Pengelolaan Data Terintegrasi Berdasarkan Instrumen Akreditasi Perguruan Tinggi 3.0 Menggunakan Zachman Framework

2020 ◽  
Vol 4 (6) ◽  
Author(s):  
Ardhin Primadewi ◽  
Mukhtar Hanafi
Keyword(s):  
Higher Education ◽  
Self Evaluation ◽  
The Core ◽  
Depth Analysis ◽  
Performance Report ◽  
Total Data ◽  
Zachman Framework ◽  
The Government ◽  
Data Gap ◽  
Education Performance

Higher education in Indonesia is regulated by the government with the Higher Education Accreditation (APT). In APT 3.0, Higher Education is required to be able to present performance data in the form of a Higher Education Performance Report (LKPT) as a reference in making a Self-Evaluation Report (LED). However, it is necessary to have an in-depth analysis to determine the gaps in the data required by Higher Education according to the APT 3.0 standard. The process of integrating the samples refer to the Zachman Framework (ZF). The results of this simplification that the data is available in support of APT 3.0 approximately 79% of the total data both inside and outside the core business of Higher Education and is well managed in an integrated database. The remaining 21% of the data that are not available is spread across several information systems, especially SIMMawa, SIMHumas and Cooperation, and SIMAKU. This shows that the change in accreditation standards that have been in effect since April 2019 has created a significant data gap for Higher Education. This research also produced an alternative model of integrated data management that can be used as input for Information System developers in the Higher Education scope.

scholarly journals An Autonomous Platform for Near Real-Time Surveillance of Harmful Algae and Their Toxins in Dynamic Coastal Shelf Environments

2021 ◽  
Vol 9 (3) ◽  
pp. 336
Author(s):  
Stephanie K. Moore ◽  
John B. Mickett ◽  
Gregory J. Doucette ◽  
Nicolaus G. Adams ◽  
Christina M. Mikulski ◽  
...  
Keyword(s):  
Real Time ◽  
Domoic Acid ◽  
Harmful Algae ◽  
Coastal Trapped Waves ◽  
Resource Managers ◽  
Bloom Formation ◽  
High Concentrations ◽  
Data Gap ◽  
Autonomous Technology

Efforts to identify in situ the mechanisms underpinning the response of harmful algae to climate change demand frequent observations in dynamic and often difficult to access marine and freshwater environments. Increasingly, resource managers and researchers are looking to fill this data gap using unmanned systems. In this study we integrated the Environmental Sample Processor (ESP) into an autonomous platform to provide near real-time surveillance of harmful algae and the toxin domoic acid on the Washington State continental shelf over a three-year period (2016–2018). The ESP mooring design accommodated the necessary subsystems to sustain ESP operations, supporting deployment durations of up to 7.5 weeks. The combination of ESP observations and a suite of contextual measurements from the ESP mooring and a nearby surface buoy permitted an investigation into toxic Pseudo-nitzschia spp. bloom dynamics. Preliminary findings suggest a connection between bloom formation and nutrient availability that is modulated by wind-forced coastal-trapped waves. In addition, high concentrations of Pseudo-nitzschia spp. and elevated levels of domoic acid observed at the ESP mooring location were not necessarily associated with the advection of water from known bloom initiation sites. Such insights, made possible by this autonomous technology, enable the formulation of testable hypotheses on climate-driven changes in HAB dynamics that can be investigated during future deployments.

A Modified CGM Algorithm Enhances Data Availability While Retaining iCGM Performance

2021 ◽  
pp. 193229682110075
Author(s):  
Rebecca A. Harvey Towers ◽  
Xiaohe Zhang ◽  
Rasoul Yousefi ◽  
Ghazaleh Esmaili ◽  
Liang Wang ◽  
...  
Keyword(s):  
Data Integration ◽  
Patient Experience ◽  
Real World ◽  
Data Availability ◽  
Post Processing ◽  
Sensor Error ◽  
The Mean ◽  
The Difference ◽  
Data Gap ◽  
Improve Patient

The algorithm for the Dexcom G6 CGM System was enhanced to retain accuracy while reducing the frequency and duration of sensor error. The new algorithm was evaluated by post-processing raw signals collected from G6 pivotal trials (NCT02880267) and by assessing the difference in data availability after a limited, real-world launch. Accuracy was comparable with the new algorithm—the overall %20/20 was 91.7% before and 91.8% after the algorithm modification; MARD was unchanged. The mean data gap due to sensor error nearly halved and total time spent in sensor error decreased by 59%. A limited field launch showed similar results, with a 43% decrease in total time spent in sensor error. Increased data availability may improve patient experience and CGM data integration into insulin delivery systems.

scholarly journals Heed the data gap: Guidelines for using incomplete datasets in annual stream temperature analyses

