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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang Zeta - Math Journal Jambura Journal of Mathematics Jurnal Varian JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi ARRUS Journal of Mathematics and Applied Science Mathematics and Applications (MAp) Journal Mikailalsys Journal of Mathematics and Statistics Journal of Education Technology and Information System
Putra, Fachrian Bimantoro
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Other

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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.
PENERAPAN ALGORITMA HIERARCHICAL CLUSTERING DALAM PENGELOMPOKKAN KABUPATEN/KOTA DI PAPUA BERDASARKAN INDIKATOR KEMISKINAN Putra, Fachrian Bimantoro; Dani, Andrea Tri Rian; Wigantono, Sri
MAp (Mathematics and Applications) Journal Vol 5, No 2 (2023)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v5i2.7025

Abstract

Papua merupakan provinsi paling timur Indonesia yang memiliki kekayaan alam yang melimpah, khususnya kekayaan alam mineral. Namun hal tersebut, tidak serta merta melepaskan masyarakat Papua dari belenggu kemiskinan. Dari sudut pandang ekonomi, kemiskinan berkaitan dengan rasio ketergantungan, pendidikan, dan Kesehatan. Oleh karena itu, dalam upaya pengentasan kemiskinan di Papua, di rasa menjadi hal yang menarik dan perlu untuk melihat pengelompokkan wilayah mana saja yang perlu diprioritaskan. Pengelompokkan kabupaten/kota dilakukan dengan menggunakan algoritma hierarchical clustering, diantaranya single linkage, complete linkage, dan average linkage. Berdasarkan hasil analisis, diperoleh algoritma yang terbaik adalah complete linkage dengan jumlah klaster optimal yaitu 3 klaster. Pada klaster 1, terdapat 12 Kabupaten/Kota, klaster 2 terdapat 13 Kabupaten/Kota, dan klaster 3 terdapat 4 Kabupaten/Kota.
Determining Sister City Regency/City Non-Sample Cost of Living Survey (SBH) and Clustering Analysis of Consumption Patterns in West Java using the Machine Learning Method Novidianto, Raditya; Tanur, Erwin; Dani, Andrea Tri Rian; Putra, Fachrian Bimantoro
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 12, No 1 (2024): Jurnal Statistika Universitass Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.12.1.2024.%p

Abstract

Inflation is a significant data source in policy making. However, not all Regency/cities have inflation figures. As a result, Regency/cities must borrow inflation figures from dietary characteristics, GDP per capita, population, and distance between Regency and cities; this is called a sister city. With the help of machine learning, the similarity level method using distance measures, namely Euclidean distance, CID distance, and ACF distance, can help Regency/cities find sister cities. Furthermore, grouping was carried out using a biclustering algorithm to see the characteristic variables in West Java from the same consumption pattern data. The biclustering parameter with tuning parameter ????=0.1 is the best bicluster with a total of 3 biclusters with a value of MSR/V=0.02433 with identical characteristic variables, namely Average Fish Consumption (X3), Average Meat Consumption (X4), Average Consumption of Eggs and Milk (X5), Average Consumption of Vegetables (X6), Average Consumption of Fruit (X8), Average Consumption of Oil and Coconut (X9), Average Consumption of Housing and Household Facilities (X15), Average Consumption of Various Goods and Services and Average Consumption of Taxes (X16), Levies and Insurance (X19).
The Modeling Maximum Water Level in Sangkuliman East Borneo using Singular Spectrum Analysis Dani, Andrea Tri Rian; Mislan, Mislan; Putra, Fachrian Bimantoro
ARRUS Journal of Mathematics and Applied Science Vol. 4 No. 2 (2024)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience2945

Abstract

Penelitian ini bertujuan untuk memodelkan rata-rata tinggi muka air maksimum di danau Sangkuliman dengan menggunakan data runtun waktu yang dikumpulkan sejak Januari 2015 – Desember 2022. Metode yang digunakan adalah Singular Spectrum Analysis (SSA). SSA adalah salah satu metode analisis runtun waktu yang memiliki kelebihan, diantaranya fleksibilitas dalam mendeteksi pola khususnya pola musiman. Data dibagi menjadi data in-sample dan out-sample dengan proporsi 90:10. Ukuran akurasi yang digunakan adalah Symmetric Mean Absolute Percentage Error (SMAPE). Berdasarkan hasil analisis, diperoleh windown length optimal L = 12 dengan nilai SMAPE minimum. Hasil peramalan dari SSA berdasarkan koefisien Linear Recurrent Formula (LRF) menunjukkan pola data hasil prediksi cenderung mengikuti pola data aktual.
Analysis the Effect of Inflation, Gold Prices in Dollars, Rupiah Exchange to Bank Indonesia Monthly Rates After the COVID 19 Seputro, Dimas Nugroho Dwi; Dani, Andrea Tri Rian; Fauziyah, Meirinda; Adrianingsih, Narita Yuri; Putra, Fachrian Bimantoro
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 3 (2024): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v2i3.3767

