Decision making of maritime development scenario on the impact of naval base for supporting navy ships operations

The Indonesian Navy is the spearhead in maintaining maritime security in Indonesian waters. In carrying out its main tasks, the Indonesian Navy has components of an Integrated Fleet Weapon System in which there are elements of Ships and Naval Bases. To ensure the effectiveness of carrying out operations by ship elements, ship operations are supported by the Naval Base as the organizer of the support function. Naval Base's carrying capacity consists of 5 (five) support functions, including: (1) support for anchoring facilities; (2) support for supply facilities; (3) support for maintenance and repair facilities; (4) support facility maintenance personnel; and (5) support for base development facilities. Naval Base does not yet have its dock to support anchoring facilities for ship operations. In addition to cooperation in the use of the Naval Base anchorage facility, there is also cooperation in port security, both in terms of land and port water aspects. As the number of ship visits at Naval Base Harbor increases, the dock utility increases. The increase in dock utility resulted in a decrease in port services which also resulted in a decrease in the Naval Base Carrying Capacity. To improve port services, Pelindo III implements the port development program contained in the Naval Base Port Master Plan in Permen KP number 792 of 2017. In this study, an analysis of the impact of the Naval Base Port development policy on the carrying capacity of the Naval Base was carried out. The data analysis uses System Dynamics modeling with a simulation period of 30 years in 3 development scenarios, namely short-term scenarios, medium-term scenarios, and long-term scenarios. From the simulation results, it is found that the construction of the Naval Base port affects the Naval Base Carrying Capacity with an average increase of 1.8% in each policy scenario. The increase in Naval Base Carrying Capacity has an effect on increasing Ship Operations by an average of 1.8% and also increasing the Security of Naval Base Harbor by an average of 0.14%. The results of the analysis of this study can be used as consideration for policymaking by the Navy.

SOCIAL ECONOMY ENTITIES IN SHAPING SOCIAL POLICY – DIFFERENT ROLES AND AREAS OF INFLUENCE

This paper analyses a myriad of roles played by the social economy entities in selected sub-areas of social policy, such as family and foster care support, senior citizen policy or prevention of poverty and social exclusion. The author points out the role of social economy entities in programming and implementation, monitoring and evaluation of performance, analysis of challenges and development scenarios, and advocacy for the rights and interests of various groups in need of social policy support.

Modeling of development scenarios for industrial-natural system

An interrelated set of methods for synthesis, static and dynamic comparison of various admissible scenarios for development of industrial-natural systems is briefly introduced and analyzed. These methods make it possible to solve various issues of design, strategic and operational management of such systems including emergencies, as well as to coordinate interactions of several decision makers involved within one system.

The realities of the economy of Kazakhstan: the possible impact of the new global economic crisis

The emergence of a pandemic has a great impact on the macroeconomic processes taking place in the world. These processes are also superimposed by the crises of political transformation associated with the emergence of new political elites in global centers that influence the management of economic and political processes around the world. The article examines the probability of a possible economic crisis in Kazakhstan and its consequences. Today, it is very important for the country to objectively analyze all our achievements and failures in economic policy over the past thirty years in order to move forward. The emergence of new payment instruments, digital currency and cryptocurrency contributes to the destruction of the old model of financing the economy, which will inevitably lead to global changes in the world economy and a possible crisis in all areas of development. The main place where these events related to the virtualization of financial resources take place are the stock exchanges and stock markets of the leading countries of the world economy, the so–called “G-7”, and China. Reduction of energy prices may cause deterioration of the balance of payments and sharply increase the costs from the funds of the National Fund of the Republic of Kazakhstan. High inflation under any economic development scenarios can accelerate and go beyond the boundaries of the “inflation corridor” and exceed 10%. Another factor of pressure on the financial and banking sector is an increase in the interest rate at the Central Bank of Russia in the near future to 6.75–7.0%, given our close economic ties within the EAEU.

Landscape Evolution and Simulation of Rural Settlements around Wetland Park Based on MCCA Model and Landscape Theory: A Case Study of Chaohu Peninsula, China

As a transitional zone between urban and rural areas, the peri-urban areas are the areas with the most intense urban expansion and the most frequent spatial reconfiguration, and in this context, it is particularly important to reveal the evolution pattern of rural settlements in the peri-urban areas to provide reference for the rearrangement of rural settlements. The study takes five townships in the urban suburbs, and explores the scale, shape, spatial layout, and spatial characteristics of the urban suburbs of Hefei from 1980 to 2030 under the influence of urban-lake symbiosis based on spatial mathematical analysis and geographical simulation software. The study shows that: (1) the overall layout of rural settlements in the study area is randomly distributed due to the hilly terrain, but in small areas there is a high and low clustering phenomenon, and the spatial density shows the distribution characteristics of “high in the east and low in the west”; (2) since the reform and opening up, there are large spatial differences in the scale of rural settlements in the study area. (3) Different development scenarios have a strong impact on the future spatial pattern of rural settlement land use within the study area, which is a strong reflection of policy.

Subsurface-to-Economics Closing the Loop on Uncertainty Analysis

We are all aware that our future is uncertain. Although some aspects can be predicted with more certainty and others with less, essentially everything is uncertain. Uncertainty exists because of lack of data, lack of resources, and lack of understanding. We cannot measure everything, so there are always unknowns. Even measurements include measurement errors. Also, we do not always have enough resources to analyze the data obtained. In addition, we do not have a full understanding of how the world, or the universe, works (Park 2011). Every day we find ourselves in situations where we must make many decisions, big or small. We tend to make the decisions based on a prediction, despite knowing that it is uncertain. For instance, imagine how many decisions are made by people every day based on the probability of it raining tomorrow (i.e., based on the weather forecast). To have a good basis for making a decision, it is of critical importance to correctly model the uncertainty in the forecast. In the oil and gas industry, uncertainties are large and complex. Oil and gas fields have been developed and operated despite tremendous uncertainty in a variety of areas, including undiscovered media and unpredictable fluid in the subsurface, wells, unexpected facility and equipment costs, and economic, political, international, environmental, and many other risks. Another important aspect of uncertainty modeling is the feasibility of verifying the uncertainty model with the actual results. For example, in the weather forecast it was announced that the probability of raining the next day was 20%. And the next day it rained. Do we say the forecast was wrong? Can we say the forecast was right? In order to make sure the uncertainty model is correct; we should strictly verify all the assumptions and follow the mathematically, statistically, proven-to-be-correct methodology to model the uncertainty (Caers et al. 2010; Caers 2011). In this paper, we show an effective, rigorous method of modeling uncertainty in the expected performance of potential field development scenarios in the oil and gas field development planning given uncertainties in various domains from subsurface to economics. The application of this method is enabled by using technology as described in a later section.