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All Journal Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Economics Development Analysis Journal
Eni Sumarminingsih
brawijaya university
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Sicad: Smart Information System For Village Administration As An Empowering Ngadiluwih Village Kediri In Improving Community Services Astuti, Ani Budi; Nugroho, Waego Hadi; Sumarminingsih, Eni; Rotchildi, Gusti Ayu Putu Rawi; Sa'diyah, Nur Kamilah; Kalangi, Olyvia Maria; Ibnu, Muhammad
Journal of Innovation and Applied Technology Vol 9, No 2 (2023)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jiat.2023.9.2.01

Abstract

The Ngadiluwih Village Government, Kediri Regency, East Java Province also really needs an Android-based application so that the reach of access is wide in an effort to digitize villages to improve village administration services online. The purpose of this community service activity is to build and develop the Ngadiluwih Village Government Smart Information System application, which is abbreviated as Ngadiluwih SICAD in the context of empowering Ngadiluwih Village in an effort to improve online village administration services to the community. The socialization, implementation, and assistance were also carried out to village officials and the community regarding the Ngadiluwih SICAD application product. The results of this activity show that the Ngadiluwih SICAD that has been built is in accordance with the expectations and needs of Ngadiluwih Village and the community with 14 types of letter facilities.
Development of Ramsey RESET to Identify the Polynomials Order of Smoothing Spline with Simulation Study Nurdin, Muhammad Rafi Hasan; Fernandes, Adji Achmad Rinaldo; Sumarminingsih, Eni; Ullah, Muhammad Ohid
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 1 (2025): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i1.26785

Abstract

Path  analysis is used to determine the effect of exogenous variables on endogenous variables. One of the assumptions in path analysis is the linearity assumption. The linearity assumption can be tested using Ramsey RESET. If the Ramsey RESET results show that all variables are non-linear then one of the alternative models that can be used is nonparametric smoothing spline. The smoothing spline method requires a smoothing spline polynomial order in estimating the nonparametric path analysis function. This polynomial order results in the smoothing spline method having good flexibility in data adjustment. The selection of the smoothing spline polynomial order becomes an obstacle because there is no test to determine the best order. Therefore, the purpose of this study is to find out how the value of V for order 3 and 4, develop Ramsey RESET to identify the best spline polynomial order, and evaluate the Ramsey RESET algorithm through simulation studies on various errors. The results of V values of order 3 and 4 can be obtained through the integral process and it is found that the higher the order, the value of V has a higher rank. Ramsey RESET development is done by modifying the second regression using nonparametric regression functions of order 2, 3, and 4. The simulation study results show that the classical Ramsey RESET can be used to detect linear shapes well because it is not affected by the value of the error variance. However, the classical Ramsey RESET has limitations in detecting non-linear forms other than quadratic and cubic forms so that other forms such as smoothing spline are needed. In testing non-linear models, the lowest p value is obtained in the form that matches the actual conditions, this can be interpreted that the modified Ramsey RESET can detect non-linear forms with spline polynomial orders well. The contribution of this research is to provide a test to identify the best smoothing spline polynomial order using Ramsey RESET modification
Multigroup Analysis on Partial Least Square-Structural Equation Modeling in Modeling College Students' Saving Behavior Asaliontin, Lisa; Sumarminingsih, Eni; Solimun, Solimun; Sepriadi, Hanifa; Iriany, Atiek; Hamdan, Rosita
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 1 (2025): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i1.27692

Abstract

This study aims to determine the factors that influence college students' saving behavior, with gender as a moderating variable. The analysis used is Partial Least Square-Structural Equation Modeling (PLS-SEM) with Multigroup Analysis. This study was conducted on 200 college students in City X who were selected by purposive sampling. Data collection was carried out using a structured questionnaire that measures Perceived Benefits, Perceived Ease of Use, Saving Intentions, and Saving Behavior. Confirmatory Factor Analysis (CFA) and Bootstrapping were used to validate the measurement model and structural relationships. The results showed that Perceived Benefits and Perceived Ease had a significant effect on Saving Intentions and Saving Behavior. In addition, Saving Intentions had a significant effect on Saving Behavior. This relationship applies to both male and female groups, with a determination coefficient of 86.2% for males and 86.7% for females. Moderation analysis shows that gender moderates the relationship between Perceived Benefits and Saving Behavior, as well as between Perceived Ease and Saving Behavior. These findings highlight the importance of considering gender differences in efforts to improve students' savings behavior. 
Analyzing The Development of Cashless Society Using the Structural Equation Modeling Nurdin, Muhammad; Fernandes, Adji; Sumarminingsih, Eni; Solimun; Ullah, Muhammad
Economics Development Analysis Journal Vol. 13 No. 4 (2024): Economics Development Analysis Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edaj.v13i4.15874

