The Broader Public Sector (BPS) plays an important role in helping Ontario meet its conservation targets and reduce greenhouse gas emissions. Under O. Reg. 25/23 (Broader Public Sector: Energy Reporting and Conservation and Demand Management Plans), made under the Electricity Act, 1998, BPS organizations are required to: 1. Report annually to the Ministry of Energy and Electrification, on their energy use and greenhouse gas (GHG) emissions and publish the reports on their websites (as of July 1, 2013); 2. Develop a five-year conservation and demand management plan and publish the plan on their websites. Plans must be updated every five years (as of July 1, 2014). This data includes the annual amount of energy used and GHG emitted by BPS organizations. BPS organizations that are required to report include municipalities, municipal service boards, school boards, universities, colleges and hospitals. Several BPS organizations also voluntarily reported on facilities that are not required by regulation. Posted data files contain the following information: * raw energy consumption and GHG emission data * data that has been normalized to account for weather conditions and GHG emissions * the names of those BPS organizations that did not report their 2013-2017 energy* consumption data. Missing or incorrect data is the sole responsibility of the BPS organization. The ministry has attempted to remove duplicate data from this data set to improve data integrity. The Ministry of Energy and Electrification developed O. Reg. 25/23 to help BPS organisations better understand how and where they use energy and demonstrate government leadership by developing conservation plans to guide energy savings. *The Ministry of Energy and Electrification is aware that COVID-19 may have restricted some BPS organizations’ ability to submit their annual energy reports using the 2018 and 2019 data.

In 2005, BPS do the Social Economic Colletion (PSE05), which aims to get the data in the form of micro poverty households directory that deserves a direct cash assistance (BLT) in 2005-2006. Given the data turns PSE05 considered better results compared to a database available in local government. Nevertheless, it is recognized that the data from PSE05 not perfect. The study of 56 universities found the data from PSE05 still contains 8 percent and 22.36 percent error inclusion exclusion error (Coordinating Minister for People's Welfare 2005). In addition to BLT program, data PSE05 also used in targeting households on several national programs, such as the Health Insurance of the Poor (HIP) and cheap rice program for the poor (Raskin). These programs succeeded in reducing poverty levels, poor households proved as much 17.8 percent in 2006 down to 15.4 percent in 2008. But be aware that the collection PSE05 an activity that is great for BPS, BPS so many other activities are pending at this time. After PSE05 activities, in 2007 the BPS also conducted the data collection for the household conditional direct cash assistance program (Family Hope Program / PKH) in 2007. The collection of data to support this program called Basic Health Care Survey and Education 2007 (SPDKP07). Results from SPDKP07 considered much better than the data from PSE05 because only less inclusion and exclusion errors of his. This is because SPDKP07 implemented only in 953 districts / cities were selected and a much larger budget.

Indonesia BPS Projection: Population: 0-4 Years data was reported at 21,959.700 Person th in 2045. This records a decrease from the previous number of 21,964.700 Person th for 2044. Indonesia BPS Projection: Population: 0-4 Years data is updated yearly, averaging 21,987.100 Person th from Dec 2000 (Median) to 2045, with 46 observations. The data reached an all-time high of 24,086.800 Person th in 2014 and a record low of 19,578.414 Person th in 2005. Indonesia BPS Projection: Population: 0-4 Years data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Socio and Demographic – Table ID.GAA001: Population Projection: Central Bureau of Statistics.

Dataset

This dataset was created by Lintang Wisesa

Released under Database: Open Database, Contents: Database Contents

Contents

Abstract

Sensus Infrastruktur Desa ini merupakan sensus yang diintegrasikan dengan pendataan Podes 2011.

Sensus Infrastruktur Desa dilaksanakan untuk mengumpulkan data kualitas infrastruktur kesehatan dan pendidikan negeri yang ada di desa. Fasilitas kesehatan yang didata adalah: Puskesmas, Pustu, Poskesdes, Polindes, dan Posyandu. Fasilitas pendidikan yang didata adalah semua sekolah negeri SD/sederajat, SMP/sederajat, dan SMU/sederajat.

