Malik Ibrahim
@unu-ntb.ac.id
Education Faculty
Universitas Nahdlatul Ulama Nusa Tenggara Barat
EDUCATION
Mathematic Education
RESEARCH, TEACHING, or OTHER INTERESTS
Education, Mathematics, General Mathematics
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Syaharuddin, D R Muharani, M Ibrahim, and V Mandailina
IOP Publishing
Abstract This study aims to analyze the neural network backpropagation (ANN-BP) algorithm in seeing the development and comparison of wind speed. We estimated the wind speed of coastal areas with a case study of five countries in Southeast Asia. We used data for the last 10 years in the form of monthly data. The ANN-BP architecture uses input layers, three hidden layers, and one output layer with 12-25-10-1 architecture. From the simulation results in the training stage, we obtained information that the data model that is closest or follows the wind speed pattern with the smallest MSE value is the coastal area in Thailand with an MSE value of 0.00012 in the training stage and 0.00011 in the testing stage. Then, we also obtained that the average prediction of wind speed on the coast of Brunei Darusslam obtained the smallest value compared to other countries.
Syaharuddin, Yuli Yasmin, and Malik Ibrahim
IOP Publishing
Abstract Global warming is an event in which the average temperature of the atmosphere, ocean and land rises. Changes in atmospheric temperature cause changes in the physical conditions of the atmosphere to become unstable, causing anomalies in weather parameters that cause climate change. In the last decade there have been temperature changes in the North Pole (Greenland) and the South Pole (Antarctica). The impacts caused by temperature changes are melting ice sheets, rising sea levels, extinction of species in large numbers, people living on the coast are threatened by tidal floods, while small islands can sink. To anticipate temperature changes, a model is needed that can forecast air or temperature conditions using Artificial Neural Network with Backpropagation method using Matlab software media. Data obtained from Data Access Viewer of NASA. After training and testing the data, the average value of the prediction results for the south polar region (Antarctica) is -47.910C with a Mean Square Error (MSE) value of 0.0015. Meanwhile, for the North Pole region (Greenland), the average value of the prediction results is -22.410C with an MSE value of 0.0069. By looking at the average value of the prediction results, it can be concluded that the temperature change for the South Pole region (Antarctica) is higher than the temperature change for the North Pole region (Greenland).
Malik Ibrahim, Anisah, Wita Ratna Puspita, Rody Satriawan, Lalu Jaswandi, Aminullah, Johri Sabaryati, and Syaharuddin
AIP Publishing
The COVID-19 pandemic data in Indonesia have been simulated from March 2, 2020, until August 31, 2020. In each case, the ARIMA method applied the mathematical model to determine the data of confirmed, recovered, and dead Covid-19 patients. Each data creates four mathematical models based on the accuracy parameters used, namely MAD, MSE, and MAPE, with the 4th mathematical model used to forecast the growth of data trends. The peak point of the number of patients being treated or in isolation occurred in December 2020 with as many as 1,150,629 positive patients, 995,922 recovered, and 29,741 deaths. It also obtained information that the increase in the number of confirmed, recovered, and dead patients were 1.56%, 1.71%, and 1.14%. © 2022 Author(s).
Syaharuddin, Habib Ratu Perwira Negara, Malik Ibrahim, Ahmad, Muhammad Zulfikri, Gilang Primajati, Via Yustitia, Suvriadi Panggabean, Rina Rohayu, and Nurjannah Septyanun
AIP Publishing
Forecasting is a process or method used to predict future uncertainty as an effort to make better decisions. The purpose of this research is to compare the proximity level of the quantitative measurement to the actual value (accuracy) between the Exponential Moving Average (EMA) method and the Brown method by modifying the alpha value between 0 and 1. The data used is the daily data dissemination of COVID-19 in NTB Province, which starts from 11 March-14 July 2020. Based on data simulation results with alpha value modification obtained information that the Brown method is more accurate than the EMA method. The alpha value with the least error in the Brown method amounted to 0.7 with the MAPE of 4.34%. Therefore, doing forecasting by using Brown should take the results of the smallest simulation value of the value of MAD, MAPE, or MSE because the smaller the value will be the better quality of objects.
H R P Negara, Syaharuddin, M Ibrahim, K R A Kurniawati, V Mandailina, D Pramita, Abdillah, Mahsup, Ahmad, and Saddam
IOP Publishing
Abstract The research aims to analyze the acceleration of the population growth in Lombok which consists of 5 districts/cities using forecasting system by constructing the winter’s method in the form of a GUI Multiple Forecasting System (G-MFS) based on Matlab by calculating the indicator level of accuracy to find predictive data for the next 10 years. At the data simulation stage, researchers used population data over the last 11 years. The evaluation of forecasting results is calculated by calculating the value of Mean Absolute Percentage Error (MAPE) with 27 attempts through modified Winter parameter values. From the simulation data obtained the most optimal parameter value is α, β, and γ sequential values of 0.9, 0.5, and 0.9. Then with the value of the parameter obtained MAPE value of 1.25%. Furthermore, it can be noted that for the next 10 years the increase in the population of Lombok Island on average of 1.49%, with the average East Lombok district details of 1.15%, the average West Lombok district by 1.17%, the average central Lombok district of 0.98%, the North Lombok district averaged 0.98%, and the average Mataram city of 3.05%. These results suggest that the simulated and numeric techniques using the GUI of MATLAB provide quite accurate results. In subsequent research, it is necessary to do predictions based on the number of births, the number of deaths, the number of transmigration, the amount of productive and non-productive, and other data series that is more complex so that it will be seen how the development of the population productivity on the island of Lombok.