Articles

Analysis of Meteorological–Hydrological Drought Propagation for the Development of a Drought Early Warning System in the Special Region of Yogyakarta (DIY): A Case Study of the 2023 El Niño Event

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The drought that affected the Special Region of Yogyakarta (DIY) as a consequence of the 2023 El Niño event was characterized by prolonged dry conditions resulting from exceptionally low rainfall, depletion of water resources, and significant impacts on agriculture, dams, reservoirs, as well as the socio-economic conditions of local communities. This study aims to examine, in a spatiotemporal framework, the influence of El Niño on drought conditions across the DIY Province and to analyze the stages and propagation of meteorological, agricultural, and hydrological drought. The analysis uses rainfall observations from 122 rain gauges and three BMKG stations. Drought assessment begins with rainfall deficit analysis, followed by meteorological drought identification using the Standardized Precipitation Index (SPI), agricultural drought assessment using the groundwater availability index (KAT), and hydrological drought assessment using the Hydrological Drought Index (HDI/IKH). The results show that meteorological drought was first detected in April 2023 in Bantul, Gunungkidul, and Kulon Progo Regencies, then expanded toward the central and northern parts of DIY in May 2023. Agricultural drought emerged in June 2023 in the same three regencies, indicated by KAT values falling below 40% of field capacity. The drought reached its peak in October 2023 as hydrological drought, when reservoir volume availability at Q80 dropped below 50%. Meteorological drought appeared 1–2 months after the onset of rainfall deficit (dry season), progressed into agricultural drought with a lag of 2–3 months, and culminated in hydrological drought with a lag of 5–6 months. The development of a regional Integrated Drought Early Warning System should incorporate monitoring and forecasting outputs, enabling drought alerts to be issued 3–6 months before critical conditions arise.

Leveraging Z-Score and Financial Ratio as Early Warning System to Mitigate Supply Chain Disruption at PT Gunung Raja Paksi TBK

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PT Gunung Raja Paksi faces significant challenges in maintaining profitability, which impacts its overall financial health. Key risk factors include the volatility of raw material prices, intense competition within the steel industry, and economic downturns. Fluctuations in raw material prices affect production costs and profit margins. Rising raw material costs can squeeze margins unless passed on to customers, which is challenging in a competitive market. The competitive landscape requires the company to balance competitive pricing with quality, leading to potential price wars and further margin erosion. Additionally, economic downturns reduce demand for steel products, impacting sales volumes and revenues. This study comprises four key components: risk assessment, Z-score model analysis, financial ratio analysis, and risk prevention formulation. The risk assessment, covering both internal and external factors, identifies major risks including supply chain disruptions, financing challenges, weather-related issues, major accidents, and steel market volatility. Analysis using the Z-score model, based on data from the past five years, reveals significant profitability risks for the company. Further examination of financial ratios shows that the company’s profitability ratios are generally below the industry average. Integrating these qualitative and quantitative findings indicates that the company should prioritize addressing supply chain disruption risks. Consequently, an early warning system has been developed, and risk prevention strategies have been established.