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Simulasi Pemodelan Jalur Semiparametrik Truncated Spline pada Kasus Perkembangan Cashless Society Pramaningrum, Dea Saraswati; Iriany, Atiek; Solimun; Budi Astuti, Ani; Haneinanda Junianto, Fachira; Fernandes, Adji
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 1: Februari 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20251218679

Abstract

Simulasi merupakan suatu proses merancang model matematis dari sistem yang nyata dengan cara melakukan percobaan terhadap model menggunakan komputer. Pada penelitian ini simulasi untuk memodelkan kasus perkembangan cashless society karena adanya keterbatasan ketersediaan data asli. Pemodelan simulasi dilakukan berdasarkan hasil analisis data asli yang menggunakan analisis jalur semiparametrik truncated spline. Data asli yang digunakan merupakan hasil kuesioner dengan responden sebanyak 100 nasabah bank pengguna m-banking. Perkembangan cashless society merupakan topik yang menarik untuk diteliti karena di Indonesia sendiri terdapat perubahan kebiasaan masyarakat dalam bertransaksi menggunakan non-tunai semenjak mewabahnya virus COVID-19. Hasil penelitian menunjukkan bahwa skenario model yang dapat dijadikan acuan untuk pengambilan keputusan terkait perkembangan cashless society adalah kombinasi model semiparametrik truncated spline berordo linier dengan dua titik knot di mana hanya terdapat satu hubungan nonparametrik pada model. Hasil penelitian dijadikan acuan oleh pemerintah terkhusus pihak bank untuk mendukung perkembangan cashless society.   Abstract Simulation is a process of designing a mathematical model of a real system by conducting experiments on the model using a computer. In this study, a simulation is used to model the case of the development of a cashless society due to the limited availability of original data. Simulation modeling was carried out based on the results of original data analysis using truncated spline semiparametric  path analysis.The original data used was the result of a questionnaire with respondents of 100 bank customers using m-banking. The development of a cashless society is an interesting topic to study because in Indonesia itself there has been a change in people's habits in transacting using non-cash since the outbreak of the COVID-19 virus. The results show that the model scenario that can be used as a reference for decision-making related to the development  of a cashless society is a combination of a semiparametric truncated spline model of a linear order with two knots where there is only one nonparametric relationship in the model. The results of the research are used as a reference by the government, especially the bank to support the development of a cashless society.
INTEGRATION OF HIERARCHICAL CLUSTER, SELF-ORGANIZING MAPS, AND ENSEMBLE CLUSTER WITH NAÏVE BAYES CLASSIFIER FOR GROUPING CABBAGE PRODUCTION IN INDONESIA Maghfiro, Maulidya; Wardhani, Ni Wayan Surya; Iriany, Atiek
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1057-1070

Abstract

The purpose of this study is to evaluate and compare different clustering techniques, including hierarchical cluster analysis (using complete linkage, average linkage, and single linkage methods), Self-Organizing Maps (SOM) clustering, and ensemble clustering, within the framework of integrated cluster analysis combined with Naïve Bayes analysis, specifically applied to cabbage production in Indonesia. The data utilized in this study are on cabbage production from various districts and cities in Indonesia, obtained from the 2023 publications of the Central Statistics Agency (BPS). The variables used in this study are cabbage harvest, cabbage production, area height, and rainfall. The data size used is 157 districts/cities in Indonesia. This research is a quantitative analysis employing integrated cluster analysis combined with Naïve Bayes. Cluster analysis is used to obtain classes in each district/city. Different clustering methods, including hierarchical clustering, Self-Organizing Map (SOM), and ensemble clustering, are compared to determine the best approach for grouping districts based on cabbage production. Naïve Bayes analysis is then used to classify cabbage production in Indonesia and identify the optimal clusters. This comparison aims to find the most effective clustering method for improving grouping accuracy and understanding cabbage production patterns. The best method for classifying cabbage production in Indonesia is the ensemble clustering approach integrated with Naïve Bayes, resulting in three distinct clusters: high, medium, and low production clusters.
DEVELOPMENT OF CLUSTER INTEGRATION WITH VARIAN BASED STRUCTURAL EQUATION MODELING TO MANAGE HETEROGENEOUS DATA Sepriadi, Hanifa; Iriany, Atiek; Solimun, Solimun; Rinaldo Fernandes, Adji Achmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1193-1202

