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All Journal JBIO: jurnal biosains (the journal of biosciences) CAUCHY: Jurnal Matematika Murni dan Aplikasi Althea Medical Journal Journal of the Indonesian Mathematical Society BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jambura Journal of Mathematics M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika GREENOMIKA Jurnal Kesehatan Jurnal Pendidikan Administrasi Perkantoran (JPAP) Milang Journal of Mathematics and Its Applications Jurnal Indonesia Sosial Sains Proceeding Applied Business and Engineering Conference MILANG Journal of Mathematics and Its Applications Limits: Journal of Mathematics and Its Applications
Retno Budiarti
Department Of Mathematics, Faculty Of Mathematics And Natural Sciences, Bogor Agricultural University, Jl. Meranti, Kampus IPB Darmaga, Bogor
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Comparative Analysis of Machine Learning Algorithms on Family Wellness Classification Budiarti, Retno; Hemarani, Febri; Reza, Mohammad; Mulyasari, Rindi Melati
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 2 (2024): 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/ca.v9i2.28259

Abstract

Family welfare is a state in which a family can experience happiness, have a decent quality of life, and be sufficient in meeting primary and secondary needs in family life. One factor that influences family welfare is the amount of per capita expenditure. This study aims to compare the performance of three machine learning algorithms, namely KNN (K-Nearest Neighbors), random forest, and naive Bayes, in classifying the status of families per province in Indonesia as prosperous or not prosperous. The data used in this study is demographic and social statistics data from the years 2017-2021, obtained from the bps.go.id website. The first statistical analysis conducted is principal component analysis (PCA) with 9 predictor variables. PCA produces four principal components which are then used in the KNN, random forest, and naive Bayes methods. The analysis results from the KNN, random forest, and naive Bayes methods each yield an F1-score of 65.46%, 68%, and 69.44%, respectively.
Determining Tomato Crop Agricultural Insurance Premium for COVID-19 Pandemic Setyawan, Binar Aulia; Purnaba, I Gusti Putu; Budiarti, Retno
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 8, No 2 (2023): 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/ca.v8i2.22782

Abstract

One type of insurance known as parametric insurance has an agreement for predetermined events made at the beginning of the contract between the insurer (insurance firm) and the insured (farmer). When the causative event occurs, the provision applies that insurer must pay insured with some amount of money (damage compensation). Ozaki has formulated parametric method of premium rates for agricultural insurance build upon yields in specific area. Indonesian Ministry of Agriculture uses this method to ensure that farmers can re-plant crops in following planting season if a crop failure occurs. However, the COVID-19 pandemic's losses were not covered by this method. Given this, we would like to develop agricultural insurance models for tomato crops which figure out COVID-19 pandemic. For make it easier to see the price of tomato commodity due to impact of COVID-19 pandemic, in this research we will take a case study on agriculture managed by PT Mitra Tani Parahyangan. This company is engaged in the horeca business, so it has been greatly affected by the quarantine policy. The results of this study are suggestions for policy makers in anticipation if a pandemic occurs again, it help farmers and Indonesia’s food availability will be maintained.
Bias Correction of Lake Toba Rainfall Data Using Quantile Delta Mapping Rafhida, Syukri Arif; Nurdiati, Sri; Budiarti, Retno; Najib, Mohamad Khoirun
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 2 (2024): 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/ca.v9i2.29124

Abstract

Lake Toba, located in North Sumatra, is the largest tectonic and volcanic lake in Indonesia. Lake Toba has an equatorial climate characterized by abundant rainfall throughout the year. High rainfall, coupled with annual increases due to climate change, results in a vulnerability to the unpredictable extreme weather, causing harm to the surrounding communities. Consequently, a rainfall prediction model is needed to anticipate the impacts of such extreme rainfall. One of the rainfall prediction models used is ERA5-Land. However, this prediction model has biases that can be avoided. A method that can be used is the statistical bias correction using the quantile delta mappings (QDM) by correcting ERA5-Land model data against BMKG observation data. The QDM method used in this study employs two types of methods: monthly and full distribution. The results shows that both methods can improve biases at Silaen, Laguboti, and Doloksanggul stations, as well as improve the model during the equatorial dry seasons in May, June, July, and August. However, the first method improves the model distribution more in Silaen and Laguboti, while the second method improves the model distribution more in Doloksanggul.
Parametric Survival Model on IPB University’s Graduation Data Nashiruddin, Muhammad Abdurrasyid; Sumarno, Hadi; Budiarti, Retno
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 2 (2023): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i2.12681

