scholarly journals Decision Support Systems in Agriculture: Administration of Meteorological Data, Use of Geographic Information Systems(GIS) and Validation Methods in Crop Protection Warning Service

Author(s):  
Racca Paolo ◽  
Kleinhenz Benno ◽  
Zeuner Thorsten ◽  
Keil Barbara ◽  
Tschope Beate ◽  
...  
2012 ◽  
Vol 1 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Richard E. Klosterman

This paper reflects on where e-planning has been and speculates on its future. It begins by briefly reviewing forty years of efforts to use advanced information and communication technologies in planning research and practice. It then considers current efforts to develop planning and decision support systems (PSS/DSS) that adopt current geographic information systems technology to meet the unique needs of planning. It concludes with the hope that the journal will take the first word of its title seriously and share the wealth of exciting e-planning research that is being conducted in all corners of the increasingly interconnected world.


2019 ◽  
Vol 9 (2) ◽  
pp. 177
Author(s):  
Dony Martinus Sihotang ◽  
Karen N.V Tarus ◽  
Tiwuk Widiastuti

The problem of waste has not been handled well, especially in cities, including the city of Kupang. Placing the right location of the trash can be one of solutions to the waste problem. The purpose of this study is to combine decision support systems and geographic information systems to determine the location of TPS locations. There are two stages of analysis, the Brown Gibson method to determine which alternative is best for construction temporary landfill and the second analysis using the GIS approach to determine suitable point. The alternative is Neigborhoods (RT) in the Nefonaek, Kupang. The results showed that in the RT22, RT17, and RT18 which is outside the buffer area were selected as the best candidates for the new location of TPS. The system is tested in two ways, testing the blackbox using questionnaire on two respondents, and the accuracy that compares the results of the system and the results of expert. From the results of the blackbox testing, the percentage values for each GUI, Function, and information obtained were 94%, 92.5%, and 97.5%. And from Accuracy testing, obtained the value of accuracy on the first staff is 86.67% and for the second staff the accuracy value is 80%. From the two staffs obtained an average accuracy of 83.34%.


1994 ◽  
Vol 23 (4) ◽  
pp. 281-285 ◽  
Author(s):  
Jonathan D. Knight ◽  
John D. Mumford

All farmers and growers have at some time faced the decision of whether to control a pest in their crop. In order to make the correct decision the farmer needs access to, and an understanding of, sufficient information relevant to such pest problems. Decision support systems are able to help farmers make these difficult decisions by providing information in an easily understandable and quickly accessed form. The increasing use of computers by farmers for record-keeping and business management is putting the hardware necessary for the implementation of these systems onto more and more farms. The scarcity of expert advice, increasingly complex decisions and reduced economic margins all increase the importance of making the right pest management decision at the right time. It is against this background that decision support systems have an important role to play in the fight against losses caused by pests and diseases.


2016 ◽  
Vol 12 (1) ◽  
pp. 201
Author(s):  
Bilal Mohammed Salem Al-Momani

Decision support systems (DSS) are interactive computer-based systems that provide information, modeling, and manipulation of data. DSS are clearly knowledge-based information systems to capture, Processing and analysis of information affecting or aims to influence the decision making process, performed by people in scope professional job appointed by a user. Hence, this study describes briefly the key concepts of decision support systems such as perceived factors with a focus on quality  of information systems and quality of information variables, behavioral intention of using DSS, and actual DSS use by adopting and extending the technology acceptance model (TAM) of Davis (1989); and Davis, Bagozzi and Warshaw (1989).There are two main goals, which stimulate the study. The first goal is to combine Perceived DSS factors and behavioral intention to use DSS from both the social perspective and a technology perspective with regard to actual DSS usage, and an experimental test of relations provide strategic locations to organizations and providing indicators that should help them manage their DSS effectiveness. Managers face the dilemma in choosing and focusing on most important factors which contributing to the positive behavioral intention of use DSS by the decision makers, which, in turn, could contribute positively in the actual DSS usage by them and other users to effectively solve organizational problems. Hence, this study presents a model which should provide the useful tool for top management in the higher education institutions- in particular-to understand the factors that determine using behaviors for designing proactive interventions and to motivate the acceptance of TAM in order to use the DSS in a way that contributes to the higher education decision-making plan and IT policy.To accomplish or attain the above mentioned objectives, the researcher developed a research instrument (questionnaire) and distributed it amongst the higher education institutions in Jordan to collect data in order to empirically study hypothesis testing (related to the objectives of study). 341 questionnaires were returned from the study respondents. Data were analyzed by utilizing both SPSS (conducted descriptive analysis) and AMOS (conducting structural equation modelling).Findings of the study indicate that some hypotheses were supported while the others were not. Contributions of the study were presented. In addition, the researcher presented some recommendations. Finally, this study has identified opportunities for further study which has progressed greatly advanced understanding constantly of DSS usage, that can help formulate powerful strategies Involving differentiation between DSS perceived factors.


Sign in / Sign up

Export Citation Format

Share Document