Article Per Year (5 Year)
p-Index From 2020 - 2025
1.325
P-Index
This Author published in this journals
All Journal Journal of Natural Sciences and Mathematics Research BAREKENG: Jurnal Ilmu Matematika dan Terapan Contemporary Mathematics and Applications (ConMathA) Tensor: Pure and Applied Mathematics Journal MATHunesa: Jurnal Ilmiah Matematika Journal Focus Action of Research Mathematic (Factor M) JMT (Jurnal Matematika dan Terapan)
Yudistira, Ira
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation Other

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
Prediction of Divorce Data in Pamekasan District Based on Comparison of Exponential Smoothing and Moving Average Yudistira, Ira; Romlah, Siti; Yulianto, Tony; faisol, Faisol; Mardianto, M.Fariz Fadillah
Tensor: Pure and Applied Mathematics Journal Vol 5 No 2 (2024): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol5iss2pp67-78

Abstract

Divorce is a form of breakdown in domestic or marital relationships which is characterized by separation. Based on the Indonesian Statistics report, the number of divorce cases in Indonesia will reach 516,334 cases in 2022. This number is up 15.31% compared to the previous year of 447,743 cases. East Java is ranked second as the province with the highest divorce cases, namely 102,065 cases throughout 2022. To know the development of divorce in the future, forecasting is needed to determine when an event will occur, an increase in the divorce rate, so that we can prepare what will be done to overcome the spike. the divorce rate. In this research, the methods used to predict the number of divorce cases in Pamekasan Regency are the Exponential Smoothing and Moving Average methods. single exponential smoothing method for both divorce lawsuits and divorce divorces with MAD values ​​= 10.40539 and 15.3366868, MSE = 449.0276211 and 181.0038, MAPE = 22.1859129 and 23.84152 and SE values ​​= 21.57911661 and 13, 70064 with a value of α=0.12 for contested divorce and α=0.26 for talak divorce.
Application of the ARIMA-GARCH Model for Forecasting Indonesia's Monthly Inflation Rate Anisa; Yudistira, Ira; Yulianto, Tony
Contemporary Mathematics and Applications (ConMathA) Vol. 7 No. 1 (2025)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v7i1.60263

Abstract

Inflation is one of the important aspects that is used as a benchmark to see economic growth and economic conditions in each country. Inflation has resulted in increasing public expenditure in meeting basic needs. Inflation must be controlled to maintain the economic stability of a country, including Indonesia. Therefore, there is a need for a model that can forecast the inflation rate in Indonesia. The aim of this research is to create a model that can predict future inflation levels so that it can help the government in determining policies related to controlling inflation in Indonesia. The data used is monthly inflation data in Indonesia for 19 years from March 2007- October 2023 in percentage form. The forecasting model used in this study is the ARIMA-GARCH model. The ARIMA model is a time series model used to forecast future data based on past data. While GARCH is a time series model used to overcome heteroscedasticity in the ARIMA model. Inflation data will be modeled using the ARIMA model and then continued by modeling the residuals using the GARCH model if heteroscedasticity occurs in the ARIMA model residuals. Based on data analysis that has been done, the best model for inflation forecasting cases in Indonesia is the ARIMA (2,0,2) - GARCH (0,1) model with a MAPE value of 17.78%.
COMPARISON OF SALINITY AND SEAWATER TEMPERATURE PREDICTIONS USING VAR AND BIRESPONSE FOURIER SERIES ESTIMATOR Faisol, Faisol; Ukhrowi, Putri; Mardianto, M. Fariz Fadillah; Yudistira, Ira; Kuzairi, Kuzairi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (510.591 KB) | DOI: 10.30598/barekengvol16iss4pp1465-1476

