Article Per Year (5 Year)
p-Index From 2020 - 2025
1.686
P-Index
This Author published in this journals
All Journal Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI CAUCHY: Jurnal Matematika Murni dan Aplikasi Journal of Mathematical and Fundamental Sciences Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Procuratio : Jurnal Ilmiah Manajemen Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Jurnal Ilmiah Sains Indonesian Journal of Applied Mathematics
Utriweni Mukhaiyar
Institut Teknologi Bandung
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Mathematics Physics Other

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 12 Documents
Search

 1   2 
FORECASTING FARMER EXCHANGE RATE IN CENTRAL JAVA PROVINCE USING VECTOR INTEGRATED MOVING AVERAGE Trimono, Trimono; Sonhaji, Abdulah; Mukhaiyar, Utriweni
MEDIA STATISTIKA Vol 13, No 2 (2020): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.13.2.182-193

Abstract

Farmer Exchange Rate (FER) is an indicator that can be used to measure the level of farmers welfare. For every agriculture sector, FER is affected by the historical price of harvest from the corresponding sector and historical prices of other agriculture sectors. In Central Java Province, rice & palawija, horticulture, and fisheries are the largest agriculture sectors which is the main livelihood for most of the population. FER forecasting is a crucial thing to determine the level of farmers welfare in the future. One method that can be used to predict the value of a variable that is influenced by the historical value of several variables is Vector Time Series. An empirical study was conducted using FER data from the rice & palawija, horticulture and fisheries sectors for January 2011-June 2017 in Central Java Province. The results obtained show that by using the VIMA(2.1) model, the FER prediction was very accurate, with MAPE values were 1.91% (rice & palawija sector), 2.44% (horticulture sector), and 2.18% (fisheries sector).
PREDIKSI HARGA EMAS DENGAN PENDEKATAN MODEL DERET WAKTU ARIMA Sunyanti Sunyanti; Utriweni Mukhaiyar
Procuratio : Jurnal Ilmiah Manajemen Vol 7 No 4 (2020): Procuratio : Jurnal Ilmiah Manajemen
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

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

Abstract

The gold is one of the minerals with high value of high value, both in term of price and usage. Investing in gold generally has a lot of profit for the investor. To get optimum benefit, the investor hope to get a low price at purchase and expensive price at sale. The observation of gold price based on the time forms a time series. The method used in predicting the price of gold based on sudden rising gold price movements can be analyzed by the ARIMA time model.The purpose of this research is to know the results of gold price predictions in the future so as to facilitate the investors to make decisions, when the right time in the investment.Based on the data that has been analyzed in this study that gold price data is not stationary, so that it is recommissioned with a predefined model and obtained best results on the ARIMA model (2, 2.0). Emas adalah salah suatu bahan galian yang bernilai tinggi, baik dari sisi harga maupun sisi penggunaan. Berinvestasi emas pada umumnya banyak mendatangkan keuntungan bagi pelakunya. Untuk mendapatkan keuntungan yang optimal, pelaku investasi emas berharap mendapatkan harga yang rendah saat pembelian dan harga yang mahal saat penjualan. Pengamatan harga emas berdasarkan waktu membentuk suatu deret waktu. Metode yang digunakan dalam memprediksi harga emas berdasarkan pergerakan harga emas yang naik turun secara tiba-tiba dapat dianalisis dengan model deret waktu ARIMA. Tujuan dari penelitian ini adalah untuk mengetahui hasil prediksi harga emas di waktu mendatang sehingga dapat memudahkan para investor untuk mengambil keputusan, kapan waktu yang tepat dalam investasi. Berdasarkan dari data yang telah dianalisis dalam penelitian ini bahwa data harga emas tidak stasioner, sehingga distasionerkan dengan model yang telah ditentukan dan diperoleh hasil terbaik pada model ARIMA (2,2,0).
A New Procedure for Generalized STAR Modeling using IAcM Approach Utriweni Mukhaiyar; Udjianna S. Pasaribu
Journal of Mathematical and Fundamental Sciences Vol. 44 No. 2 (2012)
Publisher : Institute for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.sci.2012.44.2.7

Abstract

A new procedure of space-time modeling through the Invers of Autocovariance Matrix (IAcM) is proposed. By evaluating the IAcM behaviors on behalf of the Generalized Space-Time Autoregressive (GSTAR) process stationarity, we may find an appropriate model to space-time data series. This method can complete the Space-Time ACF and PACF methods for identifying space-time models. For study case, we apply the GSTAR models to the monthly tea production of some plantations in West Java, Indonesia.
Error Assumptions on Generalized STAR Model Yundari Yundari; Udjianna Sekteria Pasaribu; Utriweni Mukhaiyar
Journal of Mathematical and Fundamental Sciences Vol. 49 No. 2 (2017)
Publisher : Institute for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.math.fund.sci.2017.49.2.4

