosiding Seminar Nasional Official Statistics ABDI UNISAP: Jurnal Pengabdian Kepada Masyarakat

Atiek Iriany

Universitas Brawijaya

Author-ID : 288480

Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Other

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Articles

Title

GSTAR-X-SUR Model with Neural Network Approach on Residuals Rosyida, Diana; Iiriany, Atiek; Nurjannah, Nurjannah
CAUCHY Vol 5, No 4 (2019): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

One of the models that combine time and inter-location elements is Generalized Space Time Autoregressive (GSTAR) model. GSTAR model involving exogenous variables is GSTARX model. The exogenous variables which are used in GSTAR model can be both metrical and non-metrical data. Exogenous variable that can be applied into the forecasting of precipitation is non-metrical data which is in a form of precipitation intensity of a certain location. Currently, precipitation possesses patterns and characteristics difficult to identify, and thus can be interpreted as non-linear phenomenon. Non-linear model which is much developed now is neural network. Parameter estimation method employed is Seemingly Unrelated Regression (SUR) model approach, which can solve the correlation between residual models. This current research employed GSTARX-SUR modelling with neural network approach on residuals. The data used in this research were the records of 10-day precipitations in four regions in West Java, namely Cisondari, Lembang, Cianjur, and Gunung Mas, from 2005 to 2015. The GSTARX-SUR NN modelling resulted in precipitation deviation average of the forecast and the actual data at 4.1385 mm. This means that this model can be used as an alternative in forecasting precipitation.

Cross-Covariance Weight of GSTAR-SUR Model for Rainfall Forecasting in Agricultural Areas Sulistyono, Agus Dwi; Hartawati, Hartawati; Suryawardhani, Ni Wayan; Iriany, Atiek; Iriany, Aniek
CAUCHY Vol 6, No 2 (2020): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

The use of location weights on the formation of the spatio-temporalÂ model contributes to the accuracy of the model formed. The location weights that are often used include uniform location weight, inverse distance, and cross-correlation normalization. The weight of the location considers the proximity between locations. For data that has a high level of variability, the use of the location weights mentioned above is less relevant. This research was conducted with the aim of obtaining a weighting method that is more suitable for data with high variability. This research was conducted using secondary data derived from 10 daily rainfall data obtained from BMKG Karangploso. The data period used was January 2008 to December 2018. The points of the rain posts studied included the rain post of the Blimbing, Karangploso, Singosari, Dau, and Wagir regions. Based on the results of the research forecasting model obtained is the GSTAR ((1), 1,2,3,12,36) -SUR model. The cross-covariance model produces a better level of accuracy in terms of lower RMSE values and higher R2 values, especially for Karangploso, Dau, and Wagir areas.

Spatio Temporal Modelling for Government Policy the COVID-19 Pandemic in East Java Iriany, Atiek; Aini, Novi Nur; Sulistyono, Agus Dwi
CAUCHY Vol 6, No 4 (2021): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v6i4.10639

COVID-19 has cursorily spread globally. Just in four months, its status altered into a pandemic. In Indonesia, the virus epicenter is identified in Java. The first positive case was identified in West Java and later spread in all Java. The Large-scale Social Restrictions are seemingly inefficient as the SARS-CoV-2 transmission remains. As such, the government is struggling to find anticipatory policies and steps best to mitigate the transmission. In this particular article, we used a Spatio-temporal model method for the total COVID-19 cases in Java and forecasted the total cases for the next 14 days, allowing the stakeholders to make more effective policies. The data we were using were the daily data of the cumulative number of COVID-19 cases taken from www.covid19.go.id. Data modelling was conducted using a generalized spatio-temporal autoregressive model. The model acquired to model the COVID-19 cases in Java was the GSTAR(1)(1,0,0) model.

