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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jambura Journal of Mathematics Mandalika Mathematics and Educations Journal JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Jurnal Ilmiah Wahana Pendidikan Prima Abdika: Jurnal Pengabdian Masyarakat Jurnal Litbang Edusaintech Multica Science and Technology Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa Pemberdayaan Masyarakat: Jurnal Aksi Sosial Mikailalsys Journal of Mathematics and Statistics
NARITA YURI ADRIANINGSIH
Universitas Tribuana Kalabahi
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Pembelajaran KPK dan FPB yang Menyenangkan pada Anak-Anak SD GMIT Lamalu Maktisen Ena; Narita Yuri Adrianingsih
Pemberdayaan Masyarakat : Jurnal Aksi Sosial Vol. 2 No. 2 (2025): Juni : Pemberdayaan Masyarakat : Jurnal Aksi Sosial
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/aksisosial.v2i2.1527

Abstract

This community service aims to improve learning outcomes and the process of learning mathematics, especially the Greatest Common Factor (GCF) and the Least Common Multiple (LCM) in Elementary Schools to be more active and enjoyable. Learning LCM and LCM in Elementary School children can be said to have not had much impact because some students do not understand the process of solving LCM and LCM through factor trees and factoring. Community service activities were carried out in one day at SD GMIT Lamalu, Pantar District, Alor Regency. We were present to deliver material about LCM and LCM. During the community service, several students were interested in completing the material or questions given using factor trees. In the learning process about LCM and LCM, it can run well and can improve the quality of learning for students at SD GMIT Lamalu.
Binomial Distribution As a Measurement of The Success and Failure FMIPA Untrib Students in The 2018-2023 Academic Year Maktisen Ena; Jeni Marianti Loban; Narita Yuri Adrianingsih; Lois Letidena
Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa Vol. 3 No. 3 (2025): Juni: Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bilangan.v3i3.561

Abstract

This research aims to determine the estimated probability of failure for the number of FMIPA Untrib Kalabahi student graduates from 2018 to 2023 for each study program. This research uses secondary data obtained directly from the Untrib Student Affairs Academic Administration Bureau for the last six years from 2018 to 2023. The Binomial Distribution is a distribution of discrete random variables with two possibilities, namely success and failure. This research shows that the three study programs at FMIPA Untrib Kalabahi have different opportunity or probability values. For the mathematics study program, it can be seen that the largest predicted failure will be in 2022, namely 0.225585937500 and the smallest predicted failure will be in 2019, namely 0.000000000015. For the chemistry study program, the biggest failure estimate is in 2023, namely 0.37500 and the largest failure estimate is in 2021, namely 0.00006. For the informatics engineering study program, the largest failure estimate is in 2018, namely 0.0000000298023223876953 and the smallest failure estimate is in 2023, namely 0.000000000000000087.
COMPARISON OF MEAN CENTERING REGRESSION AND SPLINE TRUNCATED NONPARAMETRIC REGRESSION ON FACTORS AFFECTING THE NUMBER OF CRIMES IN INDONESIA Felicia Joy Rotua Tamba; Liana Oklas Ranly; Andrea Tri Rian Dani; Meirinda Fauziyah; Narita Yuri Adrianingsih; Mislan Mislan
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 5 No. 1 (2025): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/fpp74f96

Abstract

Crime remains one of the major challenges facing Indonesia, with the national crime rate showing an upward trend in 2022. This increase is driven by various social, economic, and demographic factors. To investigate these influences, this study applies the nonparametric truncated spline regression method to identify the determinants of crime rates across provinces in Indonesia. The response variable is the number of recorded crimes, while the predictor variables include the percentage of people living in poverty, mean years of schooling, average monthly per capita expenditure on food and non-food items, number of beneficiary households, budget for food social assistance, liberty aspects from the Indonesia Democracy Index, and the percentage of people with mental disorders. The analysis reveals that the linear truncated spline regression model with three knot points provides the best fit, achieving a coefficient of determination (R²) of 87.31%. These findings highlight the model’s capability to capture complex, nonlinear relationships between socio-economic indicators, democratic freedoms, mental health, and crime incidence in Indonesia.
A Computatioal Analysis of Kernel-Based Nonparametric Regression Applied to Poverty Data Adrianingsih, Narita Yuri; Dani, Andrea Tri Rian; I Nyoman Budiantara; Dandito Laa Ull; Raditya Arya Kosasih
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.v7i3.9802

Abstract

This research aims to model the relationship between poverty and socioeconomic variables in Nusa Tenggara Timur Province, Indonesia. The purpose of the study is to assess the effectiveness of nonparametric regression, specifically using kernel methods, to provide a more accurate representation of the complex and nonlinear relationships between predictor variables and poverty levels. The study focuses on several key variables, including average years of schooling, labor force participation rate, percentage of households with access to electricity, population density, illiteracy rate, and life expectancy. The research utilized a kernel regression approach, comparing the performance of different kernel functions, including Gaussian, Epanechnikov, Triangle, and Quartic kernels. The model’s performance was evaluated using metrics such as Mean Squared Error (MSE), Generalized Cross Validation (GCV), and the coefficient of determination (R²). The results showed that the Gaussian kernel function provided the most accurate predictions for poverty levels, with the best balance between model complexity and error.
ANALISIS KLASIFIKASI ARTIST MUSIC MENGGUNAKAN MODEL REGRESI LOGISTIK BINER DAN ANALISIS DISKRIMINAN DANI, ANDREA TRI RIAN; RATNASARI, VITA; NI'MATUZZAHROH, LUDIA; AVIANTHOLIB, IGAR CALVERIA; NOVIDIANTO, RADITYA; ADRIANINGSIH, NARITA YURI
Jambura Journal of Probability and Statistics Vol 3, No 1 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i1.13708

