Article Per Year (5 Year)
p-Index From 2020 - 2025
0.817
P-Index
This Author published in this journals
All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) MAUIZHAH JURNAL KAJIAN KEISLAMAN PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Quadratic: Journal of Innovation and Technology in Mathematics and Mathematics Education
Zuliana, Sri Utami
UIN Sunan Kalijaga
Religion Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
PENENTUAN MODEL TERBAIK REGRESI RIDGE DAN TERAPANNYA Sri Utami Zuliana
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 10 No 2 (2018): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2018.10.2.2843

Abstract

Ridge regression is one of penalized regression methods. Penalized regression methods are usually used for solving the problem of multicollinearity. The best model in ridge regression has been chosen by some previous techniques. In the techniques there is bias-variance trade-off. In this paper, Schall algorithm will be applied for choosing the best model. Schall algorithm is faster because it only needs a few iteratives to be convergence.
PENENTUAN MODEL TERBAIK REGRESI RIDGE DAN TERAPANNYA Sri Utami Zuliana
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 10 No 2 (2018): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2018.10.2.2843

Abstract

Ridge regression is one of penalized regression methods. Penalized regression methods are usually used for solving the problem of multicollinearity. The best model in ridge regression has been chosen by some previous techniques. In the techniques there is bias-variance trade-off. In this paper, Schall algorithm will be applied for choosing the best model. Schall algorithm is faster because it only needs a few iteratives to be convergence.
FORECASTING USING SARIMA AND BAYESIAN STRUCTURAL TIME SERIES METHOD FOR RANGE SEASONAL TIME MUHAMMAD RIZAL; Sri Utami Zuliana
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.402

Abstract

Data containing seasonal patterns, the SARIMA and Bayesian Structural Time Series methods, are time series methods that can be used on this type of data. This research aims to determine the steps of the SARIMA model and Bayesian Structural Time Series, applying the SARIMA model and Structural Bayesians Time Series, get the forecasting results of the SARIMA model and Bayesian Structural Time Series with MAPE measurements. The research method used is a quantitative method applied to data on the number of PT KAI train passengers in the Java region for 2006-2019. The results of this research show that the best model for forecasting the number of PT KAI train passengers in the Java region in 2006-2019 is SARIMA (2,1,0)(0,1,2)[12] with a MAPE value of 4.77% compared to the Bayesian method structural time series [12] namely 5.25%.
Manajemen Program Studi Matematika UIN Sunan Kalijaga yang Profesional Berbasis Akreditasi Internasional ASIIN Zuliana, Sri Utami; Futhona, Aulia Khifah
Mau`izhah : Jurnal Kajian Keislaman Vol 14 No 1 (2024)
Publisher : Sekolah Tinggi Ilmu Tarbiyah (STIT) Syekh burhanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55936/mau`izhah.v14i1.192

Abstract

Penilaian ASIIN adalah pengakuan internasional dalam bidang sains, termasuk Matematika. Kriteria yang ditekankan dalam proses akreditasi ASIIN meliputi mahasiswa, struktur program pendidikan, prestasi lulusan, upaya keberlanjutan, rancangan kurikulum, fasilitas, dan dukungan institusional. Evaluasi ini mengikuti pendekatan Plan Do Check Act (PDCA) untuk memastikan peningkatan terus-menerus dalam mutu dan kualitas program pendidikan.
KALMUL Software Assited by GeoGebra (A New Media for Learning Multivariable Calculus) Utami Zuliana, Sri; Arfinanti, Nurul; Damar Jati, Wahyu; Ramadhan, Fadlilah Aziz
Quadratic: Journal of Innovation and Technology in Mathematics and Mathematics Education Vol. 3 No. 1 (2023): April 2023
Publisher : Pusat Studi Pengembangan Pembelajaran Matematika Sekolah UIN Sunan Kalijaga Yogyakarta Jl. Marsda Adisucipto, Yogyakarta 55281

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/quadratic.2023.031-05

Abstract

Multivariable calculus is one of the compulsory subjects for study programmes in the fields of science and technology. The graphical approach to of two variable calculus written in a book or board usually makes it difficult for students to understand. This research aims to build a tool for learning multivariable calculus using GeoGebra. GeoGebra provides three-dimensional visualization facilities through the GeoGebra 3D Graphing Calculator software. This software has an android application so that it can be accessed via a smart phone. This research developed learning media for multivariable calculus using GeoGebra software in the form of an android application. The lecture material is limited to multivariable derivative. The research method used in this study is research and development (R & D) with development of 4-D models (Four D) for research design. The design of this study includes four main stages, namely the definition phase, the design stage, the development stage, and the dissemination stage. The results of validating media products are in good criteria and the results of small and large scale tests are very good criteria.
MODEL SELECTION FOR B-SPLINE REGRESSION USING AKAIKE INFORMATION CRITERION (AIC) METHOD FOR IDR-USD EXCHANGE RATE PREDICTION Pratiwi, Indriani Wahyu Nur; Zuliana, Sri Utami
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp25-34

Abstract

Exchange rate data is a collection of information about the exchange rate the foreign currency which collected by time. Autoregressive Integrated Moving Average (ARIMA) is a well-known time series analysis. Several assumptions that need to be checked before running the ARIMA model are stationarity, normality, and white noise. B-spline regression is a method of modeling time series data without considering assumptions. This research aims to create a forecasting model for Rupiah exchange rate against US Dollar using B-spline regression. The B-spline regression model was generated with a combination of degrees two to four and a maximum of four knots. After that, the optimal model is selected using the Akaike Information Criterion (AIC) score. The performance of the selected model is validated using Mean Absolute Percentage Error (MAPE) values. The optimal degree is 3 (quadratic) and the optimal number of knot points is two-knot points with an AIC value of 857.8322 and a MAPE value of 0.0148376. The best model is:
Co-Authors Aulia Khifah Futhona Damar Jati, Wahyu MUHAMMAD RIZAL Nurul Arfinanti Pratiwi, Indriani Wahyu Nur Ramadhan, Fadlilah Aziz