MANAJEMEN PEMBELAJARAN KELAS 2A BERBASIS WEB EDMODO.COM DENGAN MENGGUNAKAN UJI OUTER MODEL EVALUATION DI JURUSAN D-III PMIK POLTEKKES KEMENKES MALANG

  • Puguh Yudho Trisnanto D-III Perekam Medis dan Informasi Kesehatan,Poltekkes Kemenkes Malang
  • Rizky Fadila D-III Perekam Medis dan Informasi Kesehatan,Poltekkes Kemenkes Malang

Abstract

By using the exsogen variable and endogenous variables that include lecturer variable, modul_dosen, student and modul_mahasiswa. Output loading (in SPSS called Factor Loadings) is used to measure the convergent validity of the measurement model (instrument). In this case, the outer load test results show a high value on the LECTURER variable that is more than the tumbs rule of 0.70 (Chin, 1998). A score of more than 0.70 also appears on the construction of POST and MANAGE. The MODUL_DOSEN variable also has a correlation not only with him (MD) but also on the MHS (Student) variable and the MDHS variable (Module_Mahasiswa) From the results it can be concluded that the Student (MHS) and (MDHS) variables have convergent validity That's good, so this variable Must be included in hypothesis testing Moderating variables From the statistical analysis using PLS, it can be concluded that the Student (MHS) and Modul_dosen (MDDS) have a positive influence on the lecturer (DSN), with p <0.05, 0.000 and 0.063 Thus it can be concluded that hypotheses 1 and 2 are supported In addition to testing the test method of construct the flowmap variable of the external test evaluation with the result of cardinality connected 1: 1,1: N and 0: N. The result of class application test is significant by using URL: / /www.edmodo.com Generate variable values that have reliability data with load factor above 0.7 so that the application is feasible in use.

 

Keywords: Management class learning, PLS, Flowmap diagrams, models outer Test Evaluation

References

Byrne, B. M. (2001). Structural Equation Modeling With Amos: Basic Concepts, Applications, and Programming. London: Lawrence Erlbaum Associates Publishers

Fox, J. (2002). Structural Equation Model. Appendix to An R and S-PLUS Companion to Applied Regression

Hair, J.F. Ringle, C.M & Sarstedt, M. (2011) PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, vol. 19, no. 2 (spring 2011), pp. 139–151. © 2011 M.E. Sharpe, In

Henseler, J. Ringle, C.M. & Sinkovicks, R.R.(2009). The use of partial least square modeling in international marketing. New Challenges to International Marketing Advances in International Marketing, Volume 20, 277-319.

Kline, R.B. (2001). Principles and Practice of Structural Equation Modeling. New York: The Guilford Press

Monecke, A. & Leisch, F.(2012) SEM PLS: Structural Equation Modeling Using Partial Least Square. Journal of Statistic Software.

Published
2018-01-31