Article Per Year (5 Year)
p-Index From 2021 - 2026
4.115
P-Index
This Author published in this journals
All Journal PROSIDING SEMINAR NASIONAL Media Statistika Jurnal Ilmu Dasar Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Edukasi dan Penelitian Informatika (JEPIN) Proceeding SENDI_U Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Variance : Journal of Statistics and Its Applications LOSARI: Jurnal Pengabdian Kepada Masyarakat Jurnal Litbang Edusaintech Journal of Data Insights Prosiding Seminar Nasional Unimus Jurnal Meteorologi dan Geofisika
Tiani Wahyu Utami
Program Studi Statistika, Universitas Muhammadiyah Semarang
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

Published : 64 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 64 Documents
Search

 3   4   5   6   7 
Implementation of K-Means Algorithm to Group Age of Cardiovascular Disease Patients: Impelementasi Algoritma K-means untuk Mengelompokkan Usia Penderita Penyakit Kardiovaskular Rahmi, Mulya Asy-syifa; Arum, Prizka Rismawati; Wahyu Utami, Tiani
Journal of Data Insights Vol 3 No 1 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i1.216

Abstract

Cardiovascular disease, including coronary heart disease, peripheral arteries and heart failure, is a serious disease that is the leading cause of death globally. Risk factors such as high blood pressure, dyslipidemia, smoking, diabetes, and obesity contribute to the development of this disease. This study aims to group cardiovascular disease sufferers based on age using the k-means clustering method with optimization of the k value using the elbow method. The data used comes from more than 35,000 preprocessed observations. The analysis results show that the optimal number of clusters is five. Data preprocessing succeeded in cleaning the data from missing values, and the elbow method helped determine the number of clusters that were relevant for age grouping of cardiovascular disease sufferers. The results of this grouping can be used for further analysis in efforts to prevent and manage cardiovascular disease.
Comparison of Holt-Winters Exponential Smoothing (HWES) and Singular Spectrum Analysis (SSA) Methods in Forecasting the Number of Passengers at PT KAI in Indonesia: Perbandingan Metode Holt-Winters Exponential Smoothing (HWES) Dan Singular Spectrum Analysis (SSA) Pada Peramalan Jumlah Penumpang PT KAI di Indonesia Ulinuha, Samikoh; Wahyu Utami, Tiani; Arum, Prizka Rismawati; Purwanto, Dannu
Journal of Data Insights Vol 2 No 2 (2024): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v2i2.654

Abstract

Penelitian ini mengkaji penerapan dua metode peramalan, yaitu Holt Winters Exponential Smoothing (HWES) dan Singular Spectrum Analysis (SSA), dalam meramalkan jumlah penumpang di PT Kereta Api Indonesia. Hasil penelitian menunjukkan bahwa penerapan metode HWES dengan model additive menghasilkan nilai parameter pemulusan optimal dengan alpha , beta dan gamma model ini memiliki nilai MAPE sebesar 10.75%. Sementara itu, pada HWES model multiplicative menghasilkan nilai parameter pemulusan alpha , beta dan gamma , menghasilkan nilai MAPE 14.50%. Metode SSA dengan window length menghasilkan nilai MAPE 13.33%. Perbandingan nilai MAPE anatara metode HWES additive, HWES multiplicative dan SSA menunjukkan bahwa HWES additive lebih unggul dengan MAPE sebesar 10.75%. Peramalan jumlah penumpang Kereta Api Indonesia menggunakan metode terbaik Holt Winters Exponential Smoothing Additive untuk periode Januari hingga Desember 2024 memperlihatkan variasi jumlah penumpang terendah pada bulan Agustus dan tertinggi pada bulan Januari.
MODELLING SCHOOL DROPOUT RATES IN WEST JAVA PROVINCE WITH MIXED GEOGRAPHICALLY TEMPORALLY WEIGHTED REGRESSION Rismawati Arum, Prizka; Maharani, Endang Tri Wahyuni; Fatimahthus Zahra, Diandra; Utami, Tiani Wahyu
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0123-0136

Abstract

School dropout is a problem in the education sector that can hinder the progress of the quality of human resources and the competitiveness of the nation. West Java Province has the highest school dropout rates among all provinces in Indonesia. The data on school dropout rates exhibit spatial and temporal variations. Additionally, the potential differences between regions allow for the occurrence of diverse data that can be addressed locally and globally. Mixed Geographically Temporally Weighted Regression (MGTWR) is an extension of the GWR method that can produce parameters that are both local and global for each location and time. So, the objective of this research is to obtain factors that have a local and global influence on the school dropout rate in West Java Province using the Mixed Geographically Temporally Weighted Regression method. In this study, the data used includes school dropout rates in West Java Province from 2018 to 2022. The data used is sourced from the official statistical data website of the Ministry of Education, Culture, Research and Technology, and the official website of the West Java Province Central Statistics Agency. The results of the MGTWR modeling show that globally influential variables include the percentage of the poor population, population density, unemployment rate, and average length of schooling, which have local effects. Based on the MGTWR model, the Fixed Kernel Gaussian weighting function is the best model for modeling school dropout rates in regencies/cities in West Java, with an RMSE value of 0.0755 and R-squares of 92.09%.
Analysis of DHF Patients Based on Laboratory Examination Results with Nonparametric Approach Utami, Tiani Wahyu; Haris, M. Al; Salma, Nadia Khoirunnafisa
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 1 (2026): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i1.33609

