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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Statistika Universitas Muhammadiyah Semarang BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Zeta - Math Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jambura Journal of Mathematics M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jurnal Varian Mandalika Mathematics and Educations Journal Inferensi JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Jurnal Litbang Edusaintech ARRUS Journal of Mathematics and Applied Science Mathematics and Applications (MAp) Journal Jurnal Siger Matematika Journal of Research Applications in Community Services Eksponensial Asian Journal of Science, Technology, Engineering, and Art Mikailalsys Journal of Mathematics and Statistics
Dani, Andrea Tri Rian
Universitas Mulawarman
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Peran edukasi dalam menjaga kebersihan dan kesehatan gigi anak di masyarakat Kusuma, Ratna; Samsurianto, Samsurianto; Darnah, Darnah; Dani, Andrea Tri Rian
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 3 (2025): May
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i3.30289

Abstract

AbstrakKesehatan gigi dan mulut merupakan aspek penting dalam mendukung kesejahteraan anak-anak serta mencegah penyakit gigi sejak dini. Namun, rendahnya kesadaran masyarakat terhadap kebersihan gigi menyebabkan tingginya prevalensi karies gigi pada anak-anak. Untuk mengatasi permasalahan ini, program sosialisasi dan edukasi kesehatan gigi dilaksanakan pada 26 Juli 2024 di SDN 001 Tabalar Muara sebagai bagian dari Kuliah Kerja Nyata (KKN) Universitas Mulawarman. Kegiatan ini bertujuan meningkatkan pemahaman siswa mengenai pentingnya menjaga kebersihan gigi serta mengajarkan teknik menyikat gigi yang benar melalui pendekatan interaktif, seperti pemaparan materi, praktik langsung, dan diskusi kelompok. Hasil kegiatan berdasarkan observasi menunjukkan peningkatan kesadaran siswa, meskipun masih ditemukan kebiasaan kurang baik, seperti konsumsi makanan manis berlebihan dan tidak menyikat gigi sebelum tidur. Sebagai tindak lanjut, poster edukatif disebarluaskan di lokasi strategis untuk memperkuat pesan yang disampaikan. Edukasi berkelanjutan serta dukungan dari berbagai pihak diharapkan dapat membentuk kebiasaan menjaga kesehatan gigi sejak dini dan menurunkan angka penyakit gigi pada anak-anak. Kata kunci: edukasi; gigi anak; kebersihan; kesehatan; sosialisasi AbstractOral health is an important aspect in supporting children's welfare and preventing dental disease from an early age. However, low public awareness of dental hygiene causes a high prevalence of tooth decay in children. To overcome this problem, a dental health socialization and education program was implemented on July 26, 2024 at SDN 001 Tabalar Muara as part of the Mulawarman University Community Service Program (KKN). This activity aims to increase students' understanding of the importance of maintaining dental hygiene and teach proper tooth brushing techniques through an interactive approach, such as material presentation, direct practice, and group discussions. The results of the activity based on observations showed an increase in student awareness, although there were still bad habits, such as excessive consumption of sweet foods and not brushing their teeth before going to bed. As a follow-up, educational posters were distributed in strategic locations to reinforce the message conveyed. Continuous education and support from various parties are expected to form the habit of maintaining dental health from an early age and reduce the number of dental diseases in children. Keywords: education; children's dental health; hygiene; health; socialization
Mengeksplorasi Masalah Kejahatan dari POV Statistik dengan Regresi Binomial Negatif Dani, Andrea Tri Rian; Fathurahman, M.; Ni'matuzzahroh, Ludia; Putri Permata, Regita; Putra, Fachrian Bimantoro
Jurnal Varian Vol. 8 No. 2 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i2.4445