Abstract

Graduation is one of the assessment criteria in the college accreditation process. Students who graduate on time will assist in the assessment of college accreditation. This study aims to determine the distribution that best fits student graduation data and determine the best model to analyze the factors that determine student graduation from IPB University. This study presents some parametric models in survival analysis, specifically, the accelerated failure time (AFT) model and the proportional hazard (PH) model. The objective of this research is to compare the performance of PH model and the AFT models in analyzing the significant factors affecting the student graduation at the IPB University. Based on the study's results, the distribution according to student graduation data is the Burr XII distribution, and the best model using the AIC criteria is the PH Burr XII model. The factors that influence the graduation of IPB University students are gender, faculty, GPA, regional origin, and school status. 
Effects of grey mangrove leaf extract (Avicennia marina) on the growth of Staphylococcus aureus Priambodo, Bima; Budiarti, Retno; Rahadianto, Rahadianto; Nefertiti, Eva
JURNAL BIOSAINS Vol. 10 No. 2 (2024): JBIO : JURNAL BIOSAINS (THE JOURNAL OF BIOSCIENCES)
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jbio.v10i2.43222

Abstract

The emergence and spread of methicillin-resistant Staphylococcus aureus in recent decades complicates the antibiotic therapy. The grey mangrove (Avicennia marina) has flavonoid, terpenoid, saponin, phenolic, tannin, and alkaloid chemical compounds that have antimicrobial activity, thus potentially inhibiting Staphylococcus aureus. This study aims to examine the effects of the grey mangrove (Avicennia marina) leaf extracts on the growth of Staphylococcus aureus. This research uses laboratory experimental design with disc diffusion method to test the inhibition of Staphylococcus aureus bacteria growth in Mueller-Hinton medium. There were 6 treatment groups, namely negative control of 0.2% DMSO,  positive control of amoxicillin 30 µg, Avicennia marina leaf extract at concentration of 25%, 50%, 75%, and 100%. The results of this research showed that Avicennia marina leaf extract produces inhibition zone of 7.06 mm, 8.51 mm, 10.07 mm, 13.29 mm at concentration of 25%, 50%, 75%, and 100%. Meanwhile, positive control produces inhibiton zone of 23.65 mm, and negative control has no inhibition zone. The statistical tests using one-way ANOVA resulted in a significance value of less than 0.05 (p<α). The conclusion of this study showed that the grey mangrove (Avicennia marina) leaf extract at 100% concentration is the most effective treatment group in inhibiting the growth of Staphylococcus aureus, although the inhibition was not much better when compared to the inhibition of the positive control group.
ASYMPTOTIC DISTRIBUTIONS OF ESTIMATORS FOR THE MEAN AND THE VARIANCE OF A COMPOUND CYCLIC POISSON PROCESS Adriani, Ika Reskiana; Mangku, I Wayan; Budiarti, Retno
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0453-0464

Abstract

A stochastic process has an important role in modeling various real phenomena. One special form of the stochastic process is a compound Poisson process. A compound Poisson process model can be extended by generalizing the corresponding Poisson process. One of them is using a cyclic Poisson process. Our goals in this research are to determine the asymptotic distribution of the estimator for the mean and the variance of this process. In this paper, the problems of estimating the mean function and the variance function of a compound cyclic Poisson process are considered. We do not assume any parametric form for the intensity function except that it is periodic. We also consider the case when only a single realization of the cyclic Poisson process is observed in a bounded interval. Consistent estimators for the mean and variance functions of this process have been proposed in respectively. This paper introduces a set of novel theorems that, to the best of our knowledge, are not available in the existing literature and contribute original results to the field. Asymptotic distributions of these estimators are established when the size of the observation interval indefinitely expands. Asymptotic distributions of and are, respectively and as .
GENERALIZED NESTED COPULA REGRESSION TO UNVEIL THE IMPACT OF EXCHANGE RATES AND NIKKEI 225 ON BANK MANDIRI STOCK PRICE Khairiati, Alfi; Budiarti, Retno; Najib, Mohamad Khoirun
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1167-1184

