Perancangan Sistem Logika Fuzzy Tipe-1 dalam Identifikasi Implementasi Mobile Learning Berdasarkan Faktor Kegunaan Menggunakan Teori Technology Acceptance Model (TAM): Studi Kasus Mahasiswa Teknik Fisika ITS

Jannah, Wardatul (2021) Perancangan Sistem Logika Fuzzy Tipe-1 dalam Identifikasi Implementasi Mobile Learning Berdasarkan Faktor Kegunaan Menggunakan Teori Technology Acceptance Model (TAM): Studi Kasus Mahasiswa Teknik Fisika ITS. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Sistem logika fuzzy dapat diterapkan sebagai sistem keputusan. Pandemi covid-19 mengharuskan pelajar termasuk mahasiswa Teknik Fisika ITS belajar secara daring dengan
mobile learning. Untuk mengetahui bagaimana implementasi mobile learning di Teknik Fisika ITS, pada penelitian ini akan dibahas rancangan fuzzy. Metode yang digunakan adalah sistem logika fuzzy tipe-1 Mamdani. Sedangkan untuk variabel yang digunakan adalah berdasarkan teori Technology Acceptance Model (TAM) dengan menggunakan variabel utama kegunaan (Perceived of Usefulness). Pada penelitian ini dilakukan rancang model dengan empat skenario di mana akan dipilih skenario atau model dengan akurasi terbaik berdasarkan kriteria MAPE. Dari hasil rancangan tersebut didapatkan model fuzzy yang dapat digunakan sebagai sistem logika dalam mengetahui implementasi mobile learning di Teknik Fisika ITS. Hasil rancangan sistem logika fuzzy didapatkan bahwa sistem logika fuzzy dengan bentuk keanggotaan trapesium dan jumlah keanggotaan 5 memiliki error yaitu 6.230% di mana model tersebut sudah sangat akurat berdasarkan teori MAPE. Analisis hubungan antar variabel dilakukan dari hasil output simulasi fuzzy dan uji statistik Uji-t, Uji-F, dan koefisien regresi di mana menunjukkan terdapat hubungan positif antar variabelnya. Hasil simulasi Matlab menunjukkan bahwa berdasarkan variabel Persepsi Kegunaan, Niat Perilaku Menggunakan, dan Perilaku Penggunaan rata- rata 85.45% dari 504 mahasiswa menunjukkan Setuju-Sangat Setuju dalam implementasi mobile learning.
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Fuzzy logic system can be applied as a decision system. The covid-19 pandemic requires students including ITS Physics Engineering students to study online with mobile learning. To find out how the implementation of mobile learning in Engineering Physics ITS, in this study will be discussed fuzzy design. The method used is Mamdani type-1 fuzzy logic system. As for the variables used are based on the theory of Technology Acceptance Model (TAM)
using the main variable of usefulness (Perceived of Usefulness). In this study, a model is designed with four scenarios where the scenario or model with the best accuracy will be selected based on the MAPE criteria. From the results of the design obtained a fuzzy model
that can be used as a logic system in knowing the implementation of mobile learning in Engineering Physics ITS. The results of the fuzzy logic system design show that the fuzzy logic system with a trapezoidal membership form and the number of membership 5 has an error of 6.230% where the model is very accurate based on MAPE theory. Analysis of the relationship between variables was carried out from the results of fuzzy simulation output and statistical tests t-test, F-test, and regression coefficients which showed there was a
positive relationship between the variables. Matlab simulation results show that based on the variables of Perception of Usefulness, Intention to Use Behavior, and Usage Behavior an average of 85.45% of 504 students indicate Agree-Strongly Agree in the implementation
of mobile learning.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: sistem logika fuzzy tipe-1,TAM, mamdani, mobile learning, Teknik Fisika ITS, MAPE ==================================================================================================== Type-1 fuzzy logic system, TAM, mamdani, mobile learning, Engineering Physics ITS
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics
H Social Sciences > HA Statistics > HA30.6 Spatial analysis
H Social Sciences > HA Statistics > HA31.35 Analysis of variance
H Social Sciences > HA Statistics > HA31.3 Regression. Correlation
H Social Sciences > HA Statistics > HA31.38 Data envelopment analysis.
T Technology > T Technology (General) > T385 Visualization--Technique
T Technology > T Technology (General) > T57.5 Data Processing
T Technology > T Technology (General) > T57.6 Operations research--Mathematics. Goal programming
T Technology > T Technology (General) > T57.62 Simulation
T Technology > T Technology (General) > T57.74 Linear programming
T Technology > T Technology (General) > T58.5 Information technology. IT--Auditing
T Technology > T Technology (General) > T58.6 Management information systems
T Technology > T Technology (General) > T58.62 Decision support systems
Divisions: Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User: Wardatul Jannah
Date Deposited: 19 Aug 2021 02:27
Last Modified: 19 Aug 2021 02:27
URI: http://repository.its.ac.id/id/eprint/87554

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