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All Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jurnal Varian JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Mathematics and Applications (MAp) Journal
Ni'matuzzahroh, Ludia
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Social Sciences Other

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Pemodelan Persentase Penduduk Miskin Kabupaten/Kota di Provinsi Jawa Barat dengan Pendekatan Regresi Nonparametrik Spline Truncated Dani, Andrea Tri Rian; Ni'matuzzahroh, Ludia
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 14 No 1 (2021): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Fakultas Sains dan Teknologi Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (259.269 KB) | DOI: 10.36456/jstat.vol14.no1.a3840

Abstract

Estimator Spline Truncated adalah salah satu pendekatan dalam regresi nonparametrik yang dapat digunakan ketika pola hubungan antara variabel respon dan variabel prediktor tidak diketahui dengan pasti polanya. Estimator Spline Truncated memiliki fleksibilitas yang tinggi dalam proses pemodelan. Pada penelitian ini bertujuan untuk memodelkan persentase penduduk miskin Kabupaten/Kota di Provinsi Jawa Barat dengan menggunakan model regresi nonparametrik estimator Spline Truncated. Metode estimasi yang digunakan adalah Ordinary Least Squares (OLS). Kriteria kebaikan model regresi nonparametrik yang digunakan adalah Generalized Cross-Validation (GCV). Berdasarkan hasil analisis, diperoleh model terbaik dari regresi nonparametrik Spline Truncated, yaitu model dengan 3 titik knot, dimana diperoleh nilai GCV minimum sebesar 2.14. Berdasarkan hasil pengujian hipotesis, baik secara simultan maupun parsial, diketahui bahwa variabel prediktor yang digunakan pada penelitian ini, berpengaruh signifikan terhadap persentase penduduk miskin, dengan nilai koefisien determinasi sebesar 95.33%.
PENERAPAN MODEL REGRESI SURVIVAL WEIBULL PADA DATA PASIEN PENYAKIT GINJAL Putra, Fachrian Bimantoro; Chandra, Yossy; Dani, Andrea Tri Rian; Wigantono, Sri; Ni'matuzzahroh, Ludia
MAp (Mathematics and Applications) Journal Vol 6, No 1 (2024)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v6i1.8221

Abstract

Regresi linier adalah suatu metode prediksi yang digunakan untuk menggambarkan hubungan antara variabel prediktor dan variabel respon. Ketika variabel respon yang digunakan mengikuti distribusi Weibull, maka analisis regresi yang digunakan adalah analisis regresi Weibull. Pemodelan regresi Weibull pada penelitian ini diaplikasikan pada data waktu rawat inap pasien penyakit ginjal. Berdasarkan hal tersebut, maka tujuan penelitian ini adalah untuk mengetahui model regresi Weibull yang diaplikasikan pada data lama rawat inap pasien ginjal, serta untuk mengetahui apakah Variabel Umur, Jenis Kelamin , Riwayat Penyakit, dan Kelemahan (Frail) memiliki pengaruh terhadap lama waktu rawat inap pasien ginjal. Pengujian distribusi data waktu rawat inap menggunakan pendekatan Anderson-Darling diperoleh data waktu rawat inap pasien penyakit ginjal mengikuti distribusi Weibull. Hasil dari penelitian ini diperoleh faktor-faktor yang terbukti berpengaruh terhadap lama waktu rawat inap pasien ginjal, yaitu Frail, Jenis Kelamin, dan Riwayat Penyakit.
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. 
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%.
Co-Authors AVIANTHOLIB, IGAR CALVERIA Chandra, Yossy Dani, Andrea Tri Rian M. Fathurahman NARITA YURI ADRIANINGSIH Novidianto, Raditya Putra, Fachrian Bimantoro Regita Putri Permata Sri Wigantono Vita Ratnasari