Abstract

Salinity is the concentration of dissolved salts in water. The salt in question is a variety of ions dissolved in water, including table salt (NaCl). Salinity and seawater temperature are one of the factors that affect salt production. The higher the NaCl content, the better the quality of the salt. Currently, people's salt production is still unable to meet the needs of national salt, especially industrial salt, because most of the quality of people's salt still does not meet the SNI criteria for industrial salt. Thus, it is necessary to predict the salinity and temperature of seawater to help determine the next steps or policies in improving the quality of people's salt. Predictions of salinity and seawater temperature were carried out by applying the Vector Autoregressive (VAR) Analysis method and nonparametric Fourier series regression with primary data of salinity and seawater temperature on the coast of Tlesah Tlanakan Beach, Pamekasan. The best model chosen is the model that has the smallest error size and the highest accuracy measure. The best models are nonparametric regression of the Fourier series of sine and cosine bases with the predicted result obtaining a MAPE value is 0.00496 and coefficient of determination is 100%.
PERAMALAN HARGA EMAS DAN PERAK DENGAN PENDEKATAN MODEL VECTOR AUTOREGRESSIVE MOVING AVERAGE (VARMA) Qutshiyah, Inayatul; Yudistira, Ira
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 2 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Investasi emas dan perak dianggap menjanjikan dalam jangka panjang, namun lentur harga yang tinggi membuat prediksi harga menjadi penting. Penelitian ini menggunakan model Vector Autoregressive Moving Average (VARMA) untuk meramalkan harga emas dan perak berdasarkan data triwulanan sepanjang tahun 2024. Model terbaik yang diperoleh adalah VARMA (1,1) dengan nilai RMSE rendah, yaitu 0,014 untuk emas dan 0,037 untuk perak. Prediksi untuk 13 periode ke depan menunjukkan tren kenaikan harga secara bertahap. MAPE peramalan emas sebesar 40,2% dan perak 26,6%, keduanya memenuhi syarat layak. Uji kointegritas menunjukkan adanya hubungan kointegrasi antara harga emas dan perak, sehingga model VARMA tidak cocok untuk perkiraan jangka panjang. Meski ada selisih dengan data aktual, model mampu menggambarkan tren secara konsisten, sehingga efektif untuk memperkirakan jangka pendek dalam pengambilan keputusan investasi.
Penerapan Model ARIMA-GARCH pada Peramalan Jumlah Kunjungan Wisatawan Mancanegara di Indonesia Anggraini, Yuyun; Subairi, Moh.; Yudistira, Ira
JMT (Jurnal Matematika dan Terapan) Vol. 7 No. 1 (2025): JMT (Jurnal Matematika dan Terapan)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jmt.7.1.2

Abstract

Indonesia memiliki potensi pariwisata yang besar, namun tingkat kunjungan wisatawan mancanegara masih berada di urutan keempat di antara negara-negara ASEAN. Peningkatan jumlah kunjungan ini penting untuk mendukung perekonomian, menciptakan lapangan kerja, dan memperbaiki infrastruktur. Penelitian ini bertujuan untuk menganalisis serta memprediksi kunjungan wisatawan mancanegara ke Indonesia pada periode Januari 2020 - Desember 2024 menggunakan pendekatan ARIMA-GARCH. Model ARIMA merupakan model time series yang digunakan untuk meramalkan data di masa depan berdasarkan data masa lalu. Sedangkan GARCH merupakan model time series yang digunakan untuk mengatasi heteroskedastisitas pada model ARIMA. Data wisman akan di modelkan dengan menggunakan model ARIMA kemudian dilanjutkan residualnya dengan menggunakan model GARCH apabila terjadi heteroskedastisitas pada model ARIMA. Berdasarkan analisis data yang dilakukan model terbaik untuk peramalan wisman di Indonesia adalah model ARIMA (1,1,2) – GARCH (0,3) dengan nilai RMSE sebesar 274.0599.
Comparison modeling of the number population who have been vaccined in East Java using the biresponse Fourier series estimator method with the trend function Yudistira, Ira; Rohman, Naylur; Mardianto, M Fariz Fadillah; Kuzairi
Journal Focus Action of Research Mathematic (Factor M) Vol. 6 No. 1 (2023)
Publisher : Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/factor_m.v6i1.685

