KAJIAN PARAMETER PENINGKATAN DAYA SAING KONTRAKTOR KUALIFIKASI KECIL DAN MENENGAH DI INDONESIA

In 2014 the number of contractors in Indonesia reached about 142,000 companies with total employment of about 7.28 million people and the value of the construction sector reached Rp 826.62 trillion. The number of small and medium qualified contractors are more than 99% with total employment of about 92.35 %. However, the market share of small and medium qualified contractors only reach about 15% of the market share of national construction. So it is not balanced when compared with the big number of qualified contractors only about 1% of companies and 7.65 % of employments, but its market share will reach 85 % of the market share of national construction. Therefore it needs attention and improvement efforts by all of stakeholders. This research aims to analyze the relationship parameters of project management competencies, resources and capabilities, strategic decisions, performance and sustainability of the company to increase the competitiveness of small and medium qualified contractors in Indonesia. The data collected through questionnaires Likert scale (1-5) to 134 respondents at 13 provinces in Indonesia by the methods of stratified sampling, purposive sampling and proportional sampling. The data, further, are analyzed using SPSS and SEM-Smart PLS software. The analyzing data research are validated using direct observation to some small and medium qualified constructors in Surabaya. The result from this research sums up that the parameter analyzed parallel in gives positive and significant influence to the improvement of competitiveness of small and medium qualified contractor in Indonesia, those are in 1) project management competency influences the resources and capabilities, and influences the strategic decision making, 2) the resources and capabilities and strategic decision making influence the performance, 3) the performance directly influences the sustainability and indirectly influences but not significant on the competitiveness 4) the sustainability influences the competitiveness Keywords : resources, performance, strategy, sustainability, competitiveness, small-medium contractors

A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part I: theory

The set of equations for global ocean biogeochemistry deterministic models have been for-mulated in a comprehensive and unified form in order to use them in numerical simulations of the marine ecosystem for climate change studies (PELAGOS, PELAgic biogeochemistry for Global Ocean Simulations). The fundamental approach stems from the representation of marine trophic interactions and major biogeochemical cycles introduced in the European Regional Seas Ecosystem Model (ERSEM). Our theoretical formulation revisits and generalizes the stoichiometric approach of ERSEM by defining the state variables as Chemical Functional Families (CFF). CFFs are further subdivided into living, non-living and inorganic components. Living CFFs are the basis for the definition of Living Functional Groups, the biomass-based functional prototype of the real organisms. Both CFFs and LFGs are theoretical constructs which allow us to relate measurable properties of marine biogeochemistry to the state variables used in deterministic models. This approach is sufficiently generic that may be used to describe other existing biomass-based ecosystem model

Forecast and analysis assessment through skill scores

International audienceThis paper describes a first comprehensive evaluation of the quality of the ten days ocean forecasts produced by the Mediterranean ocean Forecasting System (MFS). Once a week ten days forecasts are produced. The forecast starts on Tuesday at noon and the prediction is released on Wednesday morning with less then 24 hr delay. In this work we have considered 22 ten days forecasts produced from the 16 August 2005 to the 10 January 2006. All the statistical scores have been done for the Mediterranean basin and for 13 regions in which the Mediterranean sea has been subdivided. The forecast evaluation is given here in terms of root mean square (rms) values. The main skill score is computed as the root mean square of the difference between forecast and analysis (FA) and forecast and persistence (FP), where the persistence is defined as the average of the day of the analysis corresponding to the first day of the forecast. A second skill score (SSP) is defined as the ratio between rms of FA and FP, giving the percentage of accuracy of the forecast with respect to the persistence (Murphy 1993). The rms of FA is always better than FP and the FP rms error is double than the rms of FA. It is found that in the surface layers the error growth is controlled mainly by the atmospheric forcing inaccuracies while at depth the forecast errors could be due to adjustments of the data assimilation scheme to the data insertion procedure. The predictability limit for our ocean forecast seems to be 5?6 days connected to atmospheric forcing inaccuracies and to the data availability for assimilation

Use of real-time observations in an operational ocean data assimilation system: the Mediterranean case