Abstract

Criminality is a complex issue in Indonesia that is very important to the government, law enforcement agencies, and society. The underlying causes of Indonesia's crime problem are complex and impacted by various circumstances. The aim of this research is to model the crime problem in Indonesia and determine the influencing factors.  The method used in this research is Negative Binomial Regression. The results of the study show that the negative binomial regression model can be used to model criminal problems because the variance value is more significant than the average. Based on the parameter significance test results, both simultaneously and partially, the open unemployment rate, Gini ratio, average years of schooling, and prevalence of inadequate food consumption significantly affect the crime rate, with an Akaike’s Information Criterion Corrected (AICc) value of 698,098. These findings suggest that addressing economic inequality, unemployment, education, and food security could help reduce crime in Indonesia. Policies aimed at improving job opportunities, reducing income disparity, and enhancing education and food security are crucial in mitigating crime. This study provides valuable insights for policymakers and law enforcement agencies, offering a foundation for more targeted and effective crime prevention strategies. Future research could employ the robust Poisson Inverse Gaussian Regression method to avoid the overdispersion problem. 
ESTIMATION OF A BI-RESPONSE TRUNCATED SPLINE NONPARAMETRIC REGRESSION MODEL ON LIFE EXPECTANCY AND PREVALENCE OF UNDERWEIGHT CHILDREN IN INDONESIA Anisar, Anggi Putri; Sifriyani, Sifriyani; Dani, Andrea Tri Rian
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/barekengvol17iss4pp2011-2022

Abstract

Researchers use the nonparametric regression method because it provides excellent flexibility in the modeling process. Nonparametric regression procedures can be used if the relationship pattern between the predictor and response variables is unknown. The truncated spline method is one of the most frequently used nonparametric regression methods. A truncated spline is a polynomial slice with continuous segmented properties, and the resulting curve is relatively smooth. The advantage of truncated splines is that they can be used on data that experience behavior changes at specific intervals. The nonparametric spline truncated bi-response regression approach is used when one or more predictor variables affect the two response variables with the assumption that there is a correlation between the response variables. This study aimed to obtain the best spline truncated bi-response nonparametric regression model on life expectancy data and the prevalence of underweight children in Indonesia in 2021. The data used comes from the Central Bureau of Statistics and the Indonesian Ministry of Health. The optimal knot point selection method uses the Generalized Cross Validation (GCV) method. The results showed that the best model formed was obtained using three-knot points based on a minimum GCV value of 22.77 and a coefficient of determination of 99.58%.
MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS Sifriyani, Sifriyani; Dani, Andrea Tri Rian; Fauziyah, Meirinda; Mar’ah, Zakiyah
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/barekengvol17iss4pp2023-2032

Abstract

Research on innovations in the statistics and statistical computing program systems implemented in the health sector. The development of a mixed estimator model is an innovation of nonparametric regression analysis by combining two approaches in nonparametric regression, namely the truncated spline estimator and the Epanechnikov kernel. The urgency of this study is that there are often cases where there are different data patterns from each predictor variable. In addition, by using only one form of the estimator in estimating a multivariable regression curve, the result is that the estimator obtained will not match the data pattern. The research objective was to find a mixed estimator between the truncated spline and the Epanechnikov kernel and the estimator results were applied to Dengue Hemorrhagic Fever case data. The unit of observation is a province in Indonesia and This study relied on secondary data received from the Central Statistical Agency (BPS) and the Health Office. Based on the analysis results, it was found that the best model of nonparametric regression with a mixed estimator of the truncated spline and Epanechnikov Kernel is a model with 3 knots with a combination of variables. The coefficient of determination (R2) is 98.11%. We can conclude that the mixed estimator tends to follow actual data and represents a nonparametric regression model with a mixed estimator that can predict the number of Dengue Hemorrhagic Fever Cases in Indonesia
MODELING OPEN UNEMPLOYMENT RATE IN KALIMANTAN ISLAND USING NONPARAMETRIC REGRESSION WITH FOURIER SERIES ESTIMATOR Rahmania, Rahmania; Sifriyani, Sifriyani; Dani, Andrea Tri Rian
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/barekengvol18iss1pp0245-0254

Abstract

Nonparametric regression is a regression approach that is used to determine the relationship between the response variable and the predictor variable if the shape of the regression curve is unknown. One of the popular estimators used in nonparametric regression is the Fourier series estimator. Fourier series nonparametric regression is generally used when the pattern of the investigated data is unknown and there is a tendency for the pattern to repeat. The purpose of this study is to estimate nonparametric regression using the Fourier series approach and to find out the factors that influence the open unemployment rate on the island of Borneo in 2021. The criteria for the goodness of the model used Generalized Cross Validation (GCV) and the coefficient of determination ( ). Based on the results, it was found that the best nonparametric regression model for the Fourier series was the model with 5 oscillations which indicated a minimum GCV of 10.47 and an of 74.22%. Furthermore, based on the results of parameter significance testing either simultaneously or partially, it shows that all predictor variables have a significant effect on the open unemployment rate. The predictor variables include the labor force participation rate, the average length of schooling, the percentage of poor people, economic growth rate, and total population.
MODELING STUNTING PREVALENCE IN INDONESIA USING SPLINE TRUNCATED SEMIPARAMETRIC REGRESSION Fadlirhohim, Rizki Dwi; Sifriyani, Sifriyani; Dani, Andrea Tri Rian
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp2015-2028