Abstract

For GSTAR models, the least squares estimation method is commonly used since errors are assumed be uncorrelated. However, this method is not appropriate when errors are correlated, either in time or spatially. For these cases, the generalized least squares (GLS) method can be applied. GLS is more powerful since it has an error parameter that can act as a controller of the model to produce an efficient estimator. In this study, R Software was used to estimate GSTAR parameters. The resulted model was applied to real data, i.e. the monthly tea production of five plantations in West Java, Indonesia. The best model for forecasting was the GSTAR(1;1) model with temporally correlated error assumption.
Konfigurasi Spasial Potensi Kekuatan Gempa Bumi Menggunakan Metode Kriging Semivariogram Anisotropik 3D Salim Salim; Utriweni Mukhaiyar
SAINTIFIK Vol 5 No 2 (2019): Saintifik: Jurnal Matematika, Sains, dan Pembelajarannya
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (392.196 KB) | DOI: 10.31605/saintifik.v5i2.225

Abstract

Indonesia terletak pada pertemuan empat lempeng tektonik, yaitu lempeng Eurasia, lempeng Indo-Australia, lempeng Filipina, dan Samudera Pasifik. PergerIndonesia terletak pada pertemuan empat lempeng tektonik, yaitu lempeng Eurasia, lempeng Indo-Australia, lempeng Filipina, dan Samudera Pasifik. Pergerakan relatif dari lempeng tektonik tersebut menimbulkan terjadinya gempa bumi. Tujuan dilakukan penelitian ini adalah memberikan gambaran spasial lokasi gempa di sekitar observasi yang tidak diketahui dengan metode Ordinary Kriging (OK) melalui semivariogram anisotropik. Data gempa bumi diperoleh dari website IRIS (Incorporated Research Institutions For Seismology), yang pernah terjadi di wilayah Indonesia yaitu di Laut Banda, pada tanggal 31 Januari 2008. Dengan asumsi stasioner, proses pencocokan digunakan dengan model semivariogram Eksponensial. Hasil analisis Ordinary Kriging (OK) melalui semivariogram anisotropik dalam tiga dimensi dari potensi kekuatan gempa bumi diperoleh gambaran spasial bahwa setiap hasil estimasi dipengaruhi perubahan arah dan data observasi di sekitarnya dengan arah sudut dan . Jika lokasi yang akan diestimasi berada di sekitar data observasi dengan rataan cukup besar, maka hasil estimasi akan mendekati nilai data observasi sebaliknya, jika lokasi yang akan diestimasi berada jauh dari data observasi dengan rataan cukup besar maupun kecil, maka hasil estimasi akan berbeda jauh dengan nilai data observasi.akan relatif dari lempeng tektonik tersebut menimbulkan terjadinya gempa bumi. Tujuan dilakukan penelitian ini adalah memberikan gambaran spasial lokasi gempa di sekitar observasi yang tidak diketahui dengan metode Ordinary Kriging (OK) melalui semivariogram anisotropik. Data gempa bumi diperoleh dari website IRIS (Incorporated Research Institutions For Seismology), yang pernah terjadi di wilayah Indonesia yaitu di Laut Banda, pada tanggal 31 Januari 2008. Dengan asumsi stasioner, proses pencocokan digunakan dengan model semivariogram Eksponensial. Hasil analisis Ordinary Kriging (OK) melalui semivariogram anisotropik dalam tiga dimensi dari potensi kekuatan gempa bumi diperoleh gambaran spasial bahwa setiap hasil estimasi dipengaruhi perubahan arah dan data observasi di sekitarnya dengan arah sudut dan . Jika lokasi yang akan diestimasi berada di sekitar data observasi dengan rataan cukup besar, maka hasil estimasi akan mendekati nilai data observasi sebaliknya, jika lokasi yang akan diestimasi berada jauh dari data observasi dengan rataan cukup besar maupun kecil, maka hasil estimasi akan berbeda jauh dengan nilai data observasi.
The Generalized STAR Modeling with Heteroscedastic Effects Utriweni Mukhaiyar; Syahri Ramadhani
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 7, No 2 (2022): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i2.13097

Abstract

In general, the Generalized Space Time Autoregressive (GSTAR) model of space-time assumes constant error variance. In this study, a GSTAR model was built with an error variance that was not constant or had a heteroscedasticity effect, namely the combination of GSTAR–Autoregressive Conditional Heteroskedasticity (ARCH). The parameters of the GSTAR–ARCH model were estimated using the Generalized Least Square (GLS) method to obtain an efficient parameter estimation. As a case study, the GSTAR–ARCH model was applied to the daily mean wind speed data of New Orleans, Florida and Mississippi to predict the occurrence of Hurricane Katrina that occurred in 2005. The results obtained show that the GSTAR model (3;0,0,1)–ARCH(1) predicts Hurricane Katrina very well.
Analisis Faktor-Faktor yang Memengaruhi Angka Partisipasi Kasar SMA/Sederajat di Indonesia Menggunakan Regresi Ridge Utriweni Mukhaiyar; Ferdy Rontos; Kurnia Handoko; Salma Kardiyanti
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 10 Issue 2 December 2022
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/euler.v10i2.15903