Abstract

The Covid-19 pandemic has caused economic turmoil to become uncertain, affecting all aspects of Indonesian society's lives. This research aims to determine the relationship between the inflation rate, the transaction price of the last issuer of gold and the rupiah exchange rate that occurred in the period after the Covid-19 pandemic on the monthly interest rate of Bank Indonesia, both together and each variable on the monthly interest rate of Bank Indonesia. This research details the research steps starting from classical assumption test analysis, multiple linear regression, coefficient of determination to hypothesis testing. The research results show that from the inflation rate, the price of gold in dollars together has a significant influence on the dependent variable, namely the Bank Indonesia monthly interest rate. Inflation and gold prices in dollars partially have a significant influence on Bank Indonesia's monthly interest rate, while the rupiah exchange rate variable partially does not have a significant influence on Bank Indonesia's monthly interest rate. Inflation is the most dominant variable in Bank Indonesia's monthly interest rate after the Covid-19 pandemic.
Time Series Modeling with Intervention Analysis to Evaluate of COVID-19 Impact on the Stock Markets in Indonesia and Global Dani, Andrea Tri Rian; Putra, Fachrian Bimantoro
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 1 April 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i1.31081

Abstract

The COVID-19 pandemic began in December 2019 and led to significant disruptions in global financial markets. This study investigates the impact of the pandemic on stock indices in Indonesia (IHSG), the United States (DJI), and South Korea (KOSPI) using intervention analysis with a step function, which is designed to model permanent shifts in time series data following external shocks. Unlike traditional models such as ARIMA that assume data continuity, intervention models, particularly those using step functions, are highly suitable for assessing long-term economic disruptions and structural breaks caused by pandemics. This research uses daily stock price index data from January 10, 2019, to May 8, 2020, obtained from Yahoo Finance. The step function identifies the point of sustained change triggered by the initial COVID-19 outbreak and subsequent market reactions. The analysis shows that the pandemic caused significant and persistent declines across all observed indices. IHSG recorded its sharpest drop on March 26, 2020, while DJI and KOSPI experienced similar downward trends from March to April 2020. The forecasting performance of the intervention model was excellent, with Mean Absolute Percentage Error (MAPE) values of 0.72% for IHSG, 0.87% for DJI, and 0.82% for KOSPI, demonstrating high accuracy in modeling stock market behavior during crisis conditions.
I-Regs (Internet-Regression Analysis) as a Statistical Innovation in Nonparametric Regression Modeling Dani, Andrea; Budiantara, I Nyoman; Nuraini, Ulfa Siti; Yustanti, Wiyli; Sifriyani; Putra, Fachrian Bimantoro
Journal of Education Technology and Information System Vol. 1 No. 02 (2025): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jetis.v1i02.35288

Abstract

This research develops an information system based on the R-Shiny Dashboard, allowing users to perform nonparametric regression modeling. Internet-Regression Analysis (I-Regs) is the name of a dashboard that has been successfully developed. I-Regs provides a complete model library in regression analysis modeling, including parametric, nonparametric, and semiparametric regression. It is hoped that I-Regs can become a valuable tool for researchers, practitioners, and students in modeling regression analysis and solving various data analysis problems.
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. 
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.
A District/City Profiling Based on Poverty Indicators in East Nusa Tenggara Using the Centroid Linkage Algorithm Dani, Andrea Tri Rian; Candra, Yossy; Putra, Fachrian Bimantoro; Fauziyah, Meirinda
Zeta - Math Journal Vol 10 No 2 (2025): November
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/zeta.2025.10.2.81-91

Abstract

Poverty is a complex multidimensional phenomenon that significantly impacts human life. Poverty has always been a problem that the government has discussed regionally, centrally, and internationally. The issue of poverty is interesting to approach and analyze using a statistical approach, namely cluster analysis. Cluster analysis is used to group objects based on their level of similarity. In this research, the algorithm used is the Centroid Linkage Algorithm. The Centroid Linkage algorithm was chosen based on its advantages in the grouping process. Distance similarity measurement uses Squared Euclidean. The data used are district/city poverty indicators in East Nusa Tenggara Province. The analysis results show that two optimal clusters were obtained with their distinguishing characteristics. Hopefully, the results of this analysis can be used as a reference in formulating policies for alleviating poverty.
Co-Authors Candra, Yossy Chandra, Yossy Dani, Andrea Dani, Andrea Tri Rian Dimas Nugroho Dwi Seputro Fauziyah, Meirinda I Nyoman Budiantara M. Fathurahman Mislan NARITA YURI ADRIANINGSIH Ni'matuzzahroh, Ludia Novidianto, Raditya Nuraini, Ulfa Siti Regita Putri Permata Sifriyani, Sifriyani Sri Wigantono Tanur, Erwin Vita Ratnasari Wiyli Yustanti Zen, Muhammad Aldani