PERANCANGAN MODEL SISTEM LOGIKA FUZZY MAMDANI DIBANDINGKAN DENGAN STRUCTURAL EQUATION MODELLING (SEM) UNTUK MENGUKUR PERSEPSI PERILAKU PENGGUNAAN MOBILE LEARNING

Suharsono, Ferina Putri (2021) PERANCANGAN MODEL SISTEM LOGIKA FUZZY MAMDANI DIBANDINGKAN DENGAN STRUCTURAL EQUATION MODELLING (SEM) UNTUK MENGUKUR PERSEPSI PERILAKU PENGGUNAAN MOBILE LEARNING. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Metode sistem logika fuzzy berfungsi sebagai sistem untuk merekomendasikan dalam pengambilan keputusan terkait persepsi perilaku penggunaan m-learning. Terdapat lima variabel pada penelitian ini dengan variabel persepsi perilaku sebagai output. Rancangan model sistem logika fuzzy mamdani terdiri dari 2 sistem, dimana sistem 1 memiliki 4 subsistem dengan input merupakan indikator penyusun dan output yaitu variabel yang digunakan. Sistem 2 memiliki 1 subsistem dengan input merupakan output dari masing-masing subsistem dan output yaitu persepsi perilaku. Terdapat 3 skenario pemodelan sistem logika fuzzy dalam menentukan fungsi keanggotaan input output, sehingga diperoleh nilai MAPE yaitu 9,77%. Metode SEM berperan untuk menganalisa hubungan antar variabel yang digunakan, dengan menyusun variabel independen, variabel interveening, dan variabel dependen. Diperoleh hasil bahwa variabel kesiapan dosen secara langsung memiliki pengaruh yang signifikan terhadap variabel persepsi perilaku, sedangkan variabel kesiapan mahasiswa secara tidak langsung memiliki pengaruh yang signifikan terhadap variabel persepsi perilaku, dan nilai MAPE SEM yaitu 12,53%. Nilai MAPE kedua di atas tergolong kategori baik berdasarkan tabel rujukan MAPE (Maricar, 2019). Dengan demikian, kedua metode tersebut mampu mengukur persepsi perilaku mahasiswa dalam penggunaan m-learning.========================================================================================================= The fuzzy logic system method functions as a system to recommend in decision making related to behavioral perceptions of using m-learning. There are five variables in this study with the behavioral perception variable as the output. The design of the Mamdani fuzzy logic system model consists of 2 systems, where system 1 has 4 subsystems with inputs as constituent indicators and outputs, namely the variables used. System 2 has 1 subsystem with input is the output of each subsystem and the output is the perception of behavior. There are 3 scenarios of fuzzy logic system modeling in determining the input output membership function, so that the MAPE value is 9.77%. The SEM method plays a role in analyzing the relationship between the variables used, by compiling independent variables, interveening variables, and dependent variables. It was found that the variable of lecturer readiness directly had a significant influence on the behavioral perception variable, while the student readiness variable indirectly had a significant influence on the behavioral perception variable, and the MAPE SEM value was 12.53%. The second MAPE value above is in the good category based on the MAPE reference table (Maricar, 2019). Thus, both methods are able to measure the perception of student behavior in the use of m-learning.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: m-learning, sistem logika fuzzy, structural equation modelling, m-learning, fuzzy logic system, structural equation modeling
Subjects: L Education > L Education (General)
L Education > LA History of education
L Education > LB Theory and practice of education
L Education > LC Special aspects of education
Q Science > QA Mathematics > QA275 Theory of errors. Least squares. Including statistical inference
Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression
Q Science > QA Mathematics > QA278.3 Structural equation modeling.
Q Science > QA Mathematics > QA9.64 Fuzzy logic
Q Science > QA Mathematics > QA248_Fuzzy Sets
Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics)
Divisions: Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User: Ferina Putri Suharsono
Date Deposited: 19 Aug 2021 05:38
Last Modified: 19 Aug 2021 05:38
URI: https://repository.its.ac.id/id/eprint/87653

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