The Cisadane Watershed is in a critical state, which has expanded residential areas upstream of Cisadane. Changes in land use and cover can impact a region's hydrological characteristics. The Soil and Water Assessment Tool (SWAT) is a hydrological model that can simulate the hydrological characteristics of the watershed affected by land use. This study aims to evaluate the impact of land use change on the hydrological characteristics of the Cisadane watershed using SWAT under different land use scenarios. The models were calibrated and validated, and the results showed satisfactory agreement between observed and simulated streamflow. The main river channel is based on the results of the watershed delineation process, with the watershed boundary consisting of 85 sub-watersheds. The hydrological characteristics showed that the maximum flow rate (Q max) was 12.30 m³/s, and the minimum flow rate (Q min) was 5.50 m³/s. The study area's distribution of future land use scenarios includes business as usual (BAU), protecting paddy fields (PPF), and protecting forest areas (PFA). The BAU scenario had the worst effect on hydrological responses due to the decreasing forests and paddy fields. The PFA scenario yielded the most favourable hydrological response, achieving a notable reduction from the baseline BAU in surface flow, lateral flow, and groundwater by 2%, 7%, and 2%, respectively. This was attributed to enhanced water infiltration, alongside increases in water yield and evapotranspiration of 3% and 15%, respectively. l Therefore, it is vital to maintain green vegetation and conserve land to support sustainable water availability.

In order to further alleviate the problems of large assessment deviations, low efficiency of trading organisation and difficulties in system optimisation in medium- and long-term market trading, the article proposes an optimisation model for continuous intra-month bidding trading in the electricity market that takes into account risk hedging. Firstly, the current situation of market players’ participation in medium and long-term trading is analysed; secondly, the impact of contract trading on reducing operational risks is analysed based on the application of hedging theory in the primary and secondary markets; finally, the continuous bidding trading mechanism is designed and its optimisation effect is verified. The proposed model helps to improve the efficiency of contract trading in the secondary market, maintain the stability of market players’ returns and accelerate the formation of a unified, open, competitive and well-governed electricity market system.

The root of the problem in this research is the fact that scientific writing with a national reputation is still low and the publication of scientific writing with a national reputation is also low, thus affecting the quality of lecturers at the University. To overcome this problem, this research developed a training management model that can improve the scientific writing skills of lecturers and familiarize lecturers to actively conduct nationally reputable scientific writing. The training management model in question is called the “National Reputable Scientific Writing Training Management” model. This type of research is development research or R&D to produce a valid, practical, and effective model, as well as all devices and research instruments related to the application of the model at the University. The results showed that: (1) the National Reputable Scientific Writing Training Management model is suitable for improving the scientific writing ability of lecturers; (2) the output of the National Reputable Scientific Writing Training Management model in the model group is significantly higher than the initial group (pre-model); (3) The average value of IP/IO from experts is 4.4 with a high category, from observers at stage I test is 4.0 with a high category, at stage II test is 4.7 with a high category and stage III test is 4.77 with a high category, so it is concluded that the National Reputable Scientific Writing Training Management model meets the criteria of effectiveness, practicality and implementation; (4) The response of university managers and respondents to the implementation of the model is quite satisfactory, both regarding the concept of the model, the application in technical implementation and their perception of the National Reputable Scientific Writing Training Management model; and (5) the National Reputable Scientific Writing Training Management model can be developed as an alternative implementation in training management at the university.

The research aimed to: 1) analyze components and indicators of digital transformation leadership among school administrators, 2) assess their leadership needs, and 3) develop mechanism models to promote this leadership. A mixed-method approach was applied, involving three sample groups: 8 experts, 406 administrators, and 7 experts. Data collection tools included semi-structured interviews, leadership scales, needs assessments, and focus group discussions, with analysis performed through construct validity testing, needs assessment, and content analysis. The findings revealed: 1) The components and indicators of digital transformation leadership showed structural validity, as confirmed by the model's alignment with empirical data (Chi-Square = 82.3, df = 65, p = 0.072, CFI = 0.998, TLI = 0.997, RMR = 0.00965, RMSEA = 0.0256). 2) Among the leadership components, "innovative knowledge" ranked highest in need (PNImodified = 0.075), followed by "ideological influence" (0.066), "consideration of individuality" (0.055), "intellectual stimulation" (0.052), and "inspiration" (0.053). 3) Mechanism models for promoting leadership emphasized enhancing these five components to strengthen administrators' skills in applying technology, managing teaching and development plans, and fostering innovation. Administrators were encouraged to tailor strategies to individual needs, inspire personnel, and create a commitment to organizational change and development. These mechanisms aim to equip administrators to effectively lead transformations, motivate staff, and drive educational institutions to adapt and thrive in evolving environments.

Catastrophes, like earthquakes, bring sudden and severe damage, causing fatalities, injuries, and property loss. This often triggers a rapid increase in insurance claims. These claims can encompass various types, such as life insurance claims for deaths, health insurance claims for injuries, and general insurance claims for property damage. For insurers offering multiple types of coverage, this surge in claims can pose a risk of financial losses or bankruptcy. One option for insurers is to transfer some of these risks to reinsurance companies. Reinsurance companies will assess the potential losses due to a catastrophe event, then issue catastrophe reinsurance contracts to insurance companies. This study aims to construct a valuation model for catastrophe reinsurance contracts that can cover claim losses arising from two types of insurance products. Valuation in this study is done using the Fundamental Theorem of Asset Pricing, which is the expected present value of the number of claims that occur during the reinsurance coverage period. The number of catastrophe events during the reinsurance coverage period is assumed to follow a Poisson process. Each impact of a catastrophe event, such as the number of fatalities and injuries that cause claims, is represented as random variables, and modeled using Peaks Over Threshold (POT). This study uses Clayton, Gumbel, and Frank copulas to describe various dependence characteristics between random variables. The parameters of the POT model and copula are estimated using Inference Functions for Margins method. After estimating the model parameters, Monte Carlo simulations are performed to obtain numerical solutions for the expected value of catastrophe reinsurance based on the Fundamental Theorem of Asset Pricing. The expected reinsurance value based on Monte Carlo simulations using Indonesian earthquake data from 1979–2021 is Rp 10,296,819,838.