An executive decision support system for longitudinal statistical analysis of crime and law enforcement performance crime analysis system pacific region (CASPR)

2010 ◽  
Author(s):  
Amir H. Ghaseminejad ◽  
Paul Brantingham
Keyword(s):  
Decision Support ◽  
Statistical Analysis ◽  
Law Enforcement ◽  
Decision Support System ◽  
Support System ◽  
Crime Analysis ◽  
Pacific Region ◽  
Analysis System

The Warning Decision Support System–Integrated Information

2007 ◽  
Vol 22 (3) ◽  
pp. 596-612 ◽  
Author(s):  
Valliappa Lakshmanan ◽  
Travis Smith ◽  
Gregory Stumpf ◽  
Kurt Hondl
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Severe Weather ◽  
Weather Data ◽  
Spatial Coverage ◽  
Analysis System ◽  
Automated Algorithms ◽  
The Individual ◽  
Integrated Information

Abstract The Warning Decision Support System–Integrated Information (WDSS-II) is the second generation of a system of tools for the analysis, diagnosis, and visualization of remotely sensed weather data. WDSS-II provides a number of automated algorithms that operate on data from multiple radars to provide information with a greater temporal resolution and better spatial coverage than their currently operational counterparts. The individual automated algorithms that have been developed using the WDSS-II infrastructure together yield a forecasting and analysis system providing real-time products useful in severe weather nowcasting. The purposes of the individual algorithms and their relationships to each other are described, as is the method of dissemination of the created products.

scholarly journals Decision Support System For Employee Bonus Determination With Web-Based Simple Additive Weighting (SAW) Method In PT. Mayatama Solusindo

2020 ◽  
Vol 2 (1) ◽  
pp. 7-13
Author(s):  
Yuda Irawan
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Program Implementation ◽  
System Development ◽  
Employee Performance ◽  
Weighting Method ◽  
Simple Additive Weighting ◽  
Analysis System

Decision Support System is a computerized system designed to increase effectiveness in decision making to solve semi-structured and unstructured problems so that the decision-making process can be of higher quality. One method of solving MADM problems is by using the Simple Additive Weighting method. The SAW method is to find the weighted sum of the performance ratings for each alternative of all attributes. This study aims to design and create a system to determine which employees are entitled to receive bonuses, for that we need a decision support for giving employee bonuses decisions. In this study using the Simple Additive Weighting method. The system development model used is a waterfall. Waterfall has several stages, namely needs analysis, system design, writing program code, program testing, program implementation and maintenance. The results showed the benefits of the SAW method as a decision support system for determining employee bonuses based on the employee performance of PT. Mayatama Solusindo can assist administrators in determining employee bonuses quickly and effectively. So the bonus that employees get using the SAW method is the basic salary times the percentage of the ranking value.

scholarly journals AUTOMATED DECISION-MAKING SUPPORT SYSTEM FOR QUALIFICATION OF CRIMINAL OFFENSES AS AN ELEMENT OF HUMAN RIGHTS HEALTH PROTECTION SYSTEMS

2021 ◽  
Vol 74 (11) ◽  
pp. 2884-2890
Author(s):  
Valery F. Obolentsev ◽  
Oleh M. Hutsa ◽  
Dmytro B. Yelchaninov
Keyword(s):  
Decision Support ◽  
Law Enforcement ◽  
Decision Support System ◽  
Human Health ◽  
Support System ◽  
Legal System ◽  
Information Model ◽  
Criminal Offense ◽  
Criminal Offenses ◽  
Software Product

The aim: 1) To develop an informative model of the process of automated qualification of criminal offenses against human health for countries with a continental legal system; 2) on the basis of information model to create a decision support system in the form of a software product in terms of qualification of a criminal offense against human health. Materials and methods: The information model of the process of automated qualification of a criminal offense against human health was developed using the BPMN method on the basis of European countries’ legislation with a continental legal system. According to the information model, a decision support system was developed in the form of a software product. Results: 1. An information model of the process of automated qualification of criminal offenses against human health for countries with a continental legal system has been developed. 2. A system of decision support in the form of a software product as an element of law enforcement in terms of qualification of a criminal offense against human health. Conclusions: The proposed decision support system for automated qualification is a means of preventing unreasonable qualification of committed offenses as it minimizes the errors of this process. As a result, it will increase the preventive effect and the quality of law enforcement work to prevent crimes against human health.

scholarly journals STATISTICAL ANALYSIS OF DEMAND FOR TELECOMMUNICATIONS SERVICES FOR FORECASTING PURPOSES – STUDY OF THE IMPACT OF FACTORS NOT ARISING FROM THE CALENDAR

2019 ◽  
Vol 18 (1) ◽  
pp. 21-31
Author(s):  
Paweł Kaczmarczyk
Keyword(s):  
Decision Support ◽  
Statistical Analysis ◽  
Decision Support System ◽  
Support System ◽  
Statistical Analyses ◽  
Prediction System ◽  
Research Results ◽  
Operational Management ◽  
Telecommunications Services ◽  
The Impact

The aim of this study is to identify the impact of factors (not arising from the calendar) on the demand for connection services offered by a telecommunications operator. The theoretical part of the research presents the importance of the Prediction System (PS) as a kind of Decision Support System in the operational management of the telecommunications operator. Theoretical aspects of PS structure have been included. Special attention has been paid to the statistical analysis module (as the PS subsystem), which was implemented in the adopted (researched) scope in the empirical part of the research. The empirical part presents the results of statistical analyses of demand for telecommunications services in the scope enabling identification of the impact of factors not arising from the calendar (i.e. the impact of category of connection and type of subscribers) on the level and distribution of such demand. The presented research results provide premises for the construction of forecasting tools, carrying out the forecasting procedure and monitoring the forecasts, i.e. they provide the necessary premises for the implementation of subsequent components of the PS.

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