Seminar Nasional Teknologi Informasi dan Multimedia 2018 UNIVERSITAS AMIKOM Yogyakarta, 10 Februari 2018 ISSN : 2302-3805 2.9-7 ACCEPTANCE ANALYSIS OF EXPERT SYSTEM IN FOREX AND COMMODITIES ONLINE TRADING A CASE STUDY OF METATRADER4 USERS Asro Nasiri 1) , Mardhiya Hayty 2) 1, 2) Fakultas Ilmu Komputer, Universitas AMIKOM Yogyakarta Jl. Ring Road Utara, Condong Catur, Depok, Sleman, Yogyakarta 55281 Email: asro@amikom.ac.id 1) , mardhiya_hayati@amikom.ac.id 2) Abstract This study measures the acceptance of foreign exchange and commodities traders/investors on the use of the expert system in the form of EA in helping their online trading process. This research model is based on the Technology Acceptance Model (TAM) popularized by Fred D. Davis. Constructs used in this study is Perceived Ease of Use, Perceived Usefulness, Attitude Toward Using, Behavioural Intention to Use, Actual System Use, External Variables (User Involvement. The primary data in this study were obtained from questionnaires. Some sample of forex traders as respondents were asked to fill out an online questionnaire. The data then processed and analysed by Structural Equation Model (SEM) method with the help of IBM SPSS AMOS 20 software. The results of this study show that Perceived Ease of Use has a positive and strong influence on Perceived Usefulness, Perceived Usefulness has a positive and strong influence on Attitude Toward Using, Attitude Toward Using has a positive and strong influence on Behavioral Intention to Use, Behavioral Intention to Use has a positive and strong influence on Actual System Use and user involvement has a positive and strong influence on Perceived Ease of Use. Keywords— Expert System, Technology Acceptance Model (TAM), Structural Equation Modelling (SEM) 1. Introduction The rapid technological developments of recent times greatly affect the field of investment. Investment products such as stocks and commodities such as gold, silver, petroleum and foreign exchange can now be done online. Decisions taken in trading transactions of stocks, commodities and foreign exchange is certainly not done at random but through the process of analysis, both the analysis of price movements, as well as analysis based on economic theory. The accuracy of the results of this analysis largely determines the outcome of the transaction, but unfortunately, the ability of this analysis turns out to be a relatively difficult skill to master. This problem of causes potential investors are reluctant to invest in trading stocks, commodities, and forex. Difficulties in this technique of analysis can be overcome by the availability of expert systems in the field of investment that performs analysis of price movements and then automatically performs transactions based on the results of the analysis performed. Expert systems for conducting analysis in this field of investment are available to investors/traders who use the MetaTrader4 trading platform. By using an expert system called Expert Advisor (EA) or a trading robot, investors/traders do not need to masters on analytical skills of price movements of forex or commodities traded in order to take profit from such trades. Research on the use of EA in online trading, especially for forex and commodities has been done by other researchers by way of comparison of the results of trading done by manual and trading results conducted with EA. The study proves that the use of EA can be more accurate in obtaining profit compared to trading by manual [1]. However, the results of a poll conducted by a site about forex trading stated that EA was only used by 18.80% of traders. This, of course, raises the question of how traders actually accept the use of expert systems in online trading. To answer that question, this research will try to study the acceptance of expert system in investment by taking the case of Expert Advisor (EA) acceptance, which is one of the expert systems in online trading by using Technology Acceptance Model (TAM) model from Fred D. Davis [2]. The TAM model used in this research is a TAM model that has been adjusted based on findings from previous studies, including the results of Sung J. Shim's research