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All Journal Media Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Ecces: Economics, Social, and Development Studies JSMARTech : Journal of Smart Bioprospecting and Technology Jurnal Teknik Informatika (JUTIF) MATHunesa: Jurnal Ilmiah Matematika SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT Journal of Statistics and Data Science
Fernandes, Adji Achmad Rinaldo
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Transportation Other

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ENSEMBLE BAGGING WITH ORDINAL LOGISTIC REGRESSION TO CLASSIFY TODDLER NUTRITIONAL STATUS Arini, Luthfia Hanun Yuli; Solimun, Solimun; Efendi, Achmad; Fernandes, Adji Achmad Rinaldo
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp1-12

Abstract

One problem in classifying stunting data is that the data used does not have a balanced proportion. This study aims to apply the logistic regression classification method with ordinal scale response variables to overcome class imbalance through the ensemble bagging approach. The data used is secondary data in the form of final research reports that have been tested for validity and reliability. The predictor variables used are economic conditions, health services and the environment with categorical response variables, namely the nutritional status of toddlers in the categories of stunting, normal and high. The methods used are ordinal logistic regression and ensemble bagging on ordinal logistic regression with bootstraps of 100, 500, and 1000. The variables that influence the nutritional status of toddlers are Economic Conditions, Health Services, and the Environment. The results of the study showed that the accuracy, sensitivity, specificity, and F1-Score for ordinal logistic regression were smaller than ensemble bagging in ordinal logistic regression. The best classification method obtained was bagging logistic regression with a bootstrap number of 500 and obtained an accuracy value of 85%, sensitivity of 87.2%, specificity of 72.6%, and F1-Score of 79.3%.
STATISTICAL MODELING OF TOURISM INVESTMENT DECISIONS IN INDONESIA USING SEMIPARAMETRIC APPROACH Pratama, Yossy Maynaldi; Fernandes, Adji Achmad Rinaldo; Wardhani, Ni Wayan Surya; Nurjannah, Nurjannah; Solimun, Solimun
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/barekengvol18iss1pp0529-0536

Abstract

The tourism potential in Indonesia is very large considering that Indonesia consists of tens of thousands of separate islands. Indonesia has many diverse landscapes, with all its nature wealth and biodiversity in it is an attraction for investors who want to invest in Indonesia. The existence of relationships between variables that are linear and nonlinear, where no nonlinear pattern is known, requires a semiparametric approach. This study aims to apply a semiparametric approach to model people's investment decisions in tourism in Indonesia. The data used is in the form of respondents from investors who invest in tourism in Indonesia from the 2022 National Competitive Basic Research (PDKN) as many as 100 respondents. This study uses the semiparametric path analysis method to model tourism investment decisions in Indonesia. The results show that regulatory variables and investment interest variables have a significant and positive effect on investment decision variables. A diversity coefficient of 60.2% indicates that data diversity can be explained by 60.2% with models, while other variables outside the study explain the remaining 38.8%. In other words, the regulatory variable (X) and the investment interest variable (Y1) can influence the investment decision variable (Y2) by 60.2%.
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.
DEVELOPMENT OF SEMIPARAMETRIC PATH ANALYSIS MODELING TRUNCATED SPLINE: DETERMINANTS OF INCREASED REGIONAL ECONOMIC GROWTH Junianto, Fachira Haneinanda; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun; Hamdan, Rosita Binti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp0949-0960

Abstract

This research aims to determine regional economic improvement to achieve a better Indonesian economy and accelerate the path to achieving a Golden Indonesia in 2045 so that it can be realized in a shorter time. This goal will be achieved with the help of statistical analysis methods, where the analysis used in this research is semiparametric truncated spline indirect effect and total effect analysis. The research becomes original in its approach with the utilization of this method and offers novel insights into the dynamics of regional economic development in Indonesia. These methods in this research serve as a tool for analyzing regional economic dynamics, identifying critical factors for improvement, informing policy decisions aimed at realizing Indonesia's economic aspirations for the future, and providing more flexible results to achieve the research objectives. The study was carried out on data with regional expenditure variables as exogenous variables, labor absorption variables as mediating endogenous variables, and regional economic growth variables as pure endogenous variables. The data used in the research are data published by the National/Provincial Central Bureau of Statistics in the form of the Indonesian Statistics Book, BPS publications in the form of Provinces, Provincial Government Financial Statistics, Directorate General of Financial Balance, Sumreg Bappenas, as well as from Ministries, Institutions or Agencies that related to providing data relating to the variables of this research in 2020. The results of this research are that the relationship between regional expenditure variables and labor absorption variables has a significant effect on regional economic growth variables.
ANALYSIS OF PATH NONPARAMETRIC TRUNCATED SPLINE MAXIMUM CUBIC ORDER IN BANKING CREDIT OF RISK BEHAVIOR MODEL Amanda, Devi Veda; Iriany, Atiek; Fernandes, Adji Achmad Rinaldo; 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/barekengvol18iss4pp2639-2652