Pendataan Podes telah dilaksanakan sejak tahun 1980 bersamaan dengan penyelenggaraan Sensus Penduduk 1980. Pengumpulan data Podes dilakukan sebanyak 3 (tiga) kali dalam kurun waktu 10 tahun, sebagai bagian dari rangkaian kegiatan Sensus Penduduk, Sensus Pertanian dan Sensus Ekonomi. Namun demikian sejak tahun 2008, pendataan Podes dilaksanakan secara independen dari rangkaian kegiatan sensus. Kuesioner yang digunakan sebanyak 3 jenis yaitu kuesioner Desa, kuesioner Kecamatan, dan kuesioner Kabupaten/Kota. Pada tahun 2011 ini, Podes tidak terkait dengan manajemen pelaksanaan Sensus Pertanian 2013

Tujuan pelaksanaan Pendataan Podes 2011 adalah: 1. Menyediakan data tentang keberadaan dan perkembangan potensi yang dimiliki Desa/Kelurahan yang meliputi: sosial, ekonomi, sarana, dan prasarana wilayah. 2. Menyediakan data untuk berbadai keperluan yang berkaitan dengan perencanaan wilayah di tingkat nasional dan tingkat daerah. 3. Melengkapi penyusunan kerangka sampling (sampling frame) untuk kegiatan statistik lain lebih lanjut. 4. Menyediakan data bagi keperluan penentuan klasifikasi/tipologi desa (urban dan rural), desa tertinggal dan tidak tertinggal, dan sebagainya. 5. Menyediakan data pokok bagi penyusunan statistik wilayah kecil (Small Area Statistics).

Geographic coverage

Seluruh wilayah administrasi pemerintahan setingkat desa (desa, kelurahan, nagari/jorong) di seluruh Indonesia, termasuk Unit Permukiman Transmigrasi (UPT) dan Satuan Permukiman Transmigrasi (SPT) yang masih dibina oleh kementerian terkait.

Analysis unit

Unit analisis: desa

Sampling procedure

Pendataan Podes 2011 dilakukan di seluruh wilayah administrasi setingkat desa/kelurahan/nagari di seluruh Indonesia. Pengumpulan data Podes 2011 dilakukan secara sensus (complete enumeration). Pencacahan infrastruktur desa dilaksanakan dengan mengunjungi seluruh fasilitas pelayanan kesehatan dasar (Puskesmas, Pustu, Poskesdes, Polindes, Posyandu) dan fasilitas sekolah negeri (SD, SMP, dan SMU sederajat). Khusus untuk Posyandu yang dikunjungi adalah posyandu yang telah mempunyai bangunan tersendiri (tidak menumpang pada rumah warga/kades).

Mode of data collection

Face-to-face

Research instrument

1. Podes11-Listing Faskesdik: Pendaftaran fasilitas pendidikan dan kesehatan.
2. Podes11-Sekolah: Pendataan fasilitas sekolah.
3. Podes11-Puskesmas/Pustu: Pendataan fasilitas Puskesmas/Pustu.
4. Podes11-Poskesdes/Polindes: Pendataan fasiitas Poskesdes/Polindes.
5. Podes 11-Posyandu: Pendataan fasilitas Posyandu.

Cleaning operations

1. Pengolahan dokumen PODES11-DESA dilakukan oleh petugas entri dengan menggunakan program yang sudah disiapkan oleh BPS RI. Petugas entri adalah KSK atau staf BPS Kabupaten/Kota yang telah mengikuti pelatihan pengolahan data. Sebelum dilakukan entri data, petugas melakukan kegiatan editing coding, pemeriksaan kewajaran isian dan kebenara identitas. Entri data dilakukan segera setelah dokumen terisi secara lengkap dan benar. File hasil entri data dan dokumen-dokumen PODES11-DESA dikirim ke BPS Kabupaten/Kota setiap minggu.

2. Kompilasi dan validasi data hasil entri PODES11-DESA dilakukan di BPS Kabupaten/Kota. a. Kompilasi dilakukan setiap minggu, dan laporan kompilasi semua jumlah desa yang datanya sudah diterima di BPS Kabupaten/Kota dikirim melalui SMS. b. Dalam proses validasi data juga melakukan matching data Podes 2011 dengan data Podes sebelumnya. Laporan validasi yaitu jumlah desa yang datanya sudah selesai divalidasi dikirim melalui SMS setiap minggu. c. Bila dalam proses data clean masih terdapat error, pengawas segera melakukan perbaikan sampai diperoleh data clean.