Abstract

In the application of SEM to multivariate data, the individuals collected not only come from the same population but also from several groups (clusters). This data is heterogeneous. When SEM is applied to heterogeneous data, there will be a risk of bias in estimating equations in the measurement and structural models because there are differences between groups in the data. The purpose of this study is to overcome heterogeneous data in modeling cashless behavior with cluster using a dummy approach. This study used primary data from a survey in Bekasi City using a questionnaire with 100 respondents. Based on the study's results, it is known that using clustering in SEM can overcome heterogeneous data, which is indicated by the high coefficient of determination of 96.12%. Banks can use the results of this study to design products and services that are more in line with customer needs and preferences while encouraging financial inclusion in the digital era.
Structural Equation Modeling Semiparametric Truncated Spline in Banking Credit Risk Behavior Models Devi Veda Amanda; Atiek Iriany; Adji Achmad Rinaldo Fernandes; 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

Abstract

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.
A Spatiotemporal Analysis of Humidity Pattern in Bali using Space-Time Kriging with Seasonal Drift Nugroho, Salma Fitri; Fitriani, Rahma; Iriany, Atiek
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i3.30874

Abstract

Climate plays a vital role in framing the characteristics of tourist activity. Humidity reflects the amount of moisture in the air relative to the maximum it can hold at a specific temperature, it has a direct influences on perceived comfort levels. Bali, one of the most popular destinations renowned for its breathtaking natural beauty and varied landscapes. However, this island is currently served by only four climate observation stations which are insufficient to capture the humidity across the island. Therefore, this research aims to model humidity levels in Bali based on four observed locations at 2019-2023 using the space-time kriging with seasonal drift and predict humidity at unobserved locations. This approach was choosen due to the strong seasonal pattern exhibited in climate data, which leading to non-stationary. The space-time kriging method is applied to the residuals. The most effective model identified was the exponential-exponential-Gaussian (Exp-Exp-Gau) model using a sum-metric structure. This model provided the lowest RMSE of 2.1442. Humidity contour maps suggest a gradual decline in humidity levels over time across Bali. This trend may have significant impacts for both environmental quality and the tourism sector. Lower humidity levels could lead to increased discomfort for tourists and potentially reduce the attractiveness of the destination. Theoretically, the development of the kriging model enhances the accuracy of predictions, as shows by the low RMSE. Practically, these findings emphasize the importance of integrating climate considerations into sustainable tourism planning and management strategies based on the humidity information.
Kombinasi Analisis Bibliometrik dengan Latent Dirichlet Allocation sebagai Pemodelan Topik Cashless Society Sepriadi, Hanifa; Rudiat Sekarsari, Cindy; Iriany, Atiek; Solimun; Rinaldo Fernandes, Adji Achmad
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 2: April 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2012129244

Abstract

Era digitalisasi dan komputasi telah dimulai, ditandai dengan munculnya teknologi digital yang merasuk ke berbagai aspek kehidupan, sementara data juga terus berkembang menjadi big data.  Setelah era covid 19, metode pembayaran non-tunai berkembang sangat pesat, sehingga banyak penelitian mengenai cashless society. Tujuan dari penelitian ini adalah memodelkan topik-topik yang berkaitan dengan cashless society untuk mendapatkan variabel dan indikator yang terkait dengan menggunakan analisis bibliometrik dan latent dirichlet allocation. Data penelitian ini berasal dari artikel publikasi ilmiah dan hasil web scrapping di twitter yang bertemakan cashless society. Hasil penelitian menunjukkan bahwa terdapat 5 variabel dan 21 indikator yang berhubungan dengan cashless society.   Abstract The era of digitalization and computing has begun, marked by the emergence of digital technology which permeates various aspects of life, while data also continues to develop into big data.  After the covid 19 era, non-cash payment methods developed very rapidly, so there were many studies on the cashless society. The purpose of this research is to model topics related to the cashless society to obtain related variables and indicators using bibliometric analysis and latent dirichlet allocation. This research data comes from scientific publication articles and web scrapping results on twitter with the theme of cashless society. The results showed that there are 5 variables and 21 indicators related to cashless society.
CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVA Iriany, Atiek; Ngabu, Wigbertus; Arianto, Danang; Putra, Arditama
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (494.872 KB) | DOI: 10.30598/barekengvol17iss1pp0495-0504

Abstract

Geographically Weighted Regression Kriging (GWRK) is a special case of Geographically Weighted Regression (GWR) model, which is modeling with the effect of spatial autocorrelation on the GWR model error. The purpose of this research is to obtain a GWRK model between the factors that affect stunting density for each site viewed from the district center point in East Java Province and to make a prediction map based on the GWRK modeling. The data used was obtained from Basic Health Research (RISKESDAS) and the East Java Health Profile Book for 2021. The units of observation in this study were 38 districts in East Java.. Based on the GWR modeling results, it was found that the GWR model error contained spatial autocorrelation so that GWR model can be formed. From the GWRK modeling using stunting prevalence data in East Java in 2021, it was found that the GWR model was better than the global regression. Through prediction and prediction mapping formed from the GWR-Kriging modeling, it could be seen that stunting in regencies in East Java was evenly distributed . The interpolation map showed that the stunting forecasting values using the Kriging GWR interpolation ranged from 27% to 46%.
STRUCTURAL EQUATION MODELING MULTIGROUP INDIRECT EFFECTS ON BANK MORTGAGE PAYMENT TIMELINESS Maisaroh, Ulfah; Fernandes, Adji Achmad Rinaldo; Iriany, Atiek
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2359-2366

