Reski Wahyu Yanti
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Edugame Interaktif untuk Pembelajaran Literasi Data dan Keuangan Syariah di Sekolah Dasar Islam Terpadu andi seppewali; Reski Wahyu Yanti; Supardi Muh Said; Ahmad Adivar; Rosmila; Bintang Guntur
Symmetry: Pasundan Journal of Research in Mathematics Learning and Education Vol. 9 No. 2 (2024): Symmetry: Pasundan Journal of Research in Mathematics Learning and Education
Publisher : Mathematics Education Study Program, FKIP, Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/symmetry.v9i2.20520

Abstract

With the increasing complexity of information and the growing importance of understanding data and sharia financial literacy in society, developing effective and engaging learning methods has become crucial, especially at the elementary school level. The objective of this study is to develop and implement an interactive edugame based on the Guided Discovery approach as a learning tool to enhance students' data and sharia financial literacy. The research method employed is the R&D approach, following the 4D stages: define, design, develop, and disseminate. A comprehensive literature review was conducted to design an interactive edugame that aligns with learning needs and principles. The edugame development process includes graphic design, software coding using HTML5 and Android Studio, as well as iterative testing and revisions. The edugame implementation was carried out at an Integrated Islamic Elementary School, involving training for teachers and students, along with mentoring during the learning process. Furthermore, this study is expected to contribute to the development of innovative learning approaches, particularly in the context of data and sharia financial literacy at the Integrated Islamic Elementary School level.
Implementation of Random Forest Algorithm for Shallot Price Forecasting in Makassar City Hardianti Hafid; Arwini Arisandi; Reski Wahyu Yanti
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9477

Abstract

This study aims to implement the Random Forest algorithm for forecasting shallot prices in Makassar City using monthly historical data from January 2018 to December 2024, obtained from the Statistics Indonesia (Badan Pusat Statistik) of South Sulawesi Province. The analysis begins with identifying significant lags through the Partial Autocorrelation Function (PACF) plot, resulting in seven input variable schemes. Each scheme was tested using training and testing datasets. Model performance was evaluated using the Mean Absolute Percentage Error (MAPE). The results show that Scheme 1 (Lag 1) achieved the best performance with a MAPE value of 13.08%, which falls into the “good” category. Price forecasts for January–December 2025 using the best scheme indicate a price range of IDR 23,200 – 24,300 per kilogram, with peak prices in March, July, and November, and the lowest prices in April, August, and December. Although the model successfully captures historical price patterns, real-world fluctuations driven by seasonal factors, supply disruptions, and distribution costs may cause prediction deviations. This study recommends integrating exogenous variables and real-time data to improve forecasting accuracy and support local food price stabilization policies.