Use of information technology in general is very important for the development of the organization. Likewise, if the development of information technology can be applied to the small and medium business sector, so that it can increase the selling value of the sector. This research was conducted to answer the readiness of the SMEs sector in adopting information technology developments in business management. In this case the researcher develops the research model by adopting the technology readiness model and information technology adoption model in the context of technology and environment, combining and adjusting it according to the development of SMEs in Jakarta. This quantitative study involved 67 samples from MSME workers. Data was processed and analyzed using the PLS-SEM method using SmartPLS 2.0 software. The study also explained the results of the readiness factor which has a significant relationship to the utilization of information technology in SMEs in Jakarta
This study is preliminary in the development of a new model whereby combining and integrating an existing model, the adoption model of information technology with the technology acceptance model. The development of this model is done by using the logic of the IPO (input-process-output) and the causal model by combining, adopting, and adapting the previous model. The effect of the formed path consists of 16 links and produces 11 variables. The existing variables will be formed into 55 indicators, where one variable creates five indicators. The process of developing this model will assist researchers in testing the information technology adoption model and the technology acceptance model so that it will get the effect that occurs in both models. This research will also contribute to further research, especially in the study of information systems, which will provide a theoretical basis for modeling. Besides, the transparency of the development and proposed models, especially in the instruments used, will be taken into consideration in conducting further research .
Private Universities (PTS) compete so tight in providing performance in producing quality graduates. In addition, the number of universities in Indonesia which counts a lot both PTN and PTS makes the higher competition between universities as well. So the university strives to improve quality and provide the best education for service recipients, namely students, where one of the problems if there are some students who are late graduating or not on time so that it becomes an obstacle to the progress of the college. Prediction of students graduating on time is needed by university management in determining preventive policies related to early prevention of Drop Out (DO) cases. This prediction aims to determine the academic factors that influence the period of study and build the best prediction model with Data Mining techniques. There are 11 attributes used for Data Mining Classification, namely NPM, Gender, Age, Department, Class, Occupation, Semester 1 Achievement Index, Semester 2 Achievement Index, Semester 3 Achievement Index, Semester 4 Achievement Index and Information as result attributes. From the results of evaluations and validations that have been carried out using the RapidMiner tools the accuracy of the Decision Tree (C4.5) method is 98.04% in the 3rd test. The accuracy of the Naïve Bayes Method is 96.00% in the 4th test. And the accuracy of the K-Nearest Neighbor Method (K-NN) of 90.00% in the second test.
A questionnaire is one method that is very widely used for social research and is an essential stage in an information system survey in this case the instrument adopted from previous research. Research in the field of information systems today is highly developed by the context ranging from industry, education, and other areas that are not limited. The objectives of this study were to assess the nature of the psychometric properties of users, in this case, is the level of readiness of users in adopting information technology in SMEs. Respondents were chosen randomly and were active computer users in SMEs, and the questions and statements given could be responded to and understood well so that the perceptions between researchers and respondents were the same. The population used is by taking several SMEs industries in Jakarta. The survey was conducted by interviewing and distributing questionnaires to employees at SMEs. Data processing is done using partial least squares structural equation modeling (PLS-SEM). The results obtained are 13 of the 70 questions were recommended to be rejected. Besides, the findings can be used by other parties in terms of testing a questionnaire as a reference for consideration, and the confirmation results can be used as a reference in revising the questionnaire questions.
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