Abstract

Structural Equation Modeling (SEM) is a multivariate statistical method that is used to thoroughly explain the relationship between latent variables simultaneously. Until now, SEM continues to grow in research. This research was conducted to examine the indirect effect on the timeliness of paying bank mortgages with a multi-group moderation approach. Analysis to identify factors that influence the timeliness of paying bank mortgages is an important step for banks before extending credit to prospective customers. The data used in this research is secondary data from research grants from National Competitive Basic Research. The data scale used is the Likert scale for exogenous, mediating endogenous, and pure endogenous variables. While the moderating variable uses a dummy variable. The results of the study show that the indirect effect of Capacity and Capital on Pay on Time for Bank Mortgage customers has a significant effect, both on non-current collectibility status and current collectibility status. This is evidenced by the Sobel test value greater than (1.96) on the indirect effect test, and the p-value of the Wald test is smaller than (0.05) on the moderation indirect effect test. Mediator variable is able to increase the effect of exogenous variables on endogenous variable Customers with current collectibility status have a stronger influence on timely payments than customers with non-current collectibility status.
RAINFALL MODELING USING THE GEOGRAPHICALLY WEIGHTED POISSON REGRESSION METHOD Iriany, Atiek; Ngabu, Wigbertus; Ariyanto, Danang
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0627-0636

Abstract

Rainfall is an important parameter in understanding the climate and environment in the Malang Regency area. This research aims to model the distribution of rainfall in this region using the Geographically Weighted Poisson Regression (GWPR) method. GWPR is a spatial statistical approach that allows us to understand changes in inhomogeneous rainfall patterns throughout the Malang Regency area. Rainfall data collected from weather stations over several years was used in this study. We use GWR to study the relationship between various environmental factors, such as topography, vegetation, and land use, and rainfall distribution in Malang Regency. The results of the GWR analysis provide a deeper understanding of the spatial differences in the influence of these factors on rainfall. By applying GWR, we can find out how certain factors contribute to different rainfall patterns in certain regions. Rainfall modeling using the Geographically Weighted Poisson Regression (GWPR) method combines the power of Poisson regression in analyzing calculated data with the advantages of GWR in modeling spatial variability. GWPR allows us to identify and map rainfall distribution patterns that vary in geographic space. The main advantage of GWPR is its ability to provide local adjustments and capture the spatial variability associated with rainfall distribution. The results of the modeling analysis show that the GWPR is better, marked by the smallest AIC value, namely 336.84, compared to the generalized poisson regression model, namely 337.76.
PATH ANALYSIS OF FACTORS INFLUENCING CASHLESS SOCIETY DEVELOPMENT USING BOOTSTRAP RESAMPLING Pramaningrum, Dea Saraswati; Fernandes, Adji Achmad Rinaldo; Iriany, Atiek; Solimun, Solimun
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2071-2082

Abstract

Path analysis can be applied to various fields, one of which is the field of banking economics. This study is aimed to examine what factors significantly affect the development of cashless society both directly and indirectly. There are many studies related to the development of cashless society but there has been no research that analyzes the relationship between marketing mix variables, such as product, price and promotion, with the development of cashless society. The data used came from the results of questionnaires with respondents of bank customers in Jakarta. Direct influence tests are carried out using bootstrap resampling hypothesis tests so that they are free from data distribution assumptions. It was found that product and digitalization of electronic money had a significant direct effect on the development of cashless society while price had a significant indirect effect on the development of cashless society.
Co-Authors A. Fahmi Indrayani Achmad Efendi Achmad Efendi Adji Achmad Rinaldo Fernandes Adji Achmad Rinaldo Fernandes 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 Danang Ariyanto Darmanto Darmanto David Forgenie Devi Veda Amanda 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 Henida Ratna Ayu Putri Henny Pramoedyo Henny Pramoedyo Iwan Setiawan Khoiril Anam, Khoiril Kusdarwati, Heni Maghfiro, Maulidya Maisaroh, Ulfah Marhen Andan Prasetyo Maulidya Maghfiro Mellysa Isnaini Muhamad Firdaus Muhamad Ridwan Ni Wayan Surya Wardhani 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 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 Wigbertus Ngabu Yuliana, Mila