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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
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ESTIMASI MODEL REGRESI SEMIPARAMETRIK SPLINE TRUNCATED MENGGUNAKAN METODE MAXIMUM LIKELIHOOD ESTIMATION (MLE) NARITA YURI ADRIANINGSIH; ANDREA TRI RIAN DANI
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 
Flexibility of Nonparametric Regression Spline Truncated on Data without a Specific Pattern Andrea Tri Rian Dani; Narita Yuri Adrianingsih; Alifta Ainurrochmah; Riry Sriningsih
Jurnal Litbang Edusaintech Vol. 2 No. 1 (2021): Volume 2 No 1 2021
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v2i1.30

Abstract

Bentuk pola hubungan antara variabel prediktor dan variabel respon ada yang diketahui, namun pada nyatanya ada pula yang tidak diketahui. Apabila bentuk pola hubungan antara variabel respon dan variabel prediktor tidak diketahui, pendekatan regresi nonparametrik merupakan pendekatan yang paling sesuai. Pendekatan regresi nonparametrik tidak tergantung pada asumsi bentuk kurva regresi tertentu, sehingga akan memberikan fleksibilitas yang tinggi. Salah satu estimator regresi nonparametrik yang terkenal adalah spline truncated. Spline truncated merupakan potongan-potongan polinomial yang memiliki sifat tersegmen dan kontinu. Pada penelitian ini, akan disimulasikan pola hubungan antara kedua variabel yaitu respon dan prediktor yang tidak memiliki pola tertentu, yang kemudian didekati dengan dua pendekatan regresi, yaitu parametrik dan nonparametrik. Berdasarkan ukuran kebaikan estimasi kurva regresi menggunakan koefisien determinasi diperoleh hasil bahwa pendekatan regresi nonparametrik lebih baik daripada pendekatan regresi parametrik. Hal ini dikarenakan pendekatan regresi nonparametric memiliki fleksibilitas yang tinggi sehingga mampu menyesuaikan sendiri bentuk estimasi kurva regresi.
Pemodelan Regresi Nonparametrik dengan Estimator Spline Truncated vs Deret Fourier Andrea Tri Rian Dani; Narita Yuri Adrianingsih
Jambura Journal of Mathematics Vol 3, No 1: January 2021
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (484.641 KB) | DOI: 10.34312/jjom.v3i1.7713

Abstract

ABSTRAKPendekatan regresi nonparametrik digunakan apabila hubungan antara variabel prediktor dan variabel respon tidak diketahui polanya. Spline truncated dan deret Fourier merupakan estimator dalam pendekatan nonparametrik yang terkenal, karena memiliki fleksibilitas yang tinggi dan mampu menyesuaikan terhadap sifat lokal data secara efektif. Penelitian ini bertujuan untuk mendapatkan estimator model regresi nonparametrik terbaik menggunakan spline truncated dan deret Fourier. Metode estimasi kurva regresi nonparametrik dilakukan dengan menyelesaikan optimasi Ordinary Least Squares (OLS). Kriteria kebaikan model menggunakan GCV, R2 dan MSE. Pemodelan regresi nonparametrik diterapkan pada data Case Fatality Rate (CFR) akibat Demam Berdarah Dengue (DBD) di Indonesia.  Berdasarkan hasil analisis, hasil estimasi dari pemodelan regresi nonparametrik menunjukkan bahwa estimator spline truncated memberikan performa yang lebih baik dibandingkan estimator deret Fourier. Hal ini ditunjukkan dengan nilai R2 dari estimator spline truncated yaitu sebesar 91,80% dan MSE sebesar 0,04, sedangkan dengan estimator deret Fourier diperoleh nilai R2 sebesar 65,44% dan MSE sebesar 0,19.ABSTRACTThe nonparametric regression approach is used when the relationship between the predictor variable and the response variable is unknown. Spline truncated and Fourier series are well-known estimators in the nonparametric approach because they have high flexibility and are able to adjust to the local properties of the data effectively. This study aims to obtain the best nonparametric regression model estimator using the truncated spline and the Fourier series. The nonparametric regression curve estimation method is done by completing the Ordinary Least Squares (OLS) optimization. The criteria for the goodness of the model use GCV, R2, and MSE. Nonparametric regression modeling is applied to Case Fatality Rate (CFR) modeling due to Dengue Hemorrhagic Fever (DBD) in Indonesia. Based on the analysis, the estimation results from the nonparametric regression modeling show that the truncated spline estimator provides better performance than the Fourier series estimator. This is shown by the R2 value of the truncated spline estimator which is 91.80% and the MSE is 0.04, while the Fourier series estimator obtained an R2 value of 65.44% and MSE of 0.19.
ANALISIS KLASIFIKASI ARTIST MUSIC MENGGUNAKAN MODEL REGRESI LOGISTIK BINER DAN ANALISIS DISKRIMINAN ANDREA TRI RIAN DANI; VITA RATNASARI; LUDIA NI'MATUZZAHROH; IGAR CALVERIA AVIANTHOLIB; RADITYA NOVIDIANTO; NARITA YURI ADRIANINGSIH
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%.
Estimator Spline Truncated of Semiparametric Regression Estimator Regresi Semiparametrik Spline Truncated Narita Yuri Adrianingsih
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 2 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (244.075 KB) | DOI: 10.5281/zenodo.6224937