3. Pengecekan konsistensi data desa dan kecamatan untuk variabel-variabel yang bersesuaian dilakukan di BPS Kabupaten/Kota.

4. Setelah data clean tercapai di BPS Kabupaten/Kota, selanjutkan 25 % dokumen PODES11-DESA dikirim ke BPS Provinsi untuk dilakukan re-entri oleh staf di BPS Provinsi. BPS Provinsi akan melakukan kompolasi data dari BPS Kabupaten/Kota, dan re-entri 25 % dokumen PODES11-DESA. Beberapa hal penting yang harus diperhatikan oleh BPS Provinsi adalah: a. Melakukan matching dataset dari BPS Kabupaten/Kota dengan hasil re-entri dan menganalisanya. b. Memeriksa kelengkapan dan kewajaran data antar wilayah Kabupaten/Kota.

5. Setelah data clean tercapat di tingkat BPS Provinsi, selanjutnya dataset tersebut dikirim ke BPS RI Sub. Direktorat Integrasi Pengolahan Data (Subdit IPD). Subdit IPD melakukan kompilasi, pengecekan, dan tabulasi seluruh data dari BPS Provinsi. Database Podes akan dikirim kembali ke BPS Provinsi dan Kabupaten/Kota, dan BPS Kabupaten/Kota mencetak per desa dan menyerahkannya ke kantor Kepala Desa/Lurah sebagai arsip di tingkat Desa/Kelurahan.

Indonesia BPS Projection: Population: Male data was reported at 158,755.000 Person th in 2045. This records an increase from the previous number of 158,229.500 Person th for 2044. Indonesia BPS Projection: Population: Male data is updated yearly, averaging 128,483.400 Person th from Dec 1985 (Median) to 2045, with 61 observations. The data reached an all-time high of 158,755.000 Person th in 2045 and a record low of 81,934.415 Person th in 1985. Indonesia BPS Projection: Population: Male data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GAA001: Population Projection: Central Bureau of Statistics.

This dashboard shows information about how the Basic Payment Scheme (BPS) service is currently performing.

This is a "beta" service. The dashboard shows number of digital transactions, total cost of transactions, cost per transaction and take-up of digital services. Performance Dashboards are likely to be used by many people, including:

government service managers and their teams journalists students and researchers members of the public interested in how public services are performing The service also provides the option of a download of the data. Attribution statement:

Each year, the City of Boston publishes payroll data for employees. This dataset contains employee names, job details, and earnings information including base salary, overtime, and total compensation for employees of the City.

See the "Payroll Categories" document below for an explanation of what types of earnings are included in each category.

Indonesia BPS Projection: Population: Java data was reported at 167,325.600 Person th in 2035. This records an increase from the previous number of 166,731.300 Person th for 2034. Indonesia BPS Projection: Population: Java data is updated yearly, averaging 132,192.050 Person th from Dec 1980 (Median) to 2035, with 56 observations. The data reached an all-time high of 167,325.600 Person th in 2035 and a record low of 91,609.500 Person th in 1980. Indonesia BPS Projection: Population: Java data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GAA002: Population Projection: by Province: Central Bureau of Statistics.

10 Global import shipment records of Bps with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

BuildBPS compiles vast amounts of data and allows for ongoing analyses that can be used to guide and inform decisions related to school building investments. An assessment team of architects and educational planners visited all of Boston Public Schools’ buildings, collecting and organizing information on the physical condition of each building and their educational suitability to the programs offered within. Beyond the general information about each school building, the data is organized in the following four categories: Facility Assessment– Building, Facility Assessment–Site, Educational Facility Effectiveness: Learning Environments, and Educational Facility Effectiveness: Spaces. This dataset will be updated on a yearly basis to reflect changes as renovations and upgrades occur.

