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All Journal bit-Tech Journal of Diverse Medical Research: Medicosphere
Fairuz Haniyah Ramadhani
Faculty Of Medicine, Universitas Pembangunan Nasional Veteran Jawa Timur, Surabaya, Indonesia
Computer Science & IT Immunology & microbiology Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences

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The Relationship Between Temperature, Greenhouse Gas Emissions, and Malaria Cases in Indonesia: Original Article Fairuz Haniyah Ramadhani; Azizah R.; Mir Atudz Dzikro
Journal of Diverse Medical Research : Medicosphere Vol. 3 No. 3 (2026): Journal of Diverse Medical Research : Medicosphere 2026
Publisher : Faculty of Medicine - Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jdiversemedres.v3i3.320

Abstract

Malaria is still a public health problem in Indonesia and had the potential to be affected by climate change due to greenhouse gas emissions. This study aimed to analyze the correlations among greenhouse gas emissions across sectors, temperature, humidity, and malaria incidence in Indonesia. The study used an ecological design with a quantitative observational approach based on national aggregate data for the period 2000–2019. Greenhouse gas emission data were obtained from national inventory reports, temperature and humidity data from BMKG, and malaria data from BPS. Statistical analysis was carried out using the Spearman rank correlation test. The results showed that only the emissions of the Industrial Processes and Product Use (IPPU) sector had a strong and significant positive correlation with temperature (p = 0.025). In contrast, the other emission sectors were not significant. In addition, temperature and humidity showed a strong, significant negative correlation with malaria incidence (p = 0.007 and p = 0.005). These findings confirm that the relationship between climate and malaria is complex and non-linear, and is influenced by non-climatic factors such as strengthening of health systems and vector control.
Analisis Peramalan IHSG Menggunakan Model ARIMA-ARCH untuk Mengatasi Efek Heteroskedastisitas Nadia Puspita Adinda; Fairuz Izzaty Salamy; Salsabilla Fatika Subagyo; Dewi Puspita Sari; Shaifudin Zuhdi
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3515

Abstract

The Indeks Harga Saham Gabungan (IHSG) is widely recognized as a central indicator of the Indonesian capital market and reflects overall market performance, investor sentiment, and macroeconomic conditions. Accurate forecasting of the IHSG is essential for investors, financial institutions, and policymakers; however, financial time series data are often characterized by non-stationarity and volatility clustering, which limit the effectiveness of conventional forecasting models. This study applies a hybrid Autoregressive Integrated Moving Average–Autoregressive Conditional Heteroskedasticity (ARIMA–ARCH) model to forecast the IHSG by simultaneously modeling the conditional mean and time-varying volatility. The ARIMA model is used to capture linear temporal dependence in the mean process, while the ARCH component addresses heteroskedasticity in the residuals by allowing conditional variance to change over time. Daily IHSG closing price data from September 2024 to September 2025 are analyzed using the Box–Jenkins methodology, including stationarity analysis, model selection, parameter estimation, and diagnostic validation. The empirical results indicate that the hybrid ARIMA–ARCH model provides improved forecasting accuracy compared to a standalone ARIMA model, particularly in periods of heightened market volatility. The ARCH component successfully captures volatility clustering and enables the construction of dynamic volatility-based prediction intervals, offering additional risk-related insights beyond point forecasts. These findings demonstrate that the ARIMA–ARCH framework is effective for modeling IHSG dynamics and can support better risk management, portfolio optimization, and decision-making processes in the Indonesian capital market.
Co-Authors Azizah R. Dewi Puspita Sari Mir Atudz Dzikro Nadia Puspita Adinda Salsabilla Fatika Subagyo Shaifudin Zuhdi