scholarly journals Learning Vector Quantization Implementation to Predict the Provision of Assistance for Indonesian Telematics Services SMES

2018 ◽  
Vol 7 (3.20) ◽  
pp. 381
Author(s):  
Eneng Tita Tosida ◽  
Fajar Delli Wihartiko ◽  
Indra Lumesa

Implementation of Learning Vector Quantization (LVQ) Algorithm for classification of Indonesia telematics service is designed and created as a classification system to support the decision of grant aid for Small Medium Enterprises (SMEs). Based on the test results, the LVQ algorithm has the best accuracy (93.11%) when compared with ID3 algorithm (64%) and C45 (62%) for telematics data of National Census of Economic (Susenas 2006). The data is still valid and relevant for use in this research because in Indonesia census data is done every 10 years and there is no update of data until now. LVQ implementation results are applied to a web-based decision support system to predict the provision of assistance for Indonesian telematics services SMEs. Unlike the C45 and ID3 algorithms, the LVQ algorithm generates the weight of a neural network where it difficult to know which attributes are most influential for decision making. But in this study LVQ able to show good performance through the analysis of the relevance of existing conditions by comparing it with the weight value produced by the model that are implemented in a web-based decision support system 

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.


Author(s):  
Sunil Pratap Singh ◽  
Jitendra Sharma ◽  
Preetvanti Singh

In the last decade the use of Information and Communication Technologies (ICT) have boomed in many sectors, such as business, education, commerce and have profound implications for the tourism industry. They are being used extensively in a great variety of functions and count innumerable applications. Among these, Decision Support System (DSS) plays a fundamental role for their capacity to give tourist managing their tours and to base all the decisions concerning to queries on the climate, road conditions, cultural aspects, lodging, health facilities, banking, etc. of the location to be visited on sound and rational bases. In the present paper, a Web-Based Tourist Decision Support System (WTDSS) for Agra City has been developed that allows the traveling community to find their route in city and ask for information about sights, accommodations and other places of interest which are near by to him to improve the convenience, safety and efficiency of travel.


Sign in / Sign up

Export Citation Format

Share Document