Abstract

Semiparametric regression combines parametric and nonparametric regression approaches. It is employed when the relationship pattern of the response variable is known with some predictors, while for other predictors, the relationship pattern is uncertain. The parametric regression component in this study is linear regression, while the nonparametric component utilizes a spline truncated estimator, resulting in a semiparametric spline truncated regression model. The case study focuses on the prevalence of stunting across 34 provinces in Indonesia in 2022, revealing a relatively high prevalence of 21.60%. The research aims to determine the optimal number of knots, the best model, and factors influencing stunting prevalence in Indonesia. The findings indicate that the optimal three-knot model with a GCV of 9.30 yields an RMSE of 1.70 and R2 of 92.71%. Significance tests for simultaneous and partial parameters reveal that all predictor variables significantly influence stunting prevalence.
Comparative Analysis Of Neural Network Model Selection And Data Transformation For Rainfall Forecasting Permata, Regita Putri; Dani, Andrea Tri Rian
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 10 No. 3 (2025): Mathline : Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v10i3.763

Abstract

The selection of input models in neural networks significantly influences predictive accuracy in time series forecasting. This study evaluates different input models for neural networks in rainfall prediction using data from the Wonorejo Reservoir, Surabaya. The neural network inputs are determined based on significant lags identified through the Partial Autocorrelation Function (PACF) and ARIMA models. Simulation results indicate that the best Feed Forward Neural Network (FFNN) model utilizes PACF-derived input lags and is trained using the Rprop+ algorithm with a logistic activation function. Meanwhile, the optimal Deep Learning Neural Network (DLNN) model employs the Rprop- algorithm with a logistic activation function. The best-performing model for rainfall forecasting, based on the lowest Root Mean Squared Error of Prediction (RMSEP), is the FFNN model with an (8,4,1) architecture. To further refine the model, we applied a stepwise selection process to eliminate non-significant lag inputs. However, results show that this optimization had no substantial impact, as RMSEP increased after the stepwise procedure.
Estimasi Produksi Beras dengan Estimator Campuran Spline Truncated – Kernel di Jawa Timur Dani, Andrea Tri Rian; Putra, Fachrian Bimantoro; Budiantara, I Nyoman; Ratnasari, Vita
Jambura Journal of Mathematics Vol 7, No 2: August 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v7i2.33379

Abstract

This study aims to apply a nonparametric regression model using a mixed estimator of Truncated Spline and Kernel to estimate Rice Production in East Java Province. This model combines several predictor variables, namely Harvested Area of Rice Plants, Rice Productivity, Population, and Human Development Index. The selection of the best combination of variables is based on the lowest Generalized Cross-Validation (GCV) value to obtain a stable and accurate model. The results show that the model with a combination of variables Harvested Area of Rice Plants and Rice Productivity set as Truncated Spline components with three knot points, and Population and Human Development Index as Kernel components produces a minimum GCV value of 85,504,949, RMSE of 242,723.6, and R² of 91.24%. This model successfully captures non-linear relationship patterns and provides more stable estimates. The implication of this finding is that the resulting model can be used to design more efficient agricultural policies, by considering the factors that interact dynamically in rice production.
Pendampingan Desain Infografis dengan Statistika dan Sains Data Bagi Siswa/Siswi MAN 1 Kota Samarinda Muhammad Fathurahman; Dani, Andrea Tri Rian; Fauziyah, Meirinda; Darnah; Goenjatoro, Rito; Hayati, Memi Nor; Prangga, Surya; Siringoringo, Meiliyani; Oroh, Chiko Zet
Journal of Research Applications in Community Service Vol. 4 No. 3 (2025): Journal of Research Applications in Community Service
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/jarcoms.v4i3.5158

