Mewabahnya trend industri halal global menjadi isu krusial yang penting untuk dibahas oleh para penggiat ekonomi syariah, karena halal tidak hanya sekedar pemenuhan kebutuhan dan kepatuhan umat muslim terhadap syariah akan tetapi menjadi salah satu standar prioritas yang diakui dunia. Tujuan dilakukannya kajian ini ialah untuk menggambarkan secara komprehensif terkait posisi Indonesia disektor industri halal, sehingga hasil penelitian dapat dijadikan sebagai rujukan dalam menetapkan kebijakan bagi pemerintah maupun pemangku kepentingan dalam mengembangkan industri halal di Indonesia. Penelitian ini merupakan penelitian kualitatif deskriptif dengan menggunakan pendekatan teologi normatif dan fenomenologi, dengan sumber data sekunder yang diperoleh melalui buku, jurnal, artikel, data laporan, dan berbagai sumber keilmiahan yang relevan. Hasil penelitian diketahui bahwa kiprah industri halal di Indonesia begitu besar tidak hanya sektor makanan dan minuman, namun industri halal sudah melebar luas mencakup sektor keuangan syariah, fashion muslim, kosmetik, farmasi, travel, hotel, pariwisata, media dan termasuk rekreasi flim. Indonesia memiliki potensi besar untuk mengembangkan industri halal selain Indonesia sebagai negara penduduk muslim terbesar dunia, Indonesia juga memiliki nilai konsumsi yang besar di sektor halal, adanya regulasi hukum, dibentuknya KNEKS, sinergisitas stakeholders, adanya BPJPH dan berbagai potensi lain yang mendukung pengembangan industri halal di Indonesia yang berdaya saing global.

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.

PT.X, a coal mining company in South Kalimantan, Indonesia, plans to use the highwall mining method to excavate marginal reserves on the final slope to maintain production. However, the stability of the slope and determination of the highwall mining...

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.

Bridge is one of the important infrastructure facilities which functioned to connect roads that support the development of social and economic in a region. In Indonesia, each year, the limited fund is available to accommodate all construction projects. In practice, the government of Aceh Besar District has limited District Revenue and Expenditure Budgets (APBK) to finance the entire project of bridge construction. Considering that many other sectors still require APBK funding, the priority rank of the bridge development needs to be determined. This study aims to identify the dominant criteria in determining the development of bridges and the priority rank of bridge development projects. This study used a mixed method approach which is a qualitative and quantitative method. The Qualitative method is related to respondent perception through distributing questionnaires and the qualitative method is related to numbers used through the perception score of respondents from the analysis. Respondents are stakeholders and policymakers as many as 8 people. The questionnaire contains some criteria, namely the length of the bridge, construction costs, land use, accessibility, population, and regional development. Based on the literature review, those criteria can be used to obtain which bridge needs to be prioritized. Multi-Criteria Analysis is used to analyze those criteria from respondent perception. The results show that the dominant criteria in determining the construction of bridges in the project were construction costs with a weight of 0.35. It is also obtained that the bridge development project at first rank is the Kr. Keumeuruek with a value of 7.56.