Rainfall-induced landslides are widespread in Indonesia, particularly in West Java, where volcanic residual soils are typically stable but may become unstable during heavy rainfall. This study aims to back analyze the geotechnical factors contributing to the Cimanggung landslide in 2021. The methods applied in this study include site investigations, laboratory testing, and numerical modeling. We performed deterministic, coupled seepage-slope stability analysis and Monte Carlo probabilistic analysis to assess the slope performance prior to and after rainfall infiltration. The results reveal that the initial water level significantly affects slope stability, and heavy rainfall infiltration triggered the landslide’s initiation. The deep water table (over 20 m below ground level) maintains the slope stability, and increasing the water table to 16 m compromises its stability. Heavy rainfall infiltration reduces suction in the unsaturated zone, decreasing the shear strength and triggering landslides. The heavy rainfall infiltration did not penetrate deep enough to raise the water table; rather, poor urban drainage on the upper slope caused it. Rainfall infiltration caused wetting in the upper zone, weakening the slope and causing loss of support. It is recommended that effective drainage management and integrated slope monitoring be applied to mitigate landslide risks in this region.

Landslides represent a recurrent hazard in tropical mountain environments, where rapid urbanization and extreme rainfall amplify disaster risk. The Sentani region of Papua, Indonesia, is highly vulnerable, as demonstrated by the catastrophic debris flows of March 2019 that caused fatalities and widespread losses. This study developed high-resolution landslide susceptibility maps for Sentani using an ensemble machine learning framework. Three base learners—Random Forest, eXtreme Gradient Boosting (XGBoost), and CatBoost—were combined through a logistic regression meta-learner. Predictor redundancy was controlled using Pearson correlation and Variance Inflation Factor/Tolerance (VIF/TOL). The landslide inventory was constructed from multitemporal satellite imagery, integrating geological, topographic, hydrological, environmental, and seismic factors. Results showed that lithology, Slope Length and Steepness Factor (LS Factor), and earthquake density consistently dominated model predictions. The ensemble achieved the most balanced predictive performance, Area Under the Curve (AUC) > 0.96, and generated susceptibility maps that aligned closely with observed landslide occurrences. SHapley Additive Explanations (SHAP) analyses provided transparent, case-specific insights into the directional influence of key factors. Collectively, the findings highlight both the robustness and interpretability of ensemble learning for landslide susceptibility mapping, offering actionable evidence to support disaster preparedness, land-use planning, and sustainable development in Papua.

The hydrothermal dewatering (HTD) process was carried out using 16 coal samples obtained from several regions in Indonesia. This research aims to identify the dominant parameters that influence ash deposition during coal combustion in a boiler or gasifier due to the HTD process. This research was conducted due to the lack of clear and comprehensive information regarding this issue. Therefore, to understand the effect of HTD on ash deposition, an analysis of the chemical composition of ash and the ash melting temperature (AFT) was carried out. To verify the data obtained from the experimental analysis, statistical methods such as paired sample t-test and primary component analysis were applied to obtain the dominant parameters influencing ash deposition due to HTD. Eight parameters, namely SiO₂, Fe₂O₃, slagging viscosity index (SR), Babcock index (Rs), initial deformation temperature, softening temperature, hemispherical temperature, and fluid temperature under oxidative conditions, have the greatest influence on ash deposition due to the HTD process. Based on the average values of SR and Rs, raw coal and processed coal samples have the same ash deposition trend. On the other hand, based on AFT under oxidation conditions, processed coal has a higher AFT, indicating that the tendency for ash deposition is lower than raw coal. Therefore, the HTD process can be used to improve the quality of low-grade coal. As an implication, low-grade coal, which has not been widely utilized in Indonesia, due to several constraints regarding its characteristics, through the HTD process can be optimized where coal utilization is a bridge towards the use of green energy which is being intensively pursued.

ANALYSIS OF METALS MINING SECTOR LINKAGE ON NATIONAL ECONOMIC

This research aims to analyze the resilience of Indonesia’s copper ore reserves in supporting sustainable copper cathode production targets, in line with national downstream policies. Using a quantitative approach, this study evaluates secondary data from national mineral reserve reports and the production capacity of major smelters. The analysis is conducted by calculating the reserve-to-production ratio to project mine life under three scenarios of increasing domestic refining capacity, including an aggressive scenario of 1.145 million tons per year. The results indicate that based on current reserves, the estimated mine life is approximately 21 years under maximum production capacity. However, with potential resource-to-reserve conversion of approximately 4.318 billion tons and accounting for ore grade decline, the life of Indonesia’s copper ore reserves is projected to extend until 2077. The study also reveals a structural gap, where 70% of cathode production is still export-oriented due to low domestic manufacturing absorption. The uniqueness of this paper lies in the integration of geological reserve aspects with the dynamics of downstream policies and industrial structure theories. Practically, this study provides important implications for the government in formulating strategic reserve management and emphasizes the urgency of integrating upstream smelting with downstream manufacturing to ensure long-term industrial sovereignty.

Indonesia is currently reviewing the use of underground coal gasification (UCG) technology to utilize deep-seated coal. UCG may exploit the coal deposit that is not feasible for open-pit mines due to its great depths. In this study, the UCG plant in two coal mines, the Kideco Jaya Agung (KJA) and the Indominco (IMM) coal mines, will be compared their economics in producing low heating value gas with a capacity of 170,000 MJ/hour. The UCG plants implement the linking vertical well (LVW) technique combined with reverses combustion linking (RCL). The discounted cash flow (DCF) method is used for financial analysis to determine the minimum selling price of UCG low heating value gas. The study aims to understand the economic feasibility of applying UCG technology to Indonesia’s different characteristics of coal deposits. The results show the minimum prices of the low heating value UCG gas of KJA and IMM UCG plants are USD 3/MMBTU and USD 3.57/MMBTU, respectively. The operating cost of the IMM UCG is higher than that of the KJA UCG plant due to its thinner and deeper coal seams.