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All Journal Al-Khidmah: Jurnal Pengabdian Kepada Masyarakat Jurnal Ekonomi Syariah dan Hukum Islam
Bandawa Winata, Ega
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Peran Mathematics Anxiety (Kecemasan Matematika) Guru dalam Mempengaruhi Growth Mindset Siswa Bandawa Winata, Ega
Al-Khidmah: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025): September
Publisher : LP2M Institut Agama Islam Nazhatut Thullab Sampang, Indonesia

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Abstract

penelitian ini bertujuan untuk menguji hubungan timbal balik antara tingkat kecemasan matematika (Mathematics Anxxety) yang dialami oleh guru dan dampaknya terhadap pola pikir berkembang (Growth Mindset) serta keyakinan Diri (Self-Efficaty) siswa dalam menghadapi kesulitan matematika. Desain korelasional digunakan untuk mengukur variabel pada 20 guru matematika (tingkat SMP dan SMA) dan 150 siswa mereka. hasil stimulasi menunjukkan korelasi negatif yang signifikan antara Kecemasan Matematika Guru dan Growth Mindset Siswa Guru dengan kecemasan tinggi cenderung menciptakan lingkungan kelas yang kurang mendukung pengambilan risiko dan kesalahan, yang secara tidak langsung menghambat adopsi pola pikir bahwa kemampuan dapat dikembangkan. Implikasi penelitian ini menekankan perlunya intervensi untuk mengurangi Kecemasan Matematika pada guru guna meningkatkan iklim belajar yang lebih positif bagi siswa.
Pemodelan dan Peramalan Inflasi Indonesia Menggunakan Pendekatan Regresi Nonlinear: Studi pada Model Logistic Smooth Transition Autoregressive (LSTAR) Bandawa Winata, Ega
IQTISODINA Vol. 8 No. 1 (2025): Juni
Publisher : LPPM IAI Nazhatut Thullab

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This study aims to model and forecast inflation in Indonesia using a nonlinear regression approach, specifically the Logistic Smooth Transition Autoregressive (LSTAR) model. Inflation often exhibits nonlinear behavior due to different economic regimes, such as stable and crisis periods, which linear models fail to capture. Using monthly year-on-year inflation data from January 2009 to December 2022, this research begins with stationarity testing, nonlinearity identification using the Terasvirta test, LSTAR model parameter estimation, and diagnostic evaluation. The results confirm significant nonlinearity in Indonesian inflation. The best model is LSTAR(2) with the transition variable at a two-month lag (INF_{t-2}). This model effectively captures a smooth transition between two regimes: a low-inflation regime and a high-inflation regime, with an estimated threshold of 4.85%. In the low-inflation regime, inflation shows high persistence. In contrast, the high-inflation regime exhibits a mean-reverting characteristic, indicating a self-correcting mechanism or a policy response. Based on the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) criteria, the LSTAR model demonstrates superior forecasting accuracy compared to the conventional linear ARIMA model. This study concludes that the LSTAR model is an effective and robust tool for modeling and forecasting inflation in Indonesia. The findings imply that Bank Indonesia should be more vigilant when inflation approaches the 4.85% threshold, as the economic dynamics may shift, requiring a different monetary policy response.
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