Abstract

Vaksinasi adalah proses pemberian vaksin pada tubuh manusia yang bertujuan untuk meningkatkan kekebalan tubuh secara aktif terhadap suatu penyakit dan tidak menjadi sumber penularan penyakit tersebut. Vaksinasi massal merupakan sebuah keharusan yang harus dipenuhi untuk menanggulangi permasalahan wabah Covid-19 yang melanda seluruh dunia termasuk Indonesia. Pada tahun 2021 pelaksanaan vaksinasi Covid-19 di Jawa timur baru mencapai 50% dari total sasaran yang divaksin. Kekebalan imunitas tercapai ketika 70% penduduk telah divaksin. Sementatra ini pelaksanaan program vaksinasi pemerintah sudah mencapai pada vaksin dosis kedua. Berdasarkan uraian tersebut peneliti bertujuan untuk membandingkan pemodelan jumlah penduduk yang telah divaksin dosis pertama dan kedua menggunakan metode deret Fourier Birespon dengan Fungsi Tren. Kriteria kebaikan model yang digunakan adalah nilai GCV dan MSE terkecil, serta nilai koefisien determinasi tertinggi. Model yang diperoleh dalam penelitian ini adalah model dengan basis sinus cosinus. Model tersebut mempunyai nilai GCV dan MSE lebih kecil dibandingkan nilai GCV dan MSE pada basis cosinus dan sinus. Koefisien determinasi model tersebut sebesar menunjukkan nilai yang besar.  Vaccination is a process carried out by the human body that aims to increase the body's active immunity against a disease so that people who are vaccinated will not get sick. The Covid-19 outbreak hit the whole world, including Indonesia. Currently, the implementation of the Covid-19 vaccination in East Java has only reached 50% of the total target being vaccinated. The requirement to achieve immunity must be that 70% of the population has been vaccinated. Based on this description, the researcher aims to compare the modeling of the population that has been vaccinated with the first and second doses using the Fourier series bi-response method with a trend function. The criteria for the goodness of the model in this study used small GCV and MSE values and a high coefficient of determination. The model has smaller GCV and MSE values ​​than the cosine and sine basis. The coefficient of determination of the model shows a large value.
Prediction of seawater salinity based on comparison of truncated spline estimators, Fourier Series and Kernel Faisol, Faisol; Mardianto, M. Fariz Fadillah; Yudistira, Ira; Yulianto, Tony; Hasanah, Sarmiatul
Journal of Natural Sciences and Mathematics Research Vol. 9 No. 1 (2023): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Salinity is one of the factors that affect salt production. Salinity is defined as the level of saltiness or too much salt in water. The salt in question is a variety of ions dissolved in water, including table salt (NaCl). The higher the level of NaCl contained, the better the quality of the salt formed. This low quality causes Indonesia to import salt, both consumption salt and industrial salt. Because most of the quality of salt still does not meet the criteria of SNI. For this reason, it is necessary to predict the salinity of seawater to help determine the next steps or policies in improving the quality of salt in Indonesia, especially in the Madura area. This research is examined in the form of a nonparametric regression curve estimator with a truncated spline estimator approach, Fourier series and kernel. From the comparison results, the best model for predicting seawater salinity is the estimator of the Fourier series base sine cosine with an oscillation parameter (k) of 2 with a GCV value of 5.017987 and MSE and a coefficient of determination of 0.06299933 and 94.64373%. So the prediction results obtained in this study are close to accurate with MAPE values of 0.07225208%, MSE of 0.0001441417 and coefficient of determination of 99.99%.
Co-Authors Anggraini, Yuyun Anisa Faisol Faisol Hasanah, Sarmiatul Kuzairi M. Fariz Fadillah Mardianto Muhammad Luthfi Qutshiyah, Inayatul Rohman, Naylur Siti Romlah Subairi, Moh. Tony Yulianto Ukhrowi, Putri