Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan EIGEN MATHEMATICS JOURNAL
Luthfiyah, Fadillah
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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

Found 2 Documents
Search

 1 
PREDICTION OF TIN EXPORTS, POPULATION, POVERTY, AND LABOR FORCE IN THE PROVINCE OF BANGKA BELITUNG ISLANDS Kustiawan, Elyas; Dalimunthe, Desy Yuliana; Vebtasvili, Vebtasvili; Oktarianty, Haslen; Silaban, Yabes Sentosa; Luthfiyah, Fadillah; Rahmania, Dita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2589-2596

Abstract

The COVID-19 virus has also caused shocks to the Bangka Belitung Islands Province in various sectors, especially the economy. To overcome this problem, of course the government has prepared responsive policies, both fiscal and monetary policies to prevent post-COVID-19 risks, especially in the economic recession. To prevent a post-COVID-19 economic recession, a prediction or time series forecast is needed on four variables that influence the economic recession, namely the number of tin exports, population, poverty and labor force in the Bangka Belitung Islands Province so that economic growth is maintained. This research aims to predict the four research variables by comparing the Moving Average and Exponential Smoothing methods. This research also uses Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) as indicators of model accuracy. Based on the results of the accuracy indicators of this model, it was found that the Exponential Smoothing method was better than the Moving Average method. The predicted results for the value of tin exports in 2024 are -3.3645811 with The RMSE value is 42293770, MAE is 29558091, and MAPE is 84.46131. The negative value in the tin export prediction means that the decline in the value of tin exports in 2024 will not have a significant effect because it is still within a reasonable figure. The total labor force in 2024 will be 11057.23 with RMSE value is 16536.48, MAE value is 14194.02, and MAPE is 112.8078. Then for population the predicted result is 21241.92 with RMSE is 19537.82, MAE is 11548.41, and MAPE is 37.51894. Then for the predicted results the number of poverty is 70.22749 with RMSE, MAE, and MAPE respectively of 3992.146, 3205.528, and 139.1129. The alpha value used is 0.0183.
Modeling of the Spread of Malaria in the Bangka Belitung Islands Province Using the SEIR Method Halim, Nikken; Putri, Marwah Hotimah Nada; Alviari, Irfaliani; Luthfiyah, Fadillah; Septiani, Hera; Prayanti, Baiq Desy Aniska
Eigen Mathematics Journal Vol 7 No 1 (2024): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i1.189

Abstract

Malaria is an infectious disease caused by plasmodium through the bite of the Anopheles sp. female mosquito. (Roach, 2012). Malaria disease which hit the Bangka Belitung Islands Province in 2005 experienced a spike, reaching 36,901 people out of 981,573 residents and claimed the lives of 12 local residents. In 2011, the Bangka Belitung Islands Province was declared an endemic area for malaria. This research aims to model and interpret the spread of malaria using the SEIR model and predict the spread of malaria using parameter estimates. The steps in analyzing the SEIR model on the spread of malaria are making assumptions, forming a SEIR model, determining the equilibrium point and analyzing the stability of the equilibrium point, determining the basic reproduction number, and carrying out a simulation of the SEIR model that has been obtained. The SEIR model is classified into 4 classes, namely Susceptible (susceptible individuals), Exposed (individuals who have symptoms), Infected (infected individuals), and Recovered (recovered individuals). The data used in this research is data on the number of Susceptible, Exposed, Infected, and Recovered malaria cases in 2022 obtained from the Bangka Belitung Islands Provincial Health Service. The SEIR mathematical model is used to calculate the equilibrium point and basic reproduction number. Based on the SEIR model simulation results, it was found that the susceptible population decreased from the 0th month to the 48th month. As for the exposed population, there were 9,623 people in month 0, but in this condition the population decreased drastically per month. Furthermore, for the infected population there were 129 people in month 0, but in this condition the number of infected decreased drastically per month along with the decrease in the exposed population. For individuals who recovered, there was a increase from the 0th month to the 48th month.
Co-Authors Alviari, Irfaliani Baiq Desy Aniska Prayanti Desy Yuliana Dalimunthe, Desy Yuliana Halim, Nikken Kustiawan, Elyas Oktarianty, Haslen Putri, Marwah Hotimah Nada Rahmania, Dita Septiani, Hera Silaban, Yabes Sentosa Vebtasvili Vebtasvili