Abstract

Semiparametric regression is a combination of parametric and semiparametric regression. This regression is used on data whose pattern is known and partially the pattern is unknown. Ordinary Least Square (OLS), Maximum Likelihood Estimation (MLE), and Penalized Least Square (PLS) can be used to obtain Spline Truncated semiparametric regression curve estimators. This paper will explain about the use of Ordinary Least Square (OLS) to obtain a Spline Truncated Semiparametric Regression estimator
Pelatihan Pembuatan Diagram dengan Microsoft Excel di SMP Mainang Kabupaten Alor Narita Yuri Adrianingsih; Jeni Marianti Loban; Landerius Maro; Lory Fitriana Ur Dollu
Prima Abdika : Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2022): Volume 2 Nomor 1 Tahun 2022
Publisher : Program Studi Pendidikan Guru Sekolah Dasar Universitas Flores Ende

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37478/abdika.v2i1.1709

Abstract

 Diagram making training using Microsoft Excel is a community service carried out at the Toyg State Junior High School, which is in the Toyg Village, Alor Regency. This activity was carried out for 1 day during the training. This training aims to make students understand how to present diagrams using Microsoft Excel. The material provided has been prepared before the training, namely regarding the presentation of data with diagrams in the statistics subject. The method used is presentation and then direct practice is carried out by students. The obstacle at school is that there are no computer facilities so this is a new thing for them and they are very enthusiastic about participating in this training, so that the children quickly understand what they are being trained to do.
Belajar Perkalian dengan Menggunakan Metode Jarimatika Untuk Anak Usia SD Desa Alaang, Kabupaten Alor Jeni Marianti Loban; Narita Yuri Adrianingsih; Landerius Maro; Martasiana Karbeka
ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Vol. 1 No. 4 (2022): November 2022
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdikan.v1i4.1135

Abstract

Counting for some children is a difficult and boring activity, this has an impact on children's interest in mathematics is low. Therefore it is necessary to make efforts to increase children's interest in mathematics. A creative, innovative and interactive and fun learning process can increase children's interest and ability towards mathematics. Besides that, fun counting activities can increase a love for mathematics and counting, this is the goal of this community service activity. Multiplication by using the jarimatics method can help students more easily understand and remember multiplication one (1) to nine (9). The target of this service is all elementary school-age children in Alaang Village, Alor Barat Laut District, Alor Regency-NTT. These activities can run with the support of the Alaang Village government and all the community, our learning activities are carried out in the open, namely the shores of Alaang beach, with the concept of learning while playing. The enthusiasm of the children was high and they were interested in and really enjoyed the process of learning to count multiplication with fingers.Keywords: Calculate Multiplication, Jarimatika method.
Clustering Regencies/Cities in Kalimantan Island Based on Poverty Indicators using Agglomerative Hierarchical Clustering (AHC) Ludia Ni'matuzzahroh; Andrea Tri Rian Dani; Narita Yuri Adrianingsih
Jurnal Matematika, Statistika dan Komputasi Vol. 19 No. 1 (2022): SEPTEMBER, 2022
Publisher : Department of Mathematics, Hasanuddin University