Abstract

Payment systems continue to evolve alongside advancements in information technology, driving the digitization of financial services and payment instruments. This study examines the influence of Psychological, Socio-Cultural, and Personal Factors on adopting electronic money and the growth of a cashless society, with Financial Technology as a moderating variable. The research involved 1,000 Bank BNI customers in the Jabodetabek area (Jakarta, Bogor, Depok, Tangerang, and Bekasi) actively using BNI Mobile Banking services. The analytical methods employed include Discourse Network Analysis and Structural Equation Modeling to develop a comprehensive analysis model. The results indicate that psychological and personal factors—such as motivation, perception, learning, positive attitude, modern lifestyle, and openness to change—significantly influence electronic money usage. However, socio-cultural factors do not exhibit a significant impact, primarily due to persistent cash usage habits and a lack of trust in technology. This study highlights the need for financial education to promote awareness of electronic money benefits and security, develop tailored financial products, and enhance regulatory collaboration between the government and relevant institutions.
Perbandingan Metode Jaringan Saraf Tiruan, Fuzzy, Dan Anfis Pada Peramalan Data Inflasi Indonesia Lusia, Dwi Ayu; Semathea, Karen; Sumarminingsih, Eni; Efendi, Achmad
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 3: Juni 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025128613

Abstract

Peramalan adalah teknik penting untuk mengestimasi nilai masa depan berdasarkan data historis. Namun, metode peramalan sering menghadapi tantangan dalam memilih model dengan tingkat akurasi terbaik. Penelitian ini bertujuan membandingkan kinerja metode Jaringan Syaraf Tiruan (JST) dan Fuzzy Metode Sugeno serta gabungan kedua metode yang disebut Adaptive Neuro Fuzzy Inference System (ANFIS). Ketiga metode digunakan untuk meramalkan inflasi bulanan Indonesia. Penerapan ketiga metode membutuhkan penentuan input yang berdasarkan stasioner dan PACF. Data tidak stasioner lag 2 sehingga Differencing lag 2 kemudian tidak ada lag yang keluar pada PACF. Berdasarkan kedua hal tersebut ditentukan inputnya ialah  dan . Hasil menunjukkan bahwa metode JST dengan 3 lapisan tersembunyi dengan banyak neuron (2,1,1) memberikan kinerja terbaik (nilai RMSE terkecil sebesar 1,16127 pada data testing). Metode terbaik tersebut digunakan untuk meramalkan Inflasi bulan September 2023 hingga Desember 2024 cenderung konstan antara 2,68879% hingga 2,68887%. Kontribusi riset ini adalah metode advance (ANFIS) dengan menggabungankan dua metode (JST dan Fuzzy) belum tentu lebih baik daripada metode tanpa penggabungan (JST atau Fuzzy).   Abstract Forecasting is an important technique for estimating future values ​​based on historical data. However, forecasting methods often face challenges in choosing a model with the best level of accuracy. This study aims to compare the performance of the Artificial Neural Network (ANN) and Fuzzy Sugeno Method methods and a combination of the two methods called the Adaptive Neuro Fuzzy Inference System (ANFIS). The third method is used to predict Indonesia's monthly inflation. The application of the third method requires input determination based on stationary and PACF. The data is not stationary lag 2 so that Differencing lag 2 then there is no lag that comes out in PACF. Based on these two things, the input is determined to be Y_(t-1) and Y_(t-2). The results show that the ANN method with 3 hidden layers with many neurons (2,1,1) gives the best performance (the smallest RMSE value is 1.16127 on the test data). The best method used to predict inflation from September 2023 to December 2024 tends to be constant between 2.68879% to 2.68887%. The contribution of this research is that the advanced method (ANFIS) by combining two methods (ANN and Fuzzy) is not necessarily better than the method without combining (ANN or Fuzzy).
ESTIMATION OF MAXIMUM LIKELIHOOD WEIGHTED LOGISTIC REGRESSION USING GENETIC ALGORITHM (CASE STUDY: INDIVIDUAL WORK STATUS IN MALANG CITY) Menufandu, Dahlia Gladiola Rurina; Fitriani, Rahma; Sumarminingsih, Eni
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 (399.767 KB) | DOI: 10.30598/barekengvol17iss1pp0487-0494

Abstract

Weighted Logistic Regression (WLR) is a method used to overcome imbalanced data or rare events by using weighting and is part of the development of a simple logistic regression model. Parameter estimation of the WLR model uses Maximum Likelihood estimation. The maximum likelihood parameter estimator value is obtained using an optimization approach. The Genetic algorithm is an optimization computational algorithm that is used to optimize the estimation of model parameters. This study aims to estimate the Maximum Likelihood Weighted Logistic Regression with the applied genetic algorithm and determine the significant variables that affect the working status of individuals in Malang City. The data used is the result of data collection from the National Labor Force Survey of Malang City in 2020. The results of the analysis show that the variable education completed and the number of household members has a significant effect on individual work status in Malang City.
Co-Authors Achmad Efendi Ani Budi Astuti Asaliontin, Lisa Atiek Iriany Elfrida Ratnawati Fernandes, Adji Fernandes, Adji Achmad Rinaldo Hamdan, Rosita Kalangi, Olyvia Maria Lusia, Dwi Ayu Menufandu, Dahlia Gladiola Rurina Muhammad Nurdin Nurdin, Muhammad Rafi Hasan Rahma Fitriani Rotchildi, Gusti Ayu Putu Rawi Sa'diyah, Nur Kamilah Semathea, Karen Sepriadi, Hanifa Solimun Solimun, Solimun Ullah, Muhammad Ullah, Muhammad Ohid Waego Hadi Nugroho