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APPLICATION OF BACKPROPAGATION FOR FORECASTING OPEN UNEMPLOYMENT IN MAKASSAR CITY Syam, Rahmat; Sidjara, Sahlan; Abdullah, Adib Roisilmi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2359-2376

Abstract

Based on data from the Statistics Bureau of South Sulawesi Province, the open unemployment rate in Makassar City has remained consistently high over the past ten years, averaging 11.41%. This highlights a persistent labor market issue and positions Makassar as the leading contributor to the open unemployment rate in the province. To support effective policymaking and early intervention strategies, it is essential to forecast future unemployment trends based on historical data. Therefore, this study aims to forecast the open unemployment rate in Makassar City over the next five years using a machine learning approach. Among the available forecasting methods, the Backpropagation Artificial Neural Network (ANN) was selected due to its proven ability to model complex, non-linear relationships often found in socio-economic data. ANN is particularly effective in handling temporal dynamics without assuming linearity or stationarity, unlike traditional statistical models. In this study, the forecasting process involved data normalization, scenario-based data partitioning, ANN architecture design, and model training and testing. The model with the best performance consisted of 11 neurons in the input layer, 55 neurons in the hidden layer, and 1 neuron in the output layer, using 80% of the data for training and 20% for testing. This configuration yielded a forecasting accuracy of 91.896%, with a MAPE of 8.131% and an MSE of 0.003. The denormalized results forecast a steady decline in the open unemployment rate from 9.078% in 2023 to 7.248% in 2027, indicating a positive trend in employment. Nevertheless, it is important to acknowledge the limitations of forecasting models and the potential influence of external factors that may affect actual outcomes.
Analysis and Simulation of SELR Model in Exploring and Predicting the Dynamics of Independent Curriculum in Addressing the Gap in Student Achievement in City Centers and Remote Areas in South Sulawesi Muktamar, Muhammad Ilham; Syam, Rahmat; Side, Syafruddin; Sainon Andi Pandjajangi, Andi Muhammad Ridho Yusuf
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 13, No 2 (2024): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat132660242024

Abstract

This study aims to build and analyze the SELR mathematical model in the context of the Independent Curriculum, in order to explore and predict the gap in student achievement between urban and remote areas in South Sulawesi. This study combines theoretical studies and applications by conducting simulations using Maple software. The study population involved 400 students from urban areas and 400 students from remote areas where simulation data was used to predict the dynamics of adaptation to the Independent Curriculum. The results showed that the Independent Curriculum was not fully effective in addressing the achievement gap, with a low basic reproduction number (R₀), both in urban and remote areas. The R₀ value of 0.204 in urban areas and 0.614 in remote areas indicates that the spread of curriculum adaptation is still limited and cannot create a significant impact on improving student achievement. This study indicates the need for additional adjustments and interventions in the implementation of the Independent Curriculum to achieve more equitable and inclusive results in various regions .
Numerical Solution of Drug Addiction Mathematical Model Using Adams Moulton Method Maulida, Nurul Ismi; Side, Syafruddin; Syam, Rahmat
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i3pp521-536

Abstract

Rug abuse is one of the major social issues in Indonesia, particularly in South Sulawesi. This study aims to develop a mathematical model that represents the dynamics of drug addiction in the population and to solve the model numerically using the Adams-Moulton method. The model applied is theSIIHRcompartment model, which segments the population into five groups: susceptible (S), light addict (IR), heavy addict (IB), in rehabilitation (H), and recovered (R). The analysis results indicate that the basic reproduction number푅₀is less than 1, suggesting that drug addiction in the population can be managed. Numerical simulations are conducted using the fifth-orderRunge-Kuttamethod for initial values, followed by theAdams-Bashforth-Moultonmethod as the numerical solution technique. The model demonstrates stability at the drug-free equilibrium point and consistency between the outcomes of mathematical and numerical analysis.