Indonesia BPS Projection: Population: Sumatra data was reported at 68,500.000 Person th in 2035. This records an increase from the previous number of 68,026.600 Person th for 2034. Indonesia BPS Projection: Population: Sumatra data is updated yearly, averaging 48,401.250 Person th from Dec 1980 (Median) to 2035, with 56 observations. The data reached an all-time high of 68,500.000 Person th in 2035 and a record low of 28,120.800 Person th in 1980. Indonesia BPS Projection: Population: Sumatra data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GAA002: Population Projection: by Province: Central Bureau of Statistics.

The 2012 Beginning Postsecondary Students Longitudinal Study, 2012 Base Year (BPS:12) is part of the Beginning Postsecondary Students Longitudinal Study (BPS) program. BPS:12 is the base year of a longitudinal study that followed a cohort of students who enrolled in postsecondary education for the first time during the 2011-12 academic year, irrespective of date of high school completion. The 2012-13 National Postsecondary Student Aid Study (NPSAS:12) data provided the base-year sample for BPS:12. BPS:12 data are representative of all first-time beginning (FTB) students enrolled in postsecondary institutions in the 50 United States and the District of Columbia that were eligible to participate in the federal financial aid programs in Title IV of the Higher Education Act. The cohort includes a subset of students initially sampled for participation in NPSAS:12 and classified by their NPSAS institution as FTBs. Key statistics produced from BPS:12 are data on student persistence in, and completion of, postsecondary education programs; their transition to employment; demographic characteristics; and changes over time in their goals, marital status, income, and debt, among other measures.

LANDFIRE's (LF) Biophysical Settings (BPS) product (https://www.landfire.gov/bps.php) represents the vegetation system that may have been dominant on the landscape prior to Euro-American settlement. BPS is based on both the current biophysical environment and an approximation of the historical disturbance regime. Map units are based on NatureServe's Ecological Systems classification and represent the natural plant communities that may have been present during the reference period. Each BPS map unit is matched with a model of vegetation succession and both serve as key inputs to the LANDSUM landscape succession model (Keane et al. 2006). The actual time period for this data set is determined by historical context provided by the fire regime, vegetation system dynamics modeling, and the recent field and geospatial inputs used to create it. Weather data from the Daily Surface Weather and Climatological Summaries database [(DAYMET) https://daymet.ornl.gov/) were compiled from 1980 to 1997. LF uses BPS to depict reference conditions of vegetation systems across landscapes and should not be regarded as a representation of existing vegetation. LF Remap BPS is unchanged from LF Nationals BPS except for updates made to water, barren and snow classes (additions or removal), so that not vegetated cover types within the spatial BPS product matches LF existing vegetation and fuel products.

RNA sequencing data from spaceflown and control mouse liver samples, sourced from NASA GeneLab and augmented with generative adversarial network.

Indonesia BPS Projection: Population: Female data was reported at 160,206.000 Person th in 2045. This records an increase from the previous number of 159,581.800 Person th for 2044. Indonesia BPS Projection: Population: Female data is updated yearly, averaging 127,104.500 Person th from Dec 1985 (Median) to 2045, with 61 observations. The data reached an all-time high of 160,206.000 Person th in 2045 and a record low of 82,695.203 Person th in 1985. Indonesia BPS Projection: Population: Female data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GAA001: Population Projection: Central Bureau of Statistics.

LANDFIRE's (LF) 2023 Update Biophysical Settings (BPS) product for Alaska represents the vegetation system that may have been dominant on the landscape prior to Euro-American settlement. BPS is based on both the current biophysical environment and an approximation of the historical disturbance regime. Map units are based on NatureServe's Ecological Systems classification and represent the natural plant communities that may have been present during the reference period. Each BPS map unit is matched with a model of vegetation succession which is used to estimate reference fire frequency and severity. LANDFIRE uses BPS to depict reference conditions of vegetation systems across landscapes and should not be regarded as a representation of existing vegetation. The LF 2023 BPS product uses the revised Ecological Systems classification for AK and was created by reviewing and modifying the LF 2016 Remap Existing Vegetation Type (EVT) data and adapting it to represent BPS concepts. This includes splitting and lumping EVTs to ensure they are compatible with the recent classification changes in BPS.

