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All Journal SAINSMAT Journal of ICT Research and Applications Jurnal Daya Matematis BAREKENG: Jurnal Ilmu Matematika dan Terapan LOSARI: Jurnal Pengabdian Kepada Masyarakat Issues in Mathematics Education (IMED) Journal of Mathematics: Theory and Applications Seminar Nasional Pengabdian Kepada Masyarakat Makara Journal of Technology Indonesian Journal of Fundamental Sciences Seminar Nasional Hasil Penelitian LP2M UNM Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) Journal of Mathematics, Computation and Statistics (JMATHCOS) Issues in Mathematics Educations (IMED)
Rahmat Syam
Jurusan Matematika Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Negeri Makassar
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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 .
Co-Authors A. Asman Abdullah, Adib Roisilmi Agnes Monica Putri Agusalim Juhari Ahmad Firjatullah Hakim Ahmad Firjatullah Hakim AHMAD ZAKI Ahmad Zaki Ahmad Zaki Asep Ardat Asep Ardat Asman Awi Dassa Awi Dassa Basri, Muhammad Yusran Elfira Haryanensi Elfira Haryanensi A Fahrul Ahmad Fahrul Ahmad Hamzah Upu Hisyam Ihsan Jusman Jusman Lubis, Kristina Marwan Marwan Mauridhi Herry Purnomo Mauridhi Hery Purnomo Mauridhi Purnomo Mauridhi Purnomo, Mauridhi Meisy Tri Elsa Meisy Tri Elsa Mochamad Hariadi Mochamad Hariadi Muh Nahdi Alim Asyhari Muh Nahdi Alim Asyhari Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Farhan Muhammad Hasriyadi Basri Muhammad Hasriyadi Basri Muhammad Irham Muktamar Muhammad Yusran Basri Muktamar, Muhammad Ilham Muktamar, Muhammad Irham N. Nurmah Nurdin Arsyad Nurdin Arsyad Nurhiqmah Takbir Nurmah, Nurmah Rabiatul Adawiyah Rabiatul Adawiyah Sainon Andi Pandjajangi, Andi Muhammad Ridho Yusuf Sari, Yulfiana Sidjara, Sahlan Siti Khodidah Siti Khodidah Sukarna Sukarna Sukarna Sukarna Sukarna Sulaiman Sulaiman Sulaiman Sulaiman Syafruddin Side SYahnur, Andi Aulia Syamsuddin Mas'ud T. Tina Tina, Tina Usman Mulbar Wahidah Sanusi Wahyuni, Maya Sari Yusuf SAP, Andi Muh. Ridho