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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
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Pengenalan Pojok Statistik Sejak Dini dan Ilmu Data Sains Bagi Siswa dan Guru di SMAN Kota Samarinda Meirinda Fauziyah; Sifriyani Sifriyani; Sri Wahyuningsih; Suyitno Suyitno; Andrea Tri Rian Dani; Siti Mahmuda; Hadi Koirudin
Journal of Research Applications in Community Service Vol. 2 No. 3 (2023): 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.v2i3.2263

Abstract

Pendidikan merupakan bentuk usaha sadar seseorang untuk mengembangkan potensi diri agar memiliki kekuatan spiritual, keagamaan, serta keterampilan diri. Pada masa kini keterampilan diri terfokus dalam urgensi data yang banyak dibutuhkan di sektor industri dengan keahlian menganalisis masalah dan menghasilkan insight untuk menjawab kepentingan manusia di masa depan dengan mengenal ilmu data sains. Data sains merupakan cabang ilmu gabungan dari statistika, pendekatan sains, Artificial Intelligence (AI) untuk menganalisis sebuah big data sampai menghasilkan kesimpulan yang mudah dipahami. Tujuan kegiatan PKM ini memberikan pemahaman informasi pojok statistik sebagai wadah ilmu statistik kepada siswa dan guru sejak dini, membagikan informasi pengembangan ilmu data sains terkini menjadi seorang data scientist. Pelaksanaan kegiatan ini menggunakan metode Participatory Learning and Action (PLA) dengan melibatkan siswa/siswi dan guru. Hasil dari kegiatan ini menunjukkan bahwa terdapat perbedaan pemahaman sebelum dan setelah diberikan pemahaman ilmu data sains.
Aplikasi Model ARIMAX dengan Efek Variasi Kalender untuk Peramalan Trend Pencarian Kata Kunci “Zalora” pada Data Google Trends Andrea Tri Rian Dani; Sri Wahyuningsih; Fachrian Bimantoro Putra; Meirinda Fauziyah; Sri Wigantono; Hardina Sandariria; Qonita Qurrota A'yun; Muhammad Aldani Zen
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15793

Abstract

ARIMAX is a method in time series analysis that is used to model an event by adding exogenous variables as additional information. Currently, the ARIMAX model can be applied to time series data that has calendar variation effects. In short, calendar variations occur due to changes in the composition of the calendar. The purpose of this study is to apply the ARIMAX model with the effects of calendar variations to forecast search trends for the keyword "Zalora". Data were collected starting from January 2018 to November 2022 in the form of a weekly series. Based on the results of the analysis, the ARIMAX model is obtained with calendar variation effects with ARIMA residuals (1,1,1). Forecasting accuracy using the Mean Absolute Percentage Error (MAPE) of 10.47%. Forecasting results for the next 24 periods tend to fluctuate and it is estimated that in April 2023 there will be an increase in search trends for the keyword "Zalora".
Aplikasi Pengelompokan Data Runtun Waktu dengan Algoritma K-Medoids Muhammad Aldani Zen; Sri Wahyuningsih; Andrea Tri Rian Dani
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15864

Abstract

The development of information technology will always be accompanied by the storage and accumulation of massive quantities of digital information. Cluster analysis is one of many data processing problems that require the selection of an appropriate algorithm when dealing with large data sets. Cluster analysis is a collection of techniques for dividing a set of observation objects into clusters. Cluster analysis is applicable to time series data, the processing of which differs slightly from that of cross-section data. Clustering time series is a technique for processing multivariable time series data. K-Medoids is the clustering algorithm used for time series clustering. The objective of this study is to obtain optimal K-values in determining the number of clusters based on silhouette coefficients and grouping outcomes using the K-Medoids algorithm. In this study, the dynamic time-warping distance is utilized as the similarity metric. This study provides cooking oil price data for 34 Indonesian provinces from October 2017 to October 2022. The optimal K value is determined for two clusters based on the results of the analysis, with 19 provinces joining cluster 1, where the cluster with cooking oil prices was below cluster 2 and 15 provinces joining cluster 2 which is the cluster with the highest cooking oil prices.
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 .
Pengelompokkan Data Runtun Waktu menggunakan Analisis Cluster Dani, Andrea Tri Rian; Wahyuningsih, Sri; Rizki, Nanda Arista
EKSPONENSIAL Vol 11 No 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (673.538 KB) | DOI: 10.30872/eksponensial.v11i1.642