Real-time observations are essential for operational forecasting that in turn can be used to predict changes of the state of the ocean and its associated biochemical fi elds. In addition, real-time observations are useful to detect changes in the past with the shortest delay, to standardize practices in data collection and to exchange data between remote regions of the ocean and seas. Th e drawback is that real-time observations could be less accurate than their delayed mode counterparts due to the time constraints for data dissemination. In situ real-time data are usually decimated to be transmitted in real time (loss of accuracy and resolution), whereas satellite data are corrected with approximate algorithms and less ancillary data. Delayed mode quality control analysis increases the value of the observational data set, fl agging outliers and producing climatological estimates of the state of the system. Th us real-time data, together with a modelling system and the climatological estimates, give the appropriate information for scientifi c studies and applications. Th e principles of operational science started to develop in the 1940s and 1950s, based on the combined use of real-time data and modelling systems that can extend the information from observations in space and time. Operational science is based on a sound knowledge of the dynamics and processes for the space/timescales of interest and operational meteorology and oceanography have started to implement these principles to weather and ocean forecasting activities. In the past 20 years, operational meteorology has become a reality with a network of in situ and satellite observations that has made the weather forecast capable of extending the theoretical limit of predictability of the atmosphere (only one-two days theoretically, now forecasts are useful for more than fi ve days on average). Today meteorological observations are mainly used in their assimilated form even if observations are still collected for specifi c process-oriented studies. Recently the meteorological re-analysis projects (Gibson et al., 1997; Kalnay et al., 1996) have released a wealth of data to be understood and analysed. Th ese data sets are coherent and approximately continuous (daily), fi lling the observational gaps in space and time with a dynamical interpolation scheme. Th e model and the real-time observations are fused in one best estimate of the state of the system by data-assimilation techniques that have been developed to a great degree of sophistication in recent years (Lorenc, 2002). Th e re-analysis data are now forming the basic reference data set to understand climate variability in the atmosphere and upper oceans. Ch20.indd 73Ch20.indd 733 3/7/07 9:58:01 AM Habwatch 734 Dynamical interpolation/extrapolation of observational data for operational forecasting in the ocean began to be investigated at the beginning of the 1980s and the fi rst successful forecasts were carried out in the open ocean (Robinson and Leslie, 1985). Th ese exercises required real-time data that were initially collected with rapid ship surveys realizing adaptive sampling schemes and collecting a combination of traditional recoverable and expendable instruments (CTD, XBTs). At the same time but in a totally independent way, shelf scale and coastal real-time data from moored and drifting sensors such as meteorological buoys and sea-level stations started to be used for shelf scale storm surge operational forecasting (Prandle, 2002). Operational oceanography is now building on this experience and considers real-time measurements from opportunity platforms and satellites in a manner very similar to operational meteorology. Th is chapter aims to show the use of real-time observations in a state-of-the-art ocean-predicting system realized in the Mediterranean. We discuss the pre-processing schemes required to properly assimilate the observations into an operational nowcasting/ forecasting system, elucidate the role and impact of diff erent observations in the assimilation system and show the use of real-time data to evaluate quality of the modelling system. We start with the description of the Mediterranean Forecasting System (MFS) real-time observing system and pre-processing quality control in Section 20.2, we then describe the modelling and assimilation system in relation to the impact of diff erent real-time observations in Section 20.3. In Section 20.4 we evaluate the consistency, quality and accuracy of the forecasting system using model-data intercomparison and Section 20.5 offers conclusion

A high resolution free surface model of the Mediterranean Sea

International audienceThis study describes a new model implementation for the Mediterranean Sea which has the presently highest vertical resolution over the Mediterranean basin. The resolution is of 1/16°×1/16° in horizontal and 71 unevenly spaced vertical levels. This model has been developed in the frame of the EU-MFSTEP project and it is the operational forecast model presently used at the basin scale. For the first time in the Mediterranean, the model considers an implicit free surface and this characteristics enhances the model capability to simulate the sea surface height variability. In this study we show the calibration/validation experiments done before and after the model has been used for forecasting. The first experiment consist of six years of a simulation forced by a perpetual year forcing and the other experiment is a simulation from January 1997 to December 2004, forcing the model with 6 h atmospheric forcing fields from ECMWF. For the first time the model Sea Level Anomaly is compared with SLA and with ARGO data to provide evidence of the quality of the simulation. The results show that this model is capable to reproduce most of the variability of the general circulation in the Mediterranean Sea even if some basic model inadequacies stand out and should be corrected in the near future

Impact of Multi-altimeter Sea Level Assimilation in the Mediterranean Forecasting Model

In this paper we analyze the impact of multi-satellite altimeter observations assimilation in a high-resolution Mediterranean model. Four different altimeter missions (Jason-1, Envisat, Topex/Poseidon interleaved and Geosat Follow-On) are used over a 7-month period [September 2004, March 2005] to study the impact of the assimilation of one to four satellites on the analyses quality. The study highlights three important results. First, it shows the positive impact of the altimeter data on the analyses. The corrected fields capture missing structures of the circulation and eddies are modified in shape, position and intensity with respect to the model simulation. Secondly, the study demonstrates the improvement in the analyses induced by each satellite. The impact of the addition of a second satellite is almost equivalent to the improvement given by the introduction of the first satellite: the second satellite data brings a 12% reduction of the root mean square of the differences between analyses and observations for the Sea Level Anomaly (SLA). The third and fourth satellite also significantly improve the rms, with more than 3% reduction for each of them. Finally, it is shown that Envisat and Geosat Follow-On additions to J1 impact the analyses more than the addition of Topex/Poseidon suggesting that the across track spatial resolution is still one of the important aspects of a multi-mission satellite observing system. This result could support the concept of multi-mission altimetric monitoring done by complementary horizontal resolution satellite orbits

MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting – Part 2: Numerical simulations and validations

Abstract. In this paper we use MEDSLIK-II, a Lagrangian marine surface oil spill model described in Part 1 (De Dominicis et al., 2013), to simulate oil slick transport and transformation processes for realistic oceanic cases, where satellite or drifting buoys data are available for verification. The model is coupled with operational oceanographic currents, atmospheric analyses winds and remote sensing data for initialization. The sensitivity of the oil spill simulations to several model parameterizations is analyzed and the results are validated using surface drifters, SAR (synthetic aperture radar) and optical satellite images in different regions of the Mediterranean Sea. It is found that the forecast skill of Lagrangian trajectories largely depends on the accuracy of the Eulerian ocean currents: the operational models give useful estimates of currents, but high-frequency (hourly) and high-spatial resolution is required, and the Stokes drift velocity has to be added, especially in coastal areas. From a numerical point of view, it is found that a realistic oil concentration reconstruction is obtained using an oil tracer grid resolution of about 100 m, with at least 100 000 Lagrangian particles. Moreover, sensitivity experiments to uncertain model parameters show that the knowledge of oil type and slick thickness are, among all the others, key model parameters affecting the simulation results. Considering acceptable for the simulated trajectories a maximum spatial error of the order of three times the horizontal resolution of the Eulerian ocean currents, the predictability skill for particle trajectories is from 1 to 2.5 days depending on the specific current regime. This suggests that re-initialization of the simulations is required every day