Abstract

The dengue virus, which is spread by the Aedes aegypti mosquito, is the cause of Dengue Hemorrhagic Fever (DHF). In the city of Semarang, there was a threefold increase in cases of DHF compared to previous years. This type of research is quantitative research because it produces function that describes the relationship to what extent changes in predictor variable are related to changes in response variable to understand the level of association. Modelling the link between response and predictor factors is the aim of this study. Platelet as the response variable and hemoglobin and leukocyte as the predictor variables, so that the obtained model can be used as a prediction, especially regarding the dynamics of platelet changes influenced by hemoglobin and leukocytes. The pattern of the relationship between platelets and the suspected influencing factors does not form specific pattern, so the Nonparametric Spline method is used in this study. The Spline method is chosen for its flexibility; this model tends to independently seek data estimates, the completion of this study using R software. In the Spline method, there are knot points indicating data changes. The selection of optimum knot points is done by choosing the minimum GCV value The secondary data used came from Roemani Muhammadiyah Hospital's 2023 medical records. The data include platelet count, hemoglobin, and leukocyte. Based on the modeling conducted using truncated spline, the optimum knot points on the linier spline are determined to be 3 knot points with a coefficient determination of 83.58%. The coefficient of determination of 83.58% indicating that 83.58% of the variation in response variable can be explained by predictor variables studied in the regression model. This value indicates that predictor variables have a strong ability to explain changes in response variable.
Co-Authors Abdul Rohman Agus Rusgiyono Aisyah Lahdji, Aisyah Alan Prahutama Alan Prahutama Alwan Fadlurohman Amrullah, Setiawan Anissatush Sholiha Arianti, Irma Arini Rizky Wahyuningtyas Aulia, Syifa Aura Hisani, Zahra Ayu Wulandari Azqia Fajriyani Biru, Pelangi Langit Dannu Purwanto Devi Nurlita Dewi Ratnasari Wijaya Dhani, Oktaviana Rahma Dheanyta Alif Shafira Diana Wahyu Safitri Dwi Ispriyanti Eko Yuliyanto, Eko Elvia Nanda Sofiyanti Endah Suryaningsih Endang Tri Wahyuni Maharani Fathikatul Arnanda Fatimahthus Zahra, Diandra Fatmawati Nurjanah Fauzi, Fatkhurokhman Hanif Nur Ibrahim Haris, M. Al Hasbi Yasin Hikmah Nur Rohim, Febrian Iffah Norma Hidayati Ihsan Fathoni Amri Iis Widya Harmoko Iis Widya Harmoko, Iis Widya Imaroh Izzatun Indah Manfaati Nur Indah Sulistiya Indra Firmansyah Iqbal Kharisudin Ismawati - Juwita Rahayu Laila Khoirun Nisa Lia Miftakhul Janah M. Al Haris M. Saifudin Nur Martyana Prihaswati Maulana Afham Mifta Luthfin Alfiani Moh Yamin Darsyah Moh Yamin Darsyah Moh. Yamin Darsyah Nila Amelinda Putri Nur Chamidah Nursamsiah Nursamsiah Pranandira Rilvandri, Quinsy Prizka Rismawati Arum Rahma Dhani, Oktaviana Rahman, Budiono Rahmi, Mulya Asy-syifa Rizma Novinda Puteri Rochdi Wasono Rochdi Wasono Roosyidah, Nila Ayu Nur Salma, Nadia Khoirunnafisa Salmaa Fauziah Septi Winda Utami Setiayani, Wiwik Silvia Tri Wahyuni Sri Kustiara Sudarno Sudarno Sugito Sugito Suherdi, Andri Suparti Suparti Suparti Suparti Suparti, S. Syaifullah, Ahmad Reyhan Toha Saifudin Ujang Maulana Ujiati Suci Rahayu Ulinuha, Samikoh Vega Zayu Varima Velia Arni Widyasari Wahyu Putri Pratiwii Wisudawati, Dinda Tri Yulianita, Tanti Yuliardi, Fahrul Raditiar Yusnia Kriswanto