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INDONESIA
Journal of Oikonomia
Published by EDU PARTNER INDONESIA
ISSN : 29863899     EISSN : 29862752     DOI : -
Core Subject : Economy,
Economics, Econometrics & Finance
Journal of Oikonomia is published twiced times a year (March and September) by Edu Partner Indonesia. Journal of Oikonomia (E-ISSN: 2986-2752 | P-ISSN: 2986-3899) is intended to be the journal for publishing articles reporting the results of economic research. Invites manuscripts on various topics to include, including but not limited to functional areas of Accounting, Entrepreneurship, Strategic Alliances, Microeconomics, Behavioral and Health Economics, Government Regulation, Taxation, Macroeconomics, Financial Markets, Investment, Banking, International Economics, Foreign Direct Investment, Economic Development, Environmental Studies, Urban Issues, Emerging Markets, Empirical Studies, Quantitative and Experimental Methods.
Arjuna Subject : Ilmu Ekonomi, Ekonometrika dan Keuangan (semua kategori) - Ilmu Ekonomi, Ekonometrika dan Keuangan (Lain-Lain)
Articles 2 Documents
 1 
Search results for , issue "Vol 4 No 1 (2026): March" : 2 Documents clear
Determinan Pengungkapan Kesehatan dan Keselamatan Kerja pada Industri Berisiko Tinggi di Indonesia Meilina; Aminah
Oikonomia Vol 4 No 1 (2026): March
Publisher : Edu Partner Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69747/oikonomia.v4i1.263

Abstract

Pengungkapan kesehatan dan keselamatan kerja (K3) merupakan bagian penting dari tanggung jawab perusahaan, khususnya pada industri berisiko tinggi. Penelitian ini bertujuan menganalisis pengaruh profitabilitas, ukuran perusahaan, dan umur perusahaan terhadap pengungkapan K3 dengan leverage dan kepemilikan institusional sebagai variabel kontrol. Penelitian menggunakan data sekunder berupa laporan tahunan dan laporan keberlanjutan perusahaan sektor konstruksi dan pertambangan yang terdaftar di Bursa Efek Indonesia periode 2022–2024. Tingkat pengungkapan K3 diukur menggunakan indeks 30 indikator berdasarkan GRI 403:2018 dan regulasi K3 di Indonesia. Data dianalisis menggunakan regresi data panel dengan Random Effects Model sebagai metode estimasi terbaik. Hasil penelitian menunjukkan bahwa profitabilitas dan ukuran perusahaan berpengaruh positif signifikan terhadap pengungkapan K3, sedangkan umur perusahaan, leverage, dan kepemilikan institusional tidak berpengaruh signifikan. Temuan ini menunjukkan bahwa perusahaan dengan kinerja keuangan dan skala yang lebih besar cenderung mengungkapkan informasi K3 lebih luas. Penelitian ini memberikan bukti empiris mengenai pengungkapan K3 pada sektor konstruksi dan pertambangan sebagai industri berisiko tinggi di Indonesia. Occupational health and safety (OHS) disclosure is an important aspect of corporate responsibility, particularly in high-risk industries. This study examines the effect of profitability, firm size, and firm age on OHS disclosure, with leverage and institutional ownership as control variables. The study uses secondary data from annual and sustainability reports of construction and mining companies listed on the Indonesia Stock Exchange during 2022–2024. OHS disclosure was measured using a 30-indicator index based on GRI 403:2018 and Indonesian OHS regulations. Data were analyzed using panel data regression with the Random Effects Model as the best estimation method. The results show that profitability and firm size have a positive and significant effect on OHS disclosure, while firm age, leverage, and institutional ownership have no significant effect. These findings indicate that companies with stronger financial performance and larger scale tend to disclose OHS information more extensively. This study provides empirical evidence on OHS disclosure practices in the construction and mining sectors as high-risk industries in Indonesia.
Analisis Volatilitas nilai Tukar USD/IDR dan Impikasinya terhadap Stabilitas Ekonomi Indonesia:Pendekatan GARCH dan Hybrid ARIMA-ANN Miftahul Irfan; Nora Madonna; Erica Grace Simanjuntak
Oikonomia Vol 4 No 1 (2026): March
Publisher : Edu Partner Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk menganalisis volatilitas serta mengevaluasi kinerja peramalan return nilai tukar USD/IDR menggunakan model GARCH dan pendekatan hybrid ARIMA-ANN. Data yang digunakan adalah data harian periode 2010–2025 yang diperoleh dari Yahoo Finance. Metode analisis meliputi transformasi log return, uji stasioneritas menggunakan Augmented Dickey-Fuller (ADF), uji ARCH untuk mendeteksi heteroskedastisitas, serta estimasi model GARCH(1,1) untuk memodelkan volatilitas. Selanjutnya, model ARIMA digunakan untuk menangkap pola linear, sementara residualnya dimodelkan menggunakan Artificial Neural Network (ANN) untuk membentuk model hybrid. Hasil penelitian menunjukkan bahwa data return bersifat stasioner dan mengandung efek ARCH yang signifikan. Estimasi GARCH menunjukkan bahwa volatilitas bersifat sangat persisten dengan nilai α₁ + β₁ mendekati satu. Perbandingan kinerja model menunjukkan bahwa hybrid ARIMA-ANN menghasilkan nilai RMSE yang lebih rendah dibandingkan ARIMA, yang mengindikasikan peningkatan akurasi peramalan. Temuan ini menunjukkan bahwa dinamika nilai tukar tidak hanya dipengaruhi oleh pola linear, tetapi juga oleh hubungan nonlinear yang kompleks, sehingga pendekatan hybrid lebih efektif dalam meningkatkan akurasi prediksi. This study aims to analyze volatility and evaluate the forecasting performance of the USD/IDR return using the GARCH model and a hybrid ARIMA-ANN approach. The data used are daily exchange rate data from 2010 to 2025 obtained from Yahoo Finance. The analysis includes log return transformation, stationarity testing using the Augmented Dickey-Fuller (ADF) test, and ARCH testing to detect heteroskedasticity. The GARCH(1,1) model is employed to capture volatility dynamics. Furthermore, the ARIMA model is used to capture linear patterns, while its residuals are modeled using Artificial Neural Networks (ANN) to form a hybrid model. The results indicate that the return data are stationary and exhibit significant ARCH effects. The GARCH estimation shows that volatility is highly persistent, with α₁ + β₁ approaching one. The comparison results demonstrate that the hybrid ARIMA-ANN model produces a lower RMSE than the ARIMA model, indicating improved forecasting accuracy. These findings suggest that exchange rate dynamics are influenced not only by linear patterns but also by complex nonlinear relationships, making the hybrid approach more effective in enhancing prediction accuracy.

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