Abstract

Path analysis tests the relationship between variables through cause and effect. The assumption of linearity must be met before conducting further tests on path analysis. If the shape of the relationship is nonlinear and the shape of the curve is unknown, a nonparametric approach is used, one of which is a truncated spline. The purpose of this study is to estimate the function and obtain the best model on the nonparametric truncated spline path of linear, quadratic, and cubic orders with 1 and 2-knot points and determine the significance of the best function estimator in banking credit of risk behavior model through the jackknife resampling method. This study uses secondary data through questionnaires to KPR debtor consumers, as many as 100 respondents. Based on the results of the analysis, it is known that the best-truncated spline nonparametric path model is the quadratic order of 2 knots with a coefficient of determination of 85.50%; the significance of the best-truncated spline nonparametric path estimator shows that all exogenous variables have a significant effect on endogenous variables.
ENHANCING WEIGHTED FUZZY TIME SERIES FORECASTING THROUGH PARTICLE SWARM OPTIMIZATION Zamelina, Armando Jacquis Federal; Astutik, Suci; Fitriani, Rahma; Fernandes, Adji Achmad Rinaldo; Ramifidisoa, Lucius
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/barekengvol18iss4pp2675-2684

Abstract

Climate change is a complex process that has far-reaching consequences for daily living. Temperature is one of the climatic features. Knowing its future value through a forecasting model is critical, as it aids in earlier strategic decision-making. Without considering spatial factors, this study investigates an Air Temperature variable forecasting. Weighted Fuzzy Time Series (WFTS) is one of the forecasting techniques. Furthermore, the length of the interval and the extent to which previous values (Order length) are utilized in predicting the subsequent value are pivotal factors in WFTS modelization and its forecasting accuracy. Therefore, this research investigates the interval length and the Order length of the WFTS through the Particle Swarm Optimization (PSO) approach. The variable used is the air temperature in Malang, Indonesia. The dataset is taken from BMKG-Indonesia. The forecasting performance of classical WFTS is enhanced by setting an appropriate order level and employing Particle Swarm Optimization (PSO) to determine the optimal interval fuzzy length. As indicated by the Evaluation matrices in the result section, the proposed optimization overtaken the classical WFTS in term of accuracy. The evaluation indicates a Mean Absolute Percentage Error (MAPE) value of 1.25 and a Root Mean Square Error (RMSE) of 0.32 for the Proposed model. In contrast, the classical WFTS demonstrates a MAPE of 2.26 and RMSE of 0.58. The implementation of the PSO provides solid insights for Air temperature forecasting accuracy.
DEVELOPMENT OF NONPARAMETRIC PATH FUNCTION USING HYBRID TRUNCATED SPLINE AND KERNEL FOR MODELING WASTE-TO-ECONOMIC VALUE BEHAVIOR Rohma, Usriatur; Fernandes, Adji Achmad Rinaldo; Astutik, Suci; Solimun, Solimun
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp331-344

Abstract

Waste management remains a challenge, including in Batu City, East Java, Indonesia. Rapid population growth and economic activities in the city have resulted in a substantial increase in waste volume. One of the key factors in solving waste problems is the mindset of the community towards waste management. The application of statistical analysis methods can be an effective approach to solving problems related to waste management from an economic point of view. Nonparametric path analysis is a statistical method that does not rely on the assumption that the curve is known. Nonparametric path analysis is performed if the data does not fulfill the linearity assumption. This study aims to determine the best nonparametric path function with a hybrid truncated spline and kernel approach among EV values of 0.5; 0.8; and 1. In addition, this study also aims to test the significance of the best path function obtained. The data used in this study are timer data obtained from the Featured Basic Research Grant. The results showed that the best model of hybrid truncated spline and kernel nonparametric path analysis is a hybrid model of truncated spline nonparametric path of linear polynomial degree 1 knot and kernel triangle nonparametric path at EV 0.5. In addition, the significance of the best nonparametric truncated spline and kernel hybrid path function estimation using jackknife resampling shows that all exogenous variables have a significant effect on endogenous variables as evidenced by a p-value smaller than (0.05).
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