Abstract

One indicator of education in Indonesia is the gross enrollment ratio (GER). Based on data from Statistics Indonesia, the GER at the senior high school level in Indonesia is still low compared to the GER at primary and junior high schools. Summarizing the findings of prior studies, the factors affecting GER include the number of schools, percentage of poor population, education budget, and student-teacher ratio. Therefore, this study aims to examine the variables that affect GER in Indonesian senior high schools. Since multicollinearity between the predictor variables was identified, ridge regression was employed. This study found that the number of senior high schools, the percentage of the poor population, and the education budget simultaneously had a significant effect and contributed 71.39% to the GER at the senior high school level in Indonesia. It is remarkable to observe that, partially, the number of senior high schools, the percentage of poor people, and the education budget had no direct effect on the GER. Additionally, there was a positive correlation between the variables and GER. The number of senior high schools and the education budget have a favorable impact. In contrast, the percentage of poor people has a negative effect on GER. Meanwhile, the student-teacher ratio does not have a linear relationship with the GER at the senior high school level in Indonesia.
Metode Response Based Unit Segmentation Partial Least Square pada Model Partial Least Square Path Modeling Utriweni Mukhaiyar; Karina Ayudhia Sasmito; Muh. Qodri Alfairus
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 11 Issue 1 June 2023
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/euler.v11i1.20105

Abstract

Education is an important factor that can affect the development of a country and is a basic human need. To ensure the continuous progress of education, it is necessary to pay attention to the results and achievements of education in Indonesia. In this research model, Partial Least Square Path Modeling (PLS PM) is used to explain the relationship between education outcomes and achievements and the quality dimensions of provincial education in Indonesia. However, because there is heterogeneity in the population unit, the Response Based Unit Segmentation Partial Least Square (REBUS PLS) algorithm is used to overcome the alleged heterogeneity. The results showed that there were 20 influential indicators in the structural model, with the influential paths being student activities to participation, educational facilities and infrastructure to educational outcomes and achievements, student activities to educational outcomes and achievements, and participation to educational outcomes and achievements. REBUS PLS successfully detects heterogeneity and produces two segments, with the value of R2 on the local model greater than the value of R2 on the global model and the GoF value in the GoF large category.
The Modified Double Sampling Coefficient of Variation Control Chart Fachrur Rozi; Udjianna Sekteria Pasaribu; Utriweni Mukhaiyar; Dradjad Irianto
Journal of Mathematical and Fundamental Sciences Vol. 55 No. 1 (2023)
Publisher : Directorate for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.math.fund.sci.2023.55.1.4

Abstract

The concept of monitoring the coefficient of variation has gained significant interest in quality control, particularly in situations where the mean and standard deviation of a process are not constant. This study modified the procedure of the previous double sampling chart for monitoring the coefficient of variation, developed by Ng et al. in 2018. Instead of using only information from the second sample, here, information from both samples is used. The probability properties of the out-of-control signal and run length of this chart are presented. To evaluate the chart’s performance, the optimal design and a comparison with the previous double sampling control chart using average run-length criteria are described. It was found that the modified double sampling chart has better performance and is more efficient compared to the previous chart, especially when the total sample size is smaller. As a study case, the application of this chart is illustrated using real data from a molding process. This confirmed that the modified double sampling chart improved performance in detecting out-of-control signals. Thus, the modified chart is recommended to be applied in industry.
Analisis Sistem Antrian pada Pelayanan Help Desk UPT TIK Institut Teknologi Sumatera Menggunakan Teori Antrian Dwi Rianti; Utriweni Mukhaiyar; Lutfi Mardianto
Indonesian Journal of Applied Mathematics Vol 2 No 1 (2022): Indonesian Journal of Applied Mathematics Vol. 2 No. 1 April Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/indojam.v2i1.534

Abstract

The analysis of the queuing system at the Help Desk service of the UPT TIK Institut Teknologi Sumatera includes the number of ticket arrivals, the average length of service time, and the number of service facilities (admin). The data for the number of Help Desk tickets are Poisson distributed and the service time is the Exponential distribution. The size of the steady-state in the service has a value of so that an analysis of the performance size of the queue system can be carried out. The data used in the study are Help Desk ticket data for the period November 2020-February 2021. The results obtained indicate that the queue model for the Help Desk service can be added to the server (admin). The addition of a server in the service can reduce the workload significantly. The queue model that can be applied is M/M/3:FCFS/∞/∞ by adding one server (admin), from the previous model, namely M/M/2:FCFS/∞/∞.
Co-Authors Alfairus, Muh. Qodri Dradjad Irianto Dwi Rianti Erni Widyawati Fachrur Rozi Ferdy Rontos Karina Ayudhia Sasmito Kurnia Handoko Mardianto, Lutfi Muh. Qodri Nabila Mardiyah Riani Utami Salim Salim Salma Kardiyanti Siti Maisaroh Sonhaji, Abdulah Sunyanti Sunyanti Syahri Ramadhani Trimono, Trimono Udjianna S. Pasaribu Udjianna Sekteria Pasaribu Vira Ananda Yalela Sa’adah Yundari, Yundari