Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal technoscientia JURNAL TEKNOLOGI TECHNOSCIENTIA Journal of Fundamental Mathematics and Applications (JFMA)
Noviana Pratiwi
Jurusan Statistika, IST AKPRIND Yogyakarta
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
METODE GENERALIZED SPACE-TIME AUTOREGRESSIVE UNTUK PERAMALAN PERTUMBUHAN EKONOMI DI KAWASAN TIMUR INDONESIA Rokhana Dwi Bekti; Noviana Pratiwi; Petronella Mira Melati
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 11 No 1 Agustus 2018
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1620.59 KB) | DOI: 10.34151/technoscientia.v11i1.117

Abstract

Generalized Method of Space Time Autoregressive (GSTAR) is one of spatio temporal method. This method modifies the spatial dependencies among location by using the time series data or time lags. This research applies the GSTAR for forecasting economic growth in Eastern Indonesia. The economic development of some provinces in the region, which is far from state of capital, is highly dependent on access to the facility centers of economic activity, access to education, access to health facility, and others. Thus forecasting information by taking into account the spatial aspect (the relationship between the provinces) and time is needed to assess the economic development of several periods ahead. GSTAR (1;1) was selected for the forecasting. Parameter estimation using least squares build the different parameter in each province. Based on comparisons with ARIMA method, GSTAR provide better forecasting results.
METODE GENERALIZED SPACE-TIME AUTOREGRESSIVE UNTUK PERAMALAN PERTUMBUHAN EKONOMI DI KAWASAN TIMUR INDONESIA Rokhana Dwi Bekti; Noviana Pratiwi; Petronella Mira Melati
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 11 No 1 Agustus 2018
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/technoscientia.v11i1.117

Abstract

Generalized Method of Space Time Autoregressive (GSTAR) is one of spatio temporal method. This method modifies the spatial dependencies among location by using the time series data or time lags. This research applies the GSTAR for forecasting economic growth in Eastern Indonesia. The economic development of some provinces in the region, which is far from state of capital, is highly dependent on access to the facility centers of economic activity, access to education, access to health facility, and others. Thus forecasting information by taking into account the spatial aspect (the relationship between the provinces) and time is needed to assess the economic development of several periods ahead. GSTAR (1;1) was selected for the forecasting. Parameter estimation using least squares build the different parameter in each province. Based on comparisons with ARIMA method, GSTAR provide better forecasting results.
ESTIMASI TINGKAT RISIKO INVESTASI EMAS MENGGUNAKAN PENDEKATAN GENERALIZED EXTREME VALUE DAN GENERALIZED PARETO DISTRIBUTION Noviana Pratiwi; Catur Iswahyudi
Journal of Fundamental Mathematics and Applications (JFMA) Vol 2, No 1 (2019)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.692 KB) | DOI: 10.14710/jfma.v2i1.22

Abstract

This study estimates the level of risk in investing in gold. Value at Risk (VaR) is a method which can be used for calculating the level of risk. There are two distribution approaches used, namely Generalized Extreme Value Distribution (GEV) and Generalized Distribution Pareto (GDP). These two distributions are used because gold data is alleged to have a heavy tail distribution. The study uses secondary data on gold prices with January 2015 to December 2017 period with a total of 876 data. The results obtained indicate that the data return for the gold price has a heavy tail. Estimation results obtained indicate that the VaR value at the 95% confidence level is less than VaR with a 99% confidence level so it can be concluded that the higher the level of risk to be taken, the greater the level of confidence and capital allocation to cover losses taken by investors. The GDP Estimation value gives a greater value than GEV. and the largest VaR value is shown at 4.049%, which means that the maximum loss that may occur in one period ahead is 4.049%.
Co-Authors Catur Iswahyudi Petronella Mira Melati Rokhana Dwi Bekti