Abstract

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.
Nonparametric Smoothing Spline Approach in Examining Investor Interest Factors Pratama, Yossy Maynaldi; Fernandes, Adji Achmad Rinaldo; Wardhani, Ni Wayan Surya; Hamdan, Rosita
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i2.20192

Abstract

The nonparametric approach is an appropriate approach for patterns of relationships between predictor variables and response variables that are not or have not been known in form. In other words, there is no complete information about the pattern of relationships between variables. Curve estimation is determined based on relationship patterns in existing data. The nonparametric approach has great flexibility for estimating regression curves. This study aims to form a model on investor interest factors in improving tourism investment decisions with a nonparametric approach. The nonparametric method used is the smoothing spline regression method. The smoothing spline method is used because the modeling results from the smoothing spline approach can follow the relationship model between variables contained in the data. Thus, this method really helps researchers to model relationships between variables that are not linear and whose linear form is unknown. The results of the analysis showed that the nonparametric smoothing spline regression analysis method could model data by 94.63%, indicates that data variance can be explained by 94.63% with models, while other variance outside the study explain the remaining 5.37%. That is, investment motivation is one of the most important factors to improve investment decisions. 
The Application of Truncated Spline Semiparametric Path Analysis on Determining Factors Influencing Cashless Society Development Pramaningrum, Dea Saraswati; Fernandes, Adji Achmad Rinaldo; Iriany, Atiek; Solimun, Solimun
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i2.19913

Abstract

Semiparametric path analysis is a combination of parametric and nonparametric path analysis. Semiparametric path analysis is used when there are partially nonlinear and unknown patterns of relationships. One approach to semiparametric pathways is truncated spline. Truncated spline approach tends to search for their own estimation of regression functions according to the data. This is because in the truncated spline there are knot points, which are intersection points that indicate changes in data behavior patterns. Truncated spline semiparametric path analysis will be applied to this study to determine the variables that have a significant effect on the development of the Cashless Society so that the result can be used as a reference for banks and the government in maximizing non-cash-based community development. The data used is the result of a questionnaire with 100 respondents of mobile banking users in Jakarta and will be analyzed using R Studio. Based on the results, it was found that the optimal knot point in the truncated spline function is 3 with many knots is 1, thus dividing the condition of digitizing electronic money into 2 regimes. It was concluded that the product and digitalization of electronic money had a significant effect on the development of cashless society where the modeling obtained could explain 83.87548% of the data. However, when electronic digitalization increases through the value of knot points, the development of cashless society tends to stagnate. This could be due to people who are not ready when the condition of digitizing electronic money is increasingly sophisticated because the available electronic money features are increasingly complex. Therefore, it is important for banks to pay attention to the sophistication of electronic money features provided to customers and adjust the target market so that customers are more accustomed and comfortable to use electronic money in the future.
Co-Authors Achmad Efendi Al Jauhar, Hafizh Syihabuddin Alim, Viky Iqbal Azizul Amanda, Devi Veda Amirullah, Khoirul Insan Arini, Luthfia Hanun Yuli Atiek Iriany Azizah, Laila Nur Bakar, Normizan bin Danang Ariyanto Eni Sumarminingsih Fimba, Adfi Bio Hamdan, Rosita Hamdan, Rosita Binti Henny Pramoedyo Hidayat, Kamelia Hidayatulloh, Moh Zhafran Hidayatulloh, Moh. Zhafran Junainto, Fachira Haneinanda Junianto, Fachira Haneinanda Khairani, Aldianur Khairina, Nadia Lusia, Dwi Ayu Maisaroh, Ulfah Marchamah, Mamlu’atul Nasywa, Alfiyah Hanun Ni Wayan Surya Wardhani Nisa, Hilwin Nurdin, Muhammad Rafi Hasan Nurjannah Nurjannah Nurjannah Pramaningrum, Dea Saraswati Pratama, Yossy Maynaldi Putri, Henida Ratna Ayu Putri, Nazwa Anindya Rahma Fitriani Rahman R, Abd Rahmanda, Lalu Ramzy Ramadhan, Rangga Ramifidiosa, Lucius Ramifidisoa, Lucius Rejeki, Sasi Wilujeng Sri Rizqia, Anggun Fadhila Rohma, Usriatur Sabir Sabir Saris, Laode Muhammad Solimun Solimun, Solimun Suci Astutik Sumara, Rauzan Ullah, Mohammad Ohid Ullah, Muhammad Ohid Utomo, Candra Rezzining Wulat Sariro Weni Wigbertus Ngabu Yulianto, Shalsa Amalia Zamelina, Armando Jacquis Federal Zuhdi, Muhammad Rizal