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All Journal Jurnal Sains Matematika dan Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan
Koesnadi, Grace Lucyana
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Analisis Keputusan Hedging pada Bank Non-Syariah di Indonesia Menggunakan Model Regresi Logit Biner Data Panel dengan Efek Acak Koesnadi, Grace Lucyana; Suliyanto, Suliyanto; Mardianto, M. Fariz Fadillah; Sediono, Sediono
Jurnal Sains Matematika dan Statistika Vol 11, No 1 (2025): JSMS Januari 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v11i1.33886

Abstract

Volatilitas pasar global yang semakin tinggi telah menjadi tantangan besar bagi sektor perbankan di Indonesia, khususnya dalam menghadapi fluktuasi nilai tukar rupiah. Dalam mengatasi risiko ini, strategi hedging menjadi langkah penting untuk menjaga stabilitas keuangan. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi keputusan hedging pada bank non-syariah di Indonesia, seperti leverage, likuiditas, profitabilitas, ukuran perusahaan, dan peluang pertumbuhan. Dengan menggunakan regresi logit biner pada data panel dengan efek acak, penelitian ini memanfaatkan data sekunder dari laporan keuangan tahunan bank non-syariah yang terdaftar di Bursa Efek Indonesia (BEI) untuk periode 2020-2022. Hasil analisis menunjukkan bahwa leverage dan ukuran perusahaan memiliki pengaruh signifikan terhadap keputusan hedging, sedangkan likuiditas dan peluang pertumbuhan menunjukkan pengaruh yang bervariasi. Penelitian ini memberikan wawasan penting terkait pengelolaan risiko nilai tukar yang strategis untuk memperkuat stabilitas keuangan sektor perbankan non-syariah di Indonesia, serta mendukung pengambilan keputusan yang lebih akurat dalam mitigasi risiko keuangan.
PREDICTION OF UNIT VALUE INDEX OF EXPORTS OF SITC 897 JEWELRY AND PRECIOUS GOODS GROUP IN INDONESIA Koesnadi, Grace Lucyana; Pratama, Bagas Shata; Ain, Dzuria Hilma Qurotu; Pusporani, Elly; Mardianto, M. Fariz Fadillah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2247-2262

Abstract

Export is an international trade activity that plays an important role in the economic progress in Indonesia. One of Indonesia's leading commodities that dominate the export market is jewelry. In export activities, the export unit value index is an important component that serves to describe the development of export commodity prices. This unit value index always changes every time and fluctuates. This research conducts a comparative analysis of the performance of parametric method, non-parametric method, and machine learning, specifically, ARIMA, Fourier series estimator, and Support Vector Regression (SVR). This study aims to evaluate the effectiveness of various methods in improving prediction accuracy for the unit value index of the SITC code 897 in Indonesia. The research data used is secondary data including monthly export unit value index data with SITC code 897 in Indonesia obtained from the Central Bureau of Statistics. The data divided into 90% training data and 10% testing data. The methods used in this analysis are ARIMA, Fourier series estimator, and SVR. The best model obtained from each method is ARIMA (1,1,1) with MAPE of 10.92%, Fourier series estimator with MAPE of 8.47%, and an SVR RBF kernel function with MAPE of 3.73%. The results of this study obtained the best method for predicting the unit value index of SITC code 897 is SVR with an RMSE value of 8.288 and very good prediction accuracy.
Co-Authors Ain, Dzuria Hilma Qurotu Elly Pusporani M. Fariz Fadillah Mardianto Pratama, Bagas Shata Sediono, Sediono Suliyanto Suliyanto