Penerapan Sanksi Administratif bagi Pemberi Kerja yang Belum Mendaftarkan Pekerjanya Menjadi Peserta Program Jaminan Kesehatan Nasional Kartu Indonesia Sehat (JKN KIS)

Rakyat Indonesia. sebagian besar adalah .pekerja. Sebagai pekerja. kita harus dijamin jaminan kesehatannya .oleh pemberi kerja. Hal ini sesuai dengan Pasal 14 .Undang-undang Nomor 24 Tahun 2011.. tentang Badan Penyelenggara. . Jaminan Sosial. Setiap pemberi kerja wajib .mendaftarkan. pekerjanya .sebagai anggota BPJS Kesehatan. Apabila pemberi kerja. tidak mendaftarkan.. pekerjanya maka diatur dalam. . Peraturan Pemerintah Nomor 86. Tahun 2013. tentang Tata .Cara.Pengenaan Sanksi Administratif .kepada Pemberi Kerja selain. .Penyelenggara dan Setiap orang, Selain Pemberi Kerja, Pekerja dan. Penerima Bantuan Iuran dalam Penyelenggaran Jaminan Sosial. Permasalahan dalam penelitian ini adalah 1. Bagaimana penerapan sanksi administratif bagi pemberi. kerja yang belum mendaftarkan. pekerjanya menjadi peserta. program JKN KIS? 2. Bagaimana upaya. peningkatan kesadaran pemberi .kerja agar mendaftarkan. pekerjanya menjadi peserta program JKN KIS? 3. Bagaimana upaya peningkatan kepatuhan .pemberi kerja untuk memenuhi kewajibannya membayar iuran / premi .peserta program JKN KIS?. Penelitian ini menggunakan .metode penelitian .normatif. Upaya peningkatan kesadaran. pemberi kerja agar mendaftarkan .pekerjanya menjadi .peserta program JKN KIS melalui kerjasama strategis .dengan instansi pemerintah, misal.Pelayanan .Terpadu Satu. Pintu, BPJS Ketenagakerjaan, Dinas Tenaga Kerja. dan Transmigrasi, dan Kejaksaan dan melakukan sosialisasi. dengan pemberi kerja. dan pekerja. Melalui kerjasam. dengan instansi pemerintah .tersebut juga dapat meningkatkan kepatuhan pemberi kerja. untuk memenuhi kewajibannya .membayar iuran premi .JKN KIS. Harapannya pemerintah .agar dapat mengkaji kembali .peraturan yang telah berjalan terkait .dengan tata cara pengenaan sanksi administratif kepada .pemberi kerja.Kata Kunci : Sanksi Administratif, .Program JKN KIS, .Pemberi Kerja, .Pekerj

Sentinel-2 Recognition of Uncovered and Plastic Covered Agricultural Soil

Medium resolution satellite data, such as Sentinel-2 of the Copernicus programme, offer great new opportunities for the agricultural sector, and provide insights on soil surface characteristics and their management. Soil monitoring requires a high-quality dataset of uncovered and plastic covered agricultural soil. We developed a methodology to identify uncovered soil pixels in agricultural parcels during seedbed preparation and considered the impacts of clouds and shadows, vegetation cover, and artificial covers, such as those of greenhouses and plastic mulch films. We preserved the spatial and temporal integrity of parcels in the process and analysed spectral anomalies and their sources. The approach is based on freely available tools, namely Google Earth Engine and R Programming packages. We tested the methodology on the northern region of Belgium, which is characterised by small, fragmented parcels. We selected a period between mid-April to end-May, when active agricultural management practices leave the soil bare in preparation for the main cropping season. The spectral angle mapper was used to identify soil covered by non-plastic greenhouses or temporary soil covers, such as plastic mulch films. The effect of underlying soil on temporary covers was considered. The retrogressive plastic greenhouse index was used for detecting plastic greenhouses. The result was a high quality dataset of potential bare uncovered agricultural soil that allows further soil surface characterisation. This offered an improved understanding of the use of artificial covers, their spatial distribution, and their corresponding crops during the considered period. Artificial covers occurred most frequently in maize parcels. The approach resulted in precision values exceeding 0.9 for the detection of temporary covers and non-plastic greenhouses and a sensitivity value exceeding 0.95 for non-plastic and plastic greenhouses