2021 ◽  
Vol 122 ◽  
pp. 107229
Author(s):  
Zachary C. Johnson ◽  
Brittany G. Johnson ◽  
Martin A. Briggs ◽  
Craig D. Snyder ◽  
Nathaniel P. Hitt ◽  
...  
Keyword(s):  
Stream Temperature ◽  
Data Gap ◽  
Incomplete Datasets

BIOINDICATORS OF SEA-LEVEL FLUCTUATIONS IN SOUTHEASTERN BRAZIL: NEW DATA AND METHODOLOGICAL REVIEW

Radiocarbon ◽  
2021 ◽  
pp. 1-15
Author(s):  
Julia Caon Araujo ◽  
Kita Chaves Damasio Macario ◽  
Vinícius Nunes Moreira ◽  
Anderson dos Santos Passos ◽  
Perla Baptista de Jesus ◽  
...  
Keyword(s):  
Sea Level ◽  
Late Holocene ◽  
Data Interpretation ◽  
Progressive Increase ◽  
Southeastern Brazil ◽  
Recrystallization Process ◽  
Sea Level Changes ◽  
Sea Level Fluctuations ◽  
Data Gap ◽  
Current Zero

ABSTRACT The vermetidae fossils of Petaloconchus varians, formed by calcium carbonate, associated with their radiocarbon ages, are the most accurate indicators of paleo sea level due to their restricted occupation in the intertidal zone in the rocky shore. However, the recrystallization of minerals can affect these age calculations and, consequently, the interpretation of the data. The aim of this study is to present new indicators of paleo sea-level changes in Southeast Brazil for the last 6000 years contributing to fill the data gap for the late Holocene. The influence of the recrystallization process was successfully resolved using the CarDS protocol, enabling the separation of the original aragonite fraction by density, prior to radiocarbon dating. This avoids the rejuvenation of ages and ensures greater efficiency for data interpretation. Paleo sea-level indicators were able to show a progressive increase in sea level up to the transgressive maximum of 4.15 m in 3700 BP years, followed by a regression to the current zero. This regression seems to have in addition, here we reinforce the reliability of the use of fossil vermetids as indicators of sea-level fluctuations.

scholarly journals The data gap

Nature ◽  
2006 ◽  
Vol 444 (7115) ◽  
pp. 26-27 ◽  
Author(s):  
Declan Butler
Keyword(s):  
Data Gap

Conversion from Paper to Electronic Documentation: A Data Gap Analysis Process

2011 ◽  
Vol 26 (3) ◽  
pp. 195 ◽  
Author(s):  
Nancy L. Rueckert ◽  
Dina A. Krenzischek ◽  
Stephanie Poe
Keyword(s):  
Gap Analysis ◽  
Electronic Documentation ◽  
Analysis Process ◽  
Data Gap ◽  
Paper To Electronic

Integrating LIDAR and forest inventories to fill the trees outside forests data gap

2015 ◽  
Vol 187 (10) ◽  
Author(s):  
Kristofer D. Johnson ◽  
Richard Birdsey ◽  
Jason Cole ◽  
Anu Swatantran ◽  
Jarlath O’Neil-Dunne ◽  
...  
Keyword(s):  
Trees Outside Forests ◽  
Forest Inventories ◽  
Data Gap

Preliminary monthly gravity field models from kinematic orbits of SWARM Satellites

2021 ◽  
Author(s):  
Xingfu Zhang ◽  
Qiujie Chen ◽  
Yunzhong Shen
Keyword(s):  
Gravity Field ◽  
Large Scale ◽  
Earth System ◽  
The Earth ◽  
Swarm Satellites ◽  
Variable Gravity ◽  
Data Gap ◽  
One Year ◽  
Gravity Recovery ◽  
Gravity Field Models

<p>      Although the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE FO) satellite missions play an important role in monitoring global mass changes within the Earth system, there is a data gap of about one year spanning July 2017 to May 2018, which leads to discontinuous gravity observations for monitoring global mass changes. As an alternative mission, the SWARM satellites can provide gravity observations to close this data gap. In this paper, we are dedicated to developing alternative monthly time-variable gravity field solutions from SWARM data. Using kinematic orbits of SWARM from ITSG for the period January 2015 to September 2020, we have generated a preliminary time series of monthly gravity field models named Tongji-Swarm2019 up to degree and order 60. The comparisons between Tongji-Swarm2019 and GRACE/GRACE-FO monthly solutions show that Tongji-Swarm2019 solutions agree with GRACE/GRACE-FO models in terms of large-scale mass change signals over amazon, Greenland and other regions. We can conclude that Tongji-Swarm2019 monthly gravity field models are able to close the gap between GRACE and GRACE FO.</p>

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