Abstract

Fluctuations in exchange rates and foreign stock indices strongly influence domestic stock performance, particularly in the banking sector, which is highly sensitive to global economic dynamics. Traditional financial models often fail to capture the complex, non-linear dependencies between these variables, underscoring the need for more advanced approaches. This study examines the effectiveness of copula-based regression models in predicting Bank Mandiri’s (BMRI) stock price using exchange rates and the Nikkei 225 Index as predictors. Conventional regression methods, such as Linear Regression, cannot adequately capture nonlinear relationships and tail dependencies in financial time series. To address this, we compare Elliptical Copula, Symmetric Archimedean Copula, Asymmetric Archimedean Copula, and Generalized Nested Copula models. Results show that the Generalized Nested Copula Regression achieves the lowest Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Weighted MAPE (wMAPE), effectively modeling asymmetric and tail dependencies that are crucial in financial forecasting. While Elliptical Copula (t-Copula) also provides strong predictive accuracy, Archimedean copulas perform poorly, failing to improve upon linear regression. These findings highlight the importance of flexible statistical models in financial prediction, demonstrating that copula-based regression offers a superior alternative to traditional methods. Unlike prior research that often relied on simpler copula families or linear models, this study introduces a Generalized Nested Copula Regression in the context of the Indonesian banking sector, addressing a gap in emerging market literature. The study assumes correctly specified marginal distributions and a stable dependency structure, which may limit applicability under rapidly changing market conditions. Future work should consider dynamic copula structures and additional economic indicators to further enhance predictive accuracy.
Pengaruh Inflasi terhadap Strategi Optimal Investasi dan Konsumsi dengan Model Stokastik Dara Irsalina; Retno Budiarti; I Gusti Putu Purnaba
Limits: Journal of Mathematics and Its Applications Vol. 19 No. 1 (2022): Limits: Journal of Mathematics and Its Applications Volume 19 Nomor 1 Edisi Me
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The aim of this study is to investigate an optimal investment-consumption strategy under inflation rate with interest rate is described by Cox-Ingersol-Ross (CIR) model and volatility of the stock price is defined by Heston’s volatility model. A dynamic programming principle is used to obtain a Hamilton Jacobi Bellman (HJB) equation for the value function and choose a power utility function as utility function. The explicit solution of optimal investment and consumption are acquired with using separate variable and approach variable technique. The parameter’s values are approached by Euler-Maruyama method and Ordinary Least Square (OLS) method. Assumed that the portfolio of the investor contains a risk-free asset and a risk asset. Monthly historical data of TLK stock is used as risk asset and monthly historical data of BI 7-Day (Reverse) Repo Rate (BI7DRR) is used as risk-free asset, we obtain that the proportion of investment in stock is directly proportional to return of stock and the inflation rate does not have an impact on proportion investment in the stock. Meanwhile the optimal consumption of wealth is directly proportional to investor’s wealth and inversely proportional with inflation rate, which is the investor should consume less money of his wealth when the inflation rate increases.
Mathematical Model of Joint Life Term Insurance Premiums under Inflation, Interest Rate, and Dependent Mortality Habel, Ine Febrianti; Purnaba, I Gusti Putu; Budiarti, Retno
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.35690

Abstract

Multilife insurance refers to a contract that covers two or more lives simultaneously, with joint life insurance representing a key form in which the benefit is paid upon the first death among the insured individuals. The lifetimes of insured individuals are typically not independent, as they may be influenced by shared environmental, health, or behavioral factors, leading to mortality dependence. Inflation and interest rates also play critical roles in determining the present value of benefits and premiums. However, most previous studies have examined either mortality dependence or macroeconomic effects in isolation. This study aims to develop a comprehensive mathematical model for determining joint life term insurance premiums that simultaneously incorporates mortality dependence through the Gumbel copula and interest rate and inflation through the Fisher equation. The model integrates demographic and economic risk components within a unified actuarial valuation framework, providing a more realistic representation of premium dynamics under varying financial conditions. Simulation results indicate that premiums incorporating inflation are consistently higher than those without inflation, whereas higher nominal interest rates result in lower premium levels. These findings reflect the theoretical relationship between inflation, real interest rates, and the time value of money. The study further introduces an elasticity-based analysis that quantifies the sensitivity of premiums to changes in inflation and interest rates, demonstrating nonlinear yet economically meaningful responses across different age structures of insured spouses. The results highlight the importance of jointly modeling mortality dependence and economic variables to enhance pricing accuracy and fairness in life insurance. The proposed model offers practical relevance for actuaries in premium determination, assists insurers in risk management and product design, and supports the development of resilient pricing strategies under inflationary and interest.
Co-Authors Ade Irawan Adriani, Ika Reskiana Aldinasyah, Monicha Zalzabilla Anang Kistyanto Andre Dwijanto Witjaksono Asri Rahmawati Berlian Setiawaty Bib Paruhum Silalahi Chalimatusadiah Chalimatusadiah D. S. Rahmawati Daniel Happy Putra Dara Irsalina Dewi, Komang Nonik Afsari Diana, Adawiyah Putri Donny Citra Lesmana Dwi Fidiana Endar Hasafah Nugrahani Erliana, Windiani Fendy Septyanto Garianto, Efyluk Grifin Ryandi Egeten Habel, Ine Febrianti Hadi Sumarno Helynda Mulya Arga Retha Helynda Mulya Arga Retha Hemarani, Febri Herdiyantini, Mita I Gusti Putu Purnaba I Wayan Mangku Intansari, Kumala Khairiati, Alfi Khairiati, Alfi Khan, Joan Lusiana Sani Parwati Manjaruni, Vivin Aprilia Mohammad Reza Muhammad Yusuf Sulaiman Mulyasari, Rindi Melati Najib, Mohamad Khoirun Nashiruddin, Muhammad Abdurrasyid Nefertiti, Eva Nur Agustiani Prasetya, Hanung Priambodo, Bima Putra, Hilman Yusupi Dwi Putra, Oki Nugraha Rafhida, Syukri Arif Rahadianto, Rahadianto Rahmah, Salsabilla Rahmawati, D. S. Rizki, Kurniadi Ronald Pratama Adiwinoto Ruhiyat Ruhiyat S. Soedarsono Setyawan, Binar Aulia Silalahi, Romaito Br siswadi - Sitepu, Sanfriska Br Sri Nurdiati Sudiarta, Ketut Edy Sulaiman, Muhammad Yusuf Titut Harnanik Utami, Nadila Rizqi Windiani Erliana Yulianty, Sherly