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk memberikan pendampingan desain infografis yang mengintegrasikan ilmu statistika dan sains data serta meingkatkan literasi data bagi siswa dan siswi MAN 1 Kota Samarinda. Dalam era digital yang ditandai dengan kemudahan akses informasi, masih terdapat kekurangan pemahaman di kalangan siswa mengenai pemanfaatan teknologi, khususnya dalam desain infografis berbasis statistika dan sains data. Infografis merupakan alat yang efektif untuk menyajikan informasi secara visual yang membantu mempercepat pemahaman data kompleks menjadi lebih mudah dipahami. Aplikasi Canva dipilih sebagai platform dalam pendampingan ini karena kemudahan penggunaannya, yang memungkinkan siswa untuk berkreasi secara mandiri. Berdasarkan hasil tes awal, siswa belum memanfaatkan dengan optimal pengembangan ilmu data sains dalam pembuatan desain infografis. Oleh karena itu, kegiatan ini dirancang untuk memberikan pemahaman dan keterampilan praktis kepada peserta agar mereka dapat menggunakan teknologi visual dalam mengelola dan menyampaikan informasi berbasis data dengan lebih efektif dan inovatif. Melalui metode pengabdian ini, diharapkan terjadi peningkatan pemahaman dan keterampilan dalam penggunaan desain infografis serta pemanfaatan sains data literasi siswa yang dapat diterapkan dalam kegiatan belajar mengajar, terutama dalam pengolahan dan penyajian data statistik.
A Simulation Study of Interval Estimation in Nonparametric Regression Using the Truncated Spline Estimator Puspitasari, Melda; Dani, Andrea Tri Rian; Fauziyah, Meirinda
Mandalika Mathematics and Educations Journal Vol 7 No 3 (2025): Edisi September
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i3.9625

Abstract

This study examines interval estimation in truncated spline nonparametric regression using simulated data. The study aims to determine the impact of sample size, variance, and knot points on the performance of the truncated spline estimator. The results show that as the sample size increases, both the Generalized Maximum Likelihood (GML) and Mean Square Error (MSE) values decrease, while the coefficient of determination increases. This study also reveals that increasing the variance leads to higher GML and MSE values, as well as a lower coefficient of determination. Furthermore, the truncated spline nonparametric regression model achieves optimal performance with three knot points. The results showed that the more knot points, the GML and MSE values will decrease, while the coefficient of determination increases. The results of this study show that the determination of sample size, variance, and knot points significantly affects the accuracy and efficiency of the truncated spline nonparametric regression model, allowing it to serve as a reference for applying truncated spline nonparametric regression more effectively to produce a more optimal model that aligns with the characteristics of the data.
Co-Authors A'yun, Qonita Qurrota AINURROCHMAH, ALIFTA Alifta Ainurrochmah Alifta Ainurrochmah Anisar, Anggi Putri Avrilia, Khairunnisa budi Cahyono Budi, Ennesya Estya Candra, Yossy Chandra, Yossy Dandito Laa Ull Darnah Darnah, Darnah Dimas Nugroho Dwi Seputro Fachrian Bimantoro Putra Fadlirhohim, Rizki Dwi Fauziyah, Meirinda Goenjatoro, Rito Hadi Koirudin Hardina Sandariria Hinadang, Elen A. I Gusti Bagus Ngurah Diksa I Nyoman Budiantara I Nyoman Budiantara Ibaad, Muhammad Irsadul IGAR CALVERIA AVIANTHOLIB Koirudin, Hadi Kosasih, Raditya Arya Krisna Rendi Awalludin LUDIA NI'MATUZZAHROH Ludia Ni'matuzzahroh Ludia Ni’matuzzahroh M. Fathurahman Mar’ah, Zakiyah Meirinda Fauziyah Melisa Arumsari Memi Nor Hayati Mislan Muawanah, Chusnul Muhammad Aldani Zen Muhammad Fathurahman Nanda Arista Rizki NARITA YURI ADRIANINGSIH Ni'matuzzahroh, Ludia Nilam Novita Sari Novidianto, Raditya Oroh, Chiko Zet Puspitasari, Melda Putra, Fachrian Bimantoro Qonita Qurrota A'yun Raditya Arya Kosasih RADITYA NOVIDIANTO Raditya Novidianto Rahayu, Joana K. Rahmah, Syifa M. Rahmania Rahmania Ramadhani, Bagus D. Ratna Kusuma, Ratna Regita Putri Permata Riry Sriningsih Rito Goejantoro, Rito Samsurianto Samsurianto Sandariria, Hardina Sifriyani, Sifriyani Siringoringo, Meiliyani Siti Mahmuda Sitinjak, Jesselin Paskalis Sri Wahyuningsih Sri Wigantono Surya Prangga Suyitno Suyitno Tanur, Erwin Vita Ratnasari Watika, Noor Hikmah Wigantono, Sri