Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Economics and Finance in Indonesia
Neli Agustina
Politeknik Statistika STIS
Economics, Econometrics & Finance Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
The Impact of Human Capital on Shadow Economy in Indonesia Saraswati Saraswati; Neli Agustina
Economics and Finance in Indonesia Volume 66, Number 1, June 2020
Publisher : Institute for Economic and Social Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (203.308 KB) | DOI: 10.47291/efi.v66i1.629

Abstract

Shadow economy is a market for legal and illegal goods and services that escape recording and estimation of GDP. It can cause inaccurate estimation of GDP, declining tax revenue, and less precise economic policies. Improving the quality of human capital, both in education and health dimensions, can reduce shadow economy. The research aims to estimate shadow economy and analyze the influence of the quality of human capital on shadow economy in Indonesia. Applying time series multiple linear regression analysis, the findings show that the average shadow economy in Indonesia is 28.97 percent, changes in life expectancy negatively affect changes in shadow economy, while changes in the gross participation rate of tertiary education have a positive effect.
Comparison of Forecasting Model Using Chen and Lee High Order Fuzzy Time Series (Farmer’s Terms of Trade of Crops Subsector in Nusa Tenggara Timur Province Case) Fais Muzaki; Neli Agustina
Jurnal Matematika, Statistika dan Komputasi Vol. 21 No. 2 (2025): JANUARY 2025
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v21i2.42000

Abstract

The farmer’s terms of trade of food crops subsector (NTPP) in Nusa Tenggara Timur Province has always been below 100 in 2019-2023. Food crops are a substantial agricultural subsector in which its contribution to the PDRB is significant and concerns the food adequacy of the region. NTPP is a proxy indicator to see farmers’ welfare and its value is expected to grow periodically. Therefore, predictive modeling is required to know future NTPP values and to know the purchasing power of food crop farmers. The aim of this research is to compare the accuracy of Chen and Lee model with the high order fuzzy time series for NTPP forecasting in Nusa Tenggara Timur Province. This research uses monthly data from NTPP Nusa Tenggara Timur from January 2016 to October 2024. The research results show that additions up to the 3rd order increase forecast accuracy and the Lee model is more accurate than the Chen model seen from the smaller RMSE and MAPE values. The MAPE values ​​of the 3rd order fuzzy time series Chen and Lee model are 0.5453% and 0.5088% respectively. Based on the MAPE value, the 3rd order Lee model is the most accurate in forecasting NTPP in Nusa Tenggara Timur Province.    
Co-Authors Fais Muzaki Saraswati Saraswati