A web-based decision support system for integrated management of cereal pests

EPPO Bulletin ◽  
2003 ◽  
Vol 33 (3) ◽  
pp. 467-471 ◽  
Author(s):  
L. Hagelskjaer ◽  
L. Nistrup Jørgensen
2016 ◽  
Vol 2 (1) ◽  
pp. 40
Author(s):  
Fatikhatus Sholikhah ◽  
Diema Hernyka Satyareni ◽  
Chandra Sukma Anugerah

Abstrak Persaingan merupakan hal yang biasa terjadi terutama dalam dunia bisnis, tidak terkecuali yang telah dialami oleh Bravo Supermarket Jombang. Bravo bukanlah satu-satunya supermarket di kota Jombang, sehingga Bravo harus bersaing dengan para kompetitornya agar Bravo bisa bersaing dan tetap produktif. Salah satu cara yang dapat digunakan dalam meningkatkan penjualan dan loyalitas pelanggan adalah dengan memberikan reward kepada para pelanggan terbaik. Oleh karena itu perlu dibuatlah sebuah perancangan sistem pendukung keputusan dalam pemilihan pelanggan terbaik pada Bravo. Dalam perancangan sistem yang dibuat nantinya berbasis web dengan metode SAW(Simple Additive Weighting)sebagai proses perhitungan pemilihan pelanggan terbaik. Hasil dari perancangan sistem pemilihan pelanggan terbaik pada Bravo Supermarket Jombang diharapkan dapat membantu pihak manajemen Bravo dalam pemilihan pelanggan terbaik yang akan menerima reward dan akhirnya akan mampu meningkatkan loyalitas pelanggan dan profit Bravo. Kata kunci: Bravo, sistem pendukung keputusan, pelanggan, SAW. Abstract Competition is a common thing, especially in the business world, is no exception has been experienced by Bravo Supermarket Jombang. Bravo is not the only supermarket in the town of Jombang, so that Bravo had to compete with its competitors in order Bravo to compete and remain productive. One way that can be used to increase sales and customer loyalty is to give rewards to the best customers. Therefore, it needs to be made to a design decision support system in the selection of the best customers on Bravo. In designing the system made later on a web-based method of SAW (Simple Additive weighting) as the process of calculating the best customer selection. The results of the election system design best customers at Bravo Supermarket Jombang expected to assist management in selecting the best customer Bravo who will receive rewards and will eventually be able to increase customer loyalty and profit Bravo. Key word: Bravo, decision support system, customers, SAW.


2019 ◽  
Vol 2 (1) ◽  
pp. 40-46
Author(s):  
Rikardo Chandra ◽  
Izmy alwiah Musdar ◽  
Junaedy .

This study aims to design and build web-based decision support system applications used to recommend the best tourist attractions in South Sulawesi to tourists. The expected benefit of this research is to help the user get the best tourist recommendation information available in South Sulawesi based on the conditions in input factors. The theorem or method used in this study, namely the theorem Naïve Bayes. The design of the system isimplemented using PHP programming language and MYSQL database. Based on the results of the research, the authors have successfully built the application of decision support system to determine the recommendation of tourist attractions in South Sulawesi with 65% accuracy based on 20 tests conducted.


Weed Science ◽  
2015 ◽  
Vol 63 (3) ◽  
pp. 676-689 ◽  
Author(s):  
Myrtille Lacoste ◽  
Stephen Powles

RIM, or “Ryegrass Integrated Management,” is a model-based software allowing users to conveniently test and compare the long-term performance and profitability of numerous ryegrass control options used in Australian cropping systems. As a user-friendly decision support system that can be used by farmers, advisers, and industry professionals, RIM can aid the delivery of key recommendations among the agricultural community for broadacre cropping systems threatened by herbicide resistance. This paper provides advanced users and future developers with the keys to modify the latest version of RIM in order to facilitate future updates, modifications, and adaptations to other situations. The various components of RIM are mapped and explained, and the key principles underlying the construction of the model are explained. The implementation of RIM into a Microsoft Excel® software format is also documented, with details on how user inputs are coded and parameterized. An overview of the biological, agronomic, and economic components of the model is provided, with emphasis on the ryegrass biological characteristics most critical for its effective management. The extreme variability of these parameters and the subsequent limits of RIM are discussed. The necessary compromises were achieved by emphasizing the primary end-use of the program as a decision support system for farmers and advisors.


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