Banking BPS Market Outlook

The global Banking Business Process Services (BPS) market is poised for significant expansion, with a market size of approximately $68 billion in 2023 and expected to reach a formidable $128 billion by 2032, reflecting a robust Compound Annual Growth Rate (CAGR) of 7.2%. This expansive growth is driven by the increasing digitization within the banking sector, the demand for enhanced customer experiences, and the necessity for cost-effective operational solutions. As financial institutions navigate the complexities of a rapidly evolving digital landscape, BPS emerges as a pivotal enabler, facilitating streamlined processes through automation and outsourcing, thus allowing banks to focus on their core competencies while simultaneously improving efficiency and service delivery.

One of the primary growth factors propelling the Banking BPS market is the sharply increasing demand for cost reduction and efficiency in banking operations. In an era where maintaining profitability amidst mounting operational costs and regulatory burdens is crucial, banks are turning to BPS solutions to achieve significant cost savings. These services provide banks with the flexibility to outsource non-core activities, thereby allowing them to concentrate resources on strategic growth initiatives. Additionally, by leveraging BPS, banks can achieve operational excellence through streamlined processes, improved accuracy, and reduced cycle times, resulting in enhanced customer satisfaction and retention.

The rapid technological advancements in artificial intelligence, machine learning, and robotic process automation are another significant driver for the Banking BPS market. These technologies enable the automation of mundane and repetitive tasks, significantly improving process efficiency and accuracy. The adoption of advanced data analytics in BPS solutions helps financial institutions gain deeper insights into customer behavior, enabling them to tailor their services and offer personalized banking experiences. As competition intensifies within the banking sector, the ability to leverage these technologies through BPS becomes a critical differentiator, allowing banks to stay ahead by offering innovative and customer-centric solutions.

Moreover, the increasing focus on regulatory compliance and risk management in the banking sector further fuels the adoption of BPS solutions. With regulatory landscapes becoming more stringent and complex, banks are seeking out BPS providers who can offer specialized compliance services and risk management solutions. Outsourcing these functions to experienced third-party providers not only ensures adherence to regulatory standards but also mitigates risks associated with compliance lapses. This shift towards compliance-driven BPS solutions is expected to continue growing as regulatory requirements evolve, highlighting the importance of BPS in maintaining operational integrity and reducing vulnerability to financial and reputational damages.

Regionally, North America is currently the largest market for Banking BPS, driven by the presence of major banking institutions and the rapid adoption of advanced technology solutions. However, the Asia-Pacific region is witnessing the fastest growth, with a burgeoning banking sector keen on digital transformation and process optimization. The proliferation of fintech companies and increasing mobile banking penetration in countries such as China and India are significant contributors to this growth. Europe, with its strong regulatory frameworks, also presents substantial opportunities for BPS providers, particularly in compliance and risk management solutions.

Service Type Analysis

In the realm of Banking BPS, the service type segment plays a crucial role in defining the landscape and trajectory of market growth. Core Banking BPS, a fundamental segment, focuses on streamlining and optimizing the essential operations of financial institutions. This includes services such as account management, customer data integration, and transaction processing. The demand for Core Banking BPS is driven by the need for banks to maintain seamless operations while reducing operational costs. By outsourcing these core functions, banks can achieve higher efficiency and agility, enabling them to respond swiftly to market changes and customer needs.

Mortgage and Loan BPS, another significant sub-segment, addresses the complexities involved in loan origination, processing, and servicing. The volatility in the real estate market, coupled with stringent regulatory requirements, has amplified the demand for expert handling o

This line chart displays opening price by date using the aggregation sum. The data is filtered where the stock is BPS.F. The data is about stocks per day.

Indonesia BPS Projection: Population: Mid-Year: Central Java: Brebes Regency data was reported at 1,815.086 Person th in 2020. This records an increase from the previous number of 1,809.096 Person th for 2019. Indonesia BPS Projection: Population: Mid-Year: Central Java: Brebes Regency data is updated yearly, averaging 1,788.687 Person th from Jun 2008 (Median) to 2020, with 13 observations. The data reached an all-time high of 1,815.086 Person th in 2020 and a record low of 1,732.719 Person th in 2010. Indonesia BPS Projection: Population: Mid-Year: Central Java: Brebes Regency data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Socio and Demographic – Table ID.GAB014: Population Projection: Mid-Year: Central Java: by Regency and Municipality: Central Bureau of Statistics.