Integrating Path Analysis and Kendall’s Tau-based Principal Component Analysis to Identify Determinants of Child Health Alim, Viky Iqbal Azizul; Iriany, Atiek; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun; Utomo, Candra Rezzining Wulat Sariro Weni
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): 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.v10i2.31156

This study develops a latent variable path analysis model using a Mixed-Scale Principal Component Analysis (PCA) approach based on Kendall’s Tau correlation to identify key determinants of child health in Batu City, Indonesia. Primary data were collected from 100 mothers with children under five years old through questionnaires. The variables examined include Family Demographics, Nutritional Consumption, and Child Health Condition, each measured using mixed-scale indicators (ordinal and numerical). Kendall’s Tau-based PCA was applied to reduce data dimensionality and construct latent variables, which were then integrated into a path analysis model. The results show that maternal age is the most dominant indicator in shaping the Family Demographics construct, while balanced nutritional food is the strongest indicator forming the Nutritional Consumption construct. Path analysis further reveals that Family Demographics significantly affect Child Health Condition both directly and indirectly through Nutritional Consumption, with a coefficient of determination of 77.62\%. These findings underscore the critical role of demographic and nutritional factors in determining child health outcomes and highlight the methodological advantage of Kendall’s Tau-based mixed-scale PCA for analyzing heterogeneous indicator data within a structural path framework.

Structural Equation Modeling Semiparametric Truncated Spline in Banking Credit Risk Behavior Models Amanda, Devi Veda; Iriany, Atiek; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): 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.v10i1.29769

Housing is one of the primary needs for every individual. Along with the increasing population growth in Indonesia, the need for housing has also experienced a significant surge. This study aims to analyze the effect of customer attitudes on compliance behavior, fear of paying late, and timeliness of payment on Home Ownership Credit (KPR) customers at X Bank. Using a semiparametric Structural Equation Modeling (SEM) approach, this study examines the relationship between these variables to provide a deeper understanding of the factors that influence customer payment behavior. The data used in this study are primary data obtained through questionnaires distributed to 100 Bank X mortgage customers. The results of the analysis show that there is a significant influence between customer attitudes (X1) on obedient payment behavior (Y1) and fear of paying late (Y2), as well as timeliness of payment (Y3). The estimated coefficients obtained show a positive relationship between compliance behavior and timeliness of payment, and a negative relationship between fear of paying late and timeliness of payment, with a p-value 0.001 indicating statistical significance. This finding indicates that good customer attitudes can improve payment timeliness, while poor attitudes can lead to fear of paying late, which in turn can affect payment timeliness.

Co-Authors A. Fahmi Indrayani Achmad Efendi Agus Dwi Sulistyono, Agus Dwi Alim, Viky Iqbal Azizul Amanda, Devi Veda Aniek Iriany Arditama Putra Rochmanullah Arianto, Danang Arifin Noor Sugiharto Aris Subagiyo Asaliontin, Lisa Ayu Aisyah Ashari Bambang Dwi Argo Bestari Archita Safitri Budi Astuti, Ani Cecep Kusmana Chairunissa, Abela Danang Ariyanto Darmanto Darmanto David Forgenie Dewi, Anggi Seftia Dhanny Septimawan Sutopo Eni Sumarminingsih Faddli Lindra Wibowo Fernandes, Adji Fernandes, Adji Achmad Rinaldo Firdaus, Cahyani Jannah Fudianita, Citra Hamdan, Rosita Haneinanda Junianto, Fachira Hartawati, Hartawati Henny Pramoedyo Henny Pramoedyo Iwan Setiawan Khoiril Anam, Khoiril Kusdarwati, Heni Maghfiro, Maulidya Maghfiro, Maulidya Maisaroh, Ulfah Marhen Andan Prasetyo Mellysa Isnaini Muhamad Firdaus Muhamad Ridwan Ni Wayan Surya Wardhani NI WAYAN SURYA WARDHANI Nikmatul Khoiriyah Novi Nur Aini Novi Nur Aini, Novi Nur Nugroho, Arief Budi Nugroho, Salma Fitri Ola, Petrus Kanisius Pramaningrum, Dea Saraswati Putra, Arditama Putri, Henida Ratna Ayu Rahma Fitriani Rinaldo Fernandes, Adji Achmad Riza, Sativandi Rosyida, Diana Rudiat Sekarsari, Cindy Sepriadi, Hanifa Solimun Solimun Solimun Solimun, Solimun Suci Astutik Sugiarto S Suryawardhani, Ni Wayan Sutopo, Dhanny Septimawan Ullah, Mohammad Ohid Utomo, Candra Rezzining Wulat Sariro Weni Waego Hadi Nugroho Wardhani, Ni Wayan Surya Wigbertus Ngabu Yuliana, Mila

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