Abstract

The export value of East Kalimantan Province has big data conditions with time series and multivariable data types. Cluster analysis can be applied to time series data, where there are different procedures and grouping algorithms compared to grouping cross section data. Algorithms and procedures in the cluster formation process are done differently, because time series data is a series of observational data that occur based on a time index in sequence with a fixed time interval. The purpose of this research is to obtain the best similarity measurement using the cophenetic correlation coefficient and get the optimal c-value using the silhouete coefficient. In this study, the grouping algorithm used is a single linkage with four measurements of similarity, namely the Pearson correlation distance, euclidean, dynamic time warping and autocorrelation based distance. The sample in this study is the data on the export value of oil and non-oil commodities in East Kalimantan Province from January 2000 to December 2016 consisting of 10 variables. Based on the results of the analysis, the distance of the best similarity measurement in clustering the export value of oil and non-oil commodities in East Kalimantan Province is the dynamic time warping distance with the optimal c-value of 3 clusters.
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.
Pengelompokan Provinsi Berdasarkan Indikator Ekonomi, Pendidikan, Kesehatan, dan Kriminalitas di Indonesia Menggunakan Algoritma Centroid Linkage Candra, Yossy; Goejantoro, Rito; Dani, Andrea Tri Rian
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 12 Issue 1 June 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i1.24887

Abstract

With its rich cultural diversity and abundant natural resource potential, Indonesia still faces various social science problems. Economic inequality, low quality of education, limited access to health, and high crime rates are social problems that hit various provinces in Indonesia. This research was conducted to group provinces in Indonesia based on social indicators, which include economy, education, health, and crime. This research uses cluster analysis with the Centroid Linkage algorithm to group provinces in Indonesia. The Centroid Linkage algorithm was chosen because of its advantages in producing optimal grouping. Test cluster validity using the Silhouette Coefficient (SC). The case studies used are variables that are thought to be related to economic, health, education, and crime problems in 34 provinces in Indonesia in 2021. Based on the analysis, the grouping results using the Centroid Linkage algorithm show that the optimal number of clusters is 2, with an SC value of 0.538. Cluster 1 consists of 33 provinces, and Cluster 2 consists of only one province, DKI Jakarta.
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).
Data Speaks: District Clustering Map to Reveal Basic Education Problems in Samarinda City Oroh, Chiko Zet; Dani, Andrea Tri Rian; Muawanah, Chusnul; Sitinjak, Jesselin Paskalis; Ibaad, Muhammad Irsadul; Mislan, Mislan; Kosasih, Raditya Arya
Asian Journal of Science, Technology, Engineering, and Art Vol 2 No 6 (2024): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v2i6.3938

Abstract

Education is an effort to create a learning environment and educational process that encourages the development of students' potential. One of the statistical methods that can be used in the field of education is cluster analysis. Average linkage is a hierarchical clustering algorithm that groups objects based on the average distance between objects in different clusters. In this study, sub-districts were grouped based on education indicators at the primary/elementary level in Samarinda City in 2023. The results of this research obtained 2 clusters that were the most optimal because they had the highest Silhouette coefficient value. Cluster 1 contains the subdistricts of Samarinda Ulu and Sungai Kunjang, while cluster 2 contains the subdistricts of North Samarinda, Palaran, Sungai Pinang, Sambutan, Loa Janan Ilir, Samarinda Ilir, Samarinda Seberang, and Samarinda Kota. Cluster 1 has an advantage over cluster 2 in several aspects of education. Cluster 1 shows a higher average in terms of the number of students, the number of classrooms, the number of institutions, the number of certified teachers, and the number of A-accredited schools at the primary/secondary level in Kota Samarinda in 2023.
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