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

Abstract

Cluster analysis is a statistical analysis that can group objects of observation into several groups/clusters based on their similarity of characteristics. The grouping into several clusters is based on the information contained in the object under study. A cluster can be said to be good if it has high internal homogeneity and high external heterogeneity. The clustering method used in this study is the agglomerate hierarchical clustering (AHC) method, where the cluster formation algorithm used in this AHC method is average linkage, single linkage, complete linkage, and ward. Cluster analysis using the AHC method will be applied to poverty indicator data for Regencies/Cities in Kalimantan Island, which consists of several variables. This study aims to obtain the optimal results of grouping Regencies/Cities in Kalimantan Island, with the number of clusters that have been determined at the beginning, namely as many as 3 clusters. Based on the results of the analysis using the AHC method, the ward algorithm produces an agglomerate coefficient value of 0.89, where this value is close to 1, which means that the ward algorithm is the best in clustering Regencies/Cities in Kalimantan Island.
Pemodelan Kadar Hemoglobin pada Pasien Demam Berdarah di Kota Samarinda Menggunakan Regresi Semiparametrik Spline Truncated Andrea Tri Rian Dani; Fachrian Bimantoro Putra; Muhammad Aldani Zen; Sifriyani Sifriyani; Meirinda Fauziyah; Vita Ratnasari; Narita Yuri Adrianingsih
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 .
Penggunaan Alat Peraga Pola Bilangan Pada Pembelajaran Matematika Di SMP Negeri Mainang Loban, Jeni Marianti; Maryanes Astriani Malese; Narita Yuri Adrianingsih; Landerius Maro
NUSANTARA Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 2 (2023): Mei : Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v3i2.1136

Abstract

Visual aids are tools that can stimulate students' thoughts, skills, attention and willingness so that they can encourage the learning process in students, besides that using teaching aids can provide space for students to be actively involved in every learning process. In fact, in Toyang State Junior High School, mathematics learning has not used visual aids. The props created and used are number pattern boxes made of used cardboard, which are designed in such an attractive way to form several number pattern boxes consisting of: square, rectangular and triangular boxes. This visual aid is used in the learning process for class VIII students of SMP Negeri Toyang. This training aims to help foster the creativity of students and improve students' ability to use teaching aids. The result of this training is that students get new experiences by learning to use visual aids, this can be seen from the enthusiasm of the students who are very large and students more easily understand the concept of number patterns
Co-Authors AINURROCHMAH, ALIFTA Alifta Ainurrochmah Alifta Ainurrochmah Andrea Tri Rian Dani Dandito Laa Ull Dani, Andrea Tri Rian Dimas Nugroho Dwi Seputro Fachrian Bimantoro Putra Fauziyah, Meirinda Felicia Joy Rotua Tamba Hinadang, Elen A. I Nyoman Budiantara IGAR CALVERIA AVIANTHOLIB Jeni Marianti Loban Landerius Maro Liana Oklas Ranly Lois Letidena Lory Fitriana Ur Dollu LUDIA NI'MATUZZAHROH Ludia Ni'matuzzahroh Maktisen Ena Martasiana Karbeka Maryanes Astriani Malese Meirinda Fauziyah Meirinda Fauziyah Mislan Muhammad Aldani Zen Nilam Novita Sari Putra, Fachrian Bimantoro Raditya Arya Kosasih RADITYA NOVIDIANTO Riry Sriningsih Sifriyani, Sifriyani Vita Ratnasari