• Journal of Intelligence and Information Systems
• /
• v.11 no.1
• /
• pp.35-51
• /
• 2005

The wide spread of Internet and rapid development of e-commerce-related technology have brought sweeping changes on the traditional commercial transactions. Accordingly, many efforts to transform these transactions electronically under e-commerce environment have been carried out. As most transactions are usually made through negotiations, the function of automated negotiation is also required in the e-commerce environment. This paper aims to develop the method to generate and evaluate the multi-attribute negotiation proposals for automated negotiation systems. To this end the related articles are reviewed and the method dealing with e-negotiation strategy is suggested. In this method, the seller generates his or her own negotiation proposal and then evaluates the buyer's proposal based on SAW (Simple Additive Weighting Method), one of the MADM (Multi Attribute Decision Making) methods. To verify the suggested method, a case study is conducted in the order-based manufacturing environment.

• Journal of Korea Society of Industrial Information Systems
• /
• v.20 no.4
• /
• pp.1-9
• /
• 2015

This paper proposes CAC method that is more efficient for RRM using game theory combined with Multiple Attribute Decision Making(MADM). Because users request services with different Quality of Service(QoS), the network preference values to alternative networks for each service are calculated by MADM methods such as Grey Relational Analysis(GRA), Simple Additive Weighting(SAW) and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS). According to a utility function representing preference value, non-cooperative game is played, and then network provider select the requested service that provide maximum payoff. The appropriate service is selected through Nash Equilibrium that is the solution of game and the game is played repeated. We analyze two overlaid networks among four Wireless LAN(WLAN) systems with different properties. Simulation results show that proposed MADM techniques have same outcomes for every game round.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.3
• /
• pp.307-318
• /
• 2021

The objective of this study is to analyze the performance of Islamic banks with the Maqashid Shariah approach. The analysis technique used is the Simple Additive Weighting Method (SAW) to solve multi-attribute decision problems. The sampling technique used was purposive sampling while the data came from the annual report of each bank. The results showed that the BTPN Shariah (BTPNS) and Bank Muamalat Indonesia (BMI) are ranked first and second respectively on the Maqashid Shariah Index (MSI) with values of 0.265429 and 0.237110 respectively. Panin Dubai Shariah Bank (PDSB) ranked third with an MSI value of 0.180733, followed by BCA Shariah which ranked fourth with an MSI value of 0.151299. BRI Shariah ranked fifth with an MSI value of 0.128606, followed by BNI Shariah which ranked sixth with an MSI value of 0.124661. Bank Mega Shariah ranked last with an MSI value of 0.087068. Furthermore, there is a relationship (correlation) between ROE, ROA, and OEOI and MSI since each data has a value of 0.000, 0.000, 0.050, and 0.001 respectively, which is smaller than the significance value of 0.05. On the other hand, NPF, TPF, and Asset Growth Rates do not correlate with the MSI since each data has a value of 0.051, 0.252, and 0.215 respectively which is greater than the significance value of 0.05.