Remote Sensing of the Intertidal Zone: Aspects of Classification and Spectral/Spatial Resolution (Teledectie van intergetijdengebieden: aspecten van classificatie en spectrale/spatiale resolutie)

nrpages: 185status: publishe

Site-Dependent classes for the classification of intertidal sediments

The biophysical properties of intertidal sediments highly affect the stability of an intertidal area. Therefore,the characterization of intertidal sediments according to major biophysical properties is essential. Remote sensing technology has been offering great alternatives to classical data collection methods, where imagery is frequent and gives full spatial coverage of the study area. Various methods have been used to characterize sediment properties using remotely sensed imagery, including the highly popular pixel-based supervised classification. The typically considered biophysical properties are grain-size distribution, organic matter content, moisture content, and chlorophyll a content. To carry out a supervised classification, classes have to be specified in advance. In literature, these classes have been selected using various scientific or case-dependent justifications due to the challenging fuzzy nature of sediment classes. For example, the limits between wet and dry or sandy and muddy sediments are not easily defined as hard boundaries. Due to this case-dependent nature of the classification, comparing classified imagery of different study sites or different images of the same site has not been practical. This paper addresses the possibility of finding site-dependent classes, instead of case-dependent classes for the classification of the IJzermonding, an intertidal flat in Belgium. This is carried out using field spectra of various years. These spectra indicate the possibility of obtaining thresholds for the different properties using unsupervised classification. On this basis, thresholds for sediment classes are chosen. In a last step, the image is classified in a supervised manner by means of the Bayesian Pairwise Classifier approach using the thresholds set in the previous step. Finally, the classification accuracy is compared with respect to other used thresholds from literature.status: publishe

Assessment of unsupervised classification techniques for intertidal sediments

status: publishe

RawMatCop: Developing Skills at the intersection between Earth observation and the raw materials community

The RawMatCop programme was launched in 2017 and aims to develop skills, expertise, demonstrations, and applications of Copernicus data to the raw materials sector. It is co-funded by the European Commission (DG for Internal Market, Industry, Entrepreneurship and SMEs) and the EIT RawMaterials (RawMaterials Academy). Raw materials have become increasingly important to the European Union's economy, growth, and competitiveness. In this context, the EU aims to facilitate the exchange of best practices among its member states to improve the sustainable and safe supply of raw materials to the EU economy and society. Thus, monitoring of mining activities and environmental impact of waste and residue management are key issues of that strategy. With state-of-the-art spaceborne imagery, Copernicus has a strong potential in contributing to EU’s requirements and expectations. The aim of RawMatCop is to illustrate the usefulness of Copernicus data through three 'Research & Application Areas’ relevant for the raw materials sector: (1) multi-scale and multi-source exploration, (2) spatiotemporal mapping of dust dispersion around mining sites, (3) monitoring of surface/subsurface deformation. Multispectral data proves to be an incredible tool for regional scale mapping of surface alterations associated to mineralization or mining activities. One clear advantage of Sentinel-2 data over other sensors is that it has a good coverage of the visible and near infrared portion of the electromagnetic spectrum, which makes it an ideal tool for mapping iron-oxides. The current activities of RawMatCop include mapping alterations and iron features associated to Volcanic Hosted Massive Sulfides (Iberian Pyrite Belt, Spain) as well as mapping the weathering of lateritic profiles and iron-oxide associated to active mining in New Caledonia. For this purpose, several workflows based on downscaling from satellite-based to in-situ observations are being tested. Furthermore, RawMatCorp is also contributing to the consistency assessment of popular atmospheric correction approaches used for Sentinel-2 processing (iCOR, Sen2Cor, MAJA) and the influence of the mining setting on their performance. Moreover, ground deformation is one of the most important hazards related to mining activities, and RawMatCorp is also addressing this topic through monitoring the Riotinto mine (SW Spain). This monitoring utilizes SAR and passive seismic techniques to develop a joint Early Warning System aiming to reduce risks on ground mechanical integrity.RAWMatCop - minEOdus