Abstract

Characteristics of a song are an important aspect that must be kept authentic by a singer. Using the Spotify API feature, we can extract the characteristics or elements of a song sung by a singer.  There are eight (8) elements that we can get from the extraction of a song, namely: Danceability, Energy, Loudness, Speechiness, Acousticness, Liveness, Valence, and Tempo. Based on the extraction results, we can label the music artist using the classification analysis method. In this study, the labels are music artists, namely Ariana Grande and Taylor Swift. This study aims to obtain the classification of music artist labels using binary logistic regression methods and discriminant analysis. The response variable used in this study is Artist Music (Y) which is categorized into two categories, namely Ariana Grande (Y=0) and Taylor Swift (Y=1). The data will be divided into training and testing data with the proportion of data 90:10 and 80:20. Based on the results of the analysis, the binary regression model that was built, with the proportion of training testing data that is 90:10 has a classification accuracy for data testing of 90.00%.
ESTIMASI MODEL REGRESI SEMIPARAMETRIK SPLINE TRUNCATED MENGGUNAKAN METODE MAXIMUM LIKELIHOOD ESTIMATION (MLE) ADRIANINGSIH, NARITA YURI; DANI, ANDREA TRI RIAN
Jambura Journal of Probability and Statistics Vol 2, No 2 (2021): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v2i2.10255

Abstract

Regression modeling with a semiparametric approach is a combination of two approaches, namely the parametric regression approach and the nonparametric regression approach. The semiparametric regression model can be used if the response variable has a known relationship pattern with one or more of the predictor variables used, but with the other predictor variables the relationship pattern cannot be known with certainty. The purpose of this research is to examine the estimation form of the semiparametric spline truncated regression model. Suppose that random error is assumed to be independent, identical, and normally distributed with zero mean and variance , then using this assumption, we can estimate the semiparametric spline truncated regression model using the Maximum Likelihood Estimation (MLE) method.  Based on the results, the estimation results of the semiparametric spline truncated regression model were obtained  p=(inv(M'M)) M'y 
Pemodelan Kadar Hemoglobin pada Pasien Demam Berdarah di Kota Samarinda Menggunakan Regresi Semiparametrik Spline Truncated Dani, Andrea Tri Rian; Putra, Fachrian Bimantoro; Zen, Muhammad Aldani; Sifriyani, Sifriyani; Fauziyah, Meirinda; Ratnasari, Vita; Adrianingsih, Narita Yuri
Jambura Journal of Probability and Statistics Vol 4, No 2 (2023): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v4i2.18923

Abstract

This article discusses the innovation of statistical modeling in regression analysis with a semiparametric approach applied to health data. Regression analysis is a method in statistics that takes a lot of roles in statistical modeling. Regression analysis is used to model the relationship between the independent variable (x) and the dependent variable (y). There are three approaches to regression analysis, namely parametric, nonparametric, and a combination of the two, namely semiparametric. Semiparametric regression is used when the dependent variable has a known relationship with some of the independent variables and has an unknown pattern of a relationship with some of the other independent variables. The purpose of this study was to model hemoglobin levels in dengue fever patients, with the independent variables used being the number of hematocrits (x1) and the number of leukocytes (x2). The method used is spline truncated semiparametric regression. The truncated spline estimator was chosen for the nonparametric component because it has many advantages in modeling, one of which is being able to model patterns where the form of the relationship is unknown. The parameter estimation used is the maximum estimation. Selection of the optimal knot point using Generalized Cross-Validation (GCV). Based on the results of the analysis, the truncated spline semiparametric regression model was obtained which was applied to the hemoglobin level data in a model with three knots which have a coefficient of determination of 89.074%. Based on the results of testing the hypothesis simultaneously, it can be concluded that simultaneously the independent variable has a significant effect on the dependent variable. In the partial test, it is concluded that the variables x1 and x2 have a significant influence on the dependent variable y .
Co-Authors AINURROCHMAH, ALIFTA Alifta Ainurrochmah Alifta Ainurrochmah Andrea Tri Rian Dani AVIANTHOLIB, IGAR CALVERIA Dandito Laa Ull Dani, Andrea Tri Rian Dimas Nugroho Dwi Seputro Fauziyah, Meirinda Felicia Joy Rotua Tamba Hinadang, Elen A. I Nyoman Budiantara Jeni Marianti Loban Landerius Maro Liana Oklas Ranly Lois Letidena Lory Fitriana Ur Dollu Ludia Ni'matuzzahroh Maktisen Ena Martasiana Karbeka Maryanes Astriani Malese Meirinda Fauziyah Mislan Ni'matuzzahroh, Ludia Nilam Novita Sari Novidianto, Raditya Putra, Fachrian Bimantoro Raditya Arya Kosasih Riry Sriningsih Sifriyani, Sifriyani Vita Ratnasari Zen, Muhammad Aldani