Forecasting Domestic Water Demand Using Meteorological and Satellite Data: Case Study of Greater Beirut Area

peer reviewedGreater Beirut Area (GBA) is expected to suffer from various socio-economic burdens caused by climate change impacts, including those related to rising temperatures, reduced water availability, increased heat waves and heat island effect, and others. This study addresses future changes in water demand in GBA through utilizing water demand patterns, meteorological data, and remote sensing data. Initially, the relationships between satellite remotely sensed data on Land Surface Temperature (LST) and other weather parameters were tested for correlation. Water demand models showed that LST and air temperature had a high positive correlation with temperature, positive correlation with solar radiation and wind speed, and high negative correlation with precipitation. Single variable linear regression models were developed to predict changes in domestic water demand using atmospheric pressure and temperatures (average, minimum, and maximum) (R2 > 0.5), and a multivariable linear regression model was obtained for the city of Beirut. In addition, temperature-based models were used to forecast future water demand under four climate Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0, and 8.5). The results showed an anticipated increase, during the dry period, of 45–90 thousand cubic meter per month on the short term (2020–2039) and 90–270 thousand cubic meter per month on the long term (2080–2099). Recommendations for the way forward were provided

Mapping mineral chemistry of a lateritic outcrop in new Caledonia through generalized regression using Sentinel-2 and field reflectance spectra

Mining is fundamental for human development, yet it currently requires innovative spatial techniques as it faces diverse environmental and social pressures. With the free Sentinel-2 data of the Copernicus programme, new opportunities arise for studies related to nickel laterite, especially with its reported potential in mapping iron- oxide. This work utilizes samples from drill-holes extracted from Tiebaghi, New Caledonia. The chemical composition and the hyperspectral reflectance of each sample are obtained. The reflectance spectra are re- sampled to Sentinel-2's characteristics, and generalized linear regression was used to accurately predict Fe2O3, MgO, SiO2, Al2O3, and nickel content where three regression approaches were compared: Ridge, Elastic Net, and the Least Absolute Shrinkage and Selection Operator (LASSO). With the resulting regression models, mineral chemistry of an outcrop in the vicinity of the drill-holes is mapped by a scene of Sentinel-2. The work shows the great potential of free satellite imagery in mapping chemical characteristics of minerals and rocks. It opens up great opportunities for monitoring outcrops and for achieving more efficient mineral exploration.MINeoDUST-RawMatCo

Sixth International Conference on Remote Sensing and Geoinformation of Environment 26-29 March, 2018 - Cyprus

peer reviewedWith the free Sentinel-2 (S2) data of the Copernicus programme, new opportunities arise for the mining community that can ease its environmental and social challenges through improved monitoring. At the moment, most users worldwide need to process S2 data to achieve surface reflectance. There are recent powerful open-source developments in atmospheric correction algorithms of S2 data such as iCOR and Sen2Cor along with MAJA that publicly shares its executable files. Open pit mining in tropical sites are not the typical conditions that semi-empirical models are designed or validated for. This work aims at assessing the discrepancy in the results of the three approaches for an area rich with laterite mining activities in central New Caledonia. Cloud retrieval is compared along with aerosol optical thickness and water vapor content estimation. Finally, consistency in surface reflectance is investigated per season, and correlations among the output of the approaches are quantified. The authors recommend to the developers of the various methods to include mining sites for validation because their highly appreciated work is important to the end-users of the raw materials community.RawMatCop - minEOdus