Model dan Simulasi Rangkaian RLC Menggunakan Aplikasi Matlab Metode Simulink

Parinduri, Ikhsan

doi:10.54314/jssr.v1i1.106

Cited by 7 publications

(6 citation statements)

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“…Thus, it can be said that the independent variable, namely Matlab application-based learning, separately has a main effect on HOTS in the dimensions of conceptual knowledge, procedural knowledge, and metacognition of students. This is in line with what was revealed by Hutagalung (2018), Okoye (2010), and Zhang (2011). Yaz (1997 and Fangohr (2004) say that in the field of electronics and electricity, the calculation of the formulation of electricity, current, voltage, and power, as well as the development of system models and simulations, can be done using the Matlab program.…”

Section: The Effect Of Interaction Between Learning and Thinking Styl...supporting

confidence: 93%

“…Through the computational power of Matlab, students can cement their understanding of system concepts (Zhou, 2020). The results of research conducted by Hutagalung (2018) and Parinduri (2018) at the senior high school and vocational school levels show that the use of Matlab applications helps in modeling and simulating electrical circuits, such as voltage, current, and resistance, as well as compiling RLC circuit simulation models and aligning theory with the form of models and simulations implemented through Simulink in learning basic physics and basic electronics. Furthermore, according to Widiaty et al (2019), teachers and students have the opportunity to improve a more holistic learning process through a digital approach, and one of the tools utilized is the Matlab application.…”

Section: Matlab-based Learningmentioning

confidence: 99%

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Effectiveness of Matlab-based Learning and Thinking Styles (Internal-External) on Students' Higher Order Thinking Skills

Meok,

Kamdi,

Sutadji

et al. 2024

INT J INSTRUCTION

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Renewal efforts in learning basic electricity and electronics in vocational high schools need to be carried out in order to find the right formula in learning as a new tool to improve students' higher-order thinking skills (HOTS). HOTS are in three dimensions of knowledge, namely conceptual, procedural, and metacognition, which intersect with cognitive levels C4 (analyse), C5 (evaluate), and C6 (create). This research is a quasi-experimental, nonequivalent control group design by applying Matlab application-based learning in the experimental class and comparing it with direct learning in the control class to see differences in students' higher-order thinking skills. In addition, it also looks at the interaction effect between the type of learning applied and the moderator variable, namely the thinking style of students (internal and external), on students' HOTS in three dimensions of knowledge (conceptual, procedural, and metacognition). The participants, or experimental subjects, in this study were class X students with audio-video engineering expertise (TAV). Class X TAV 1 was selected as the experimental class with 34 students, while class X TAV 2 became the control group with 32 students. The results obtained showed the effect of matrix-based learning better than direct learning on students' HOTS in the dimensions of conceptual knowledge, procedural knowledge, and metacognition, and there was no interaction between the type of learning applied and the students' thinking style. Matlab-based learning and thinking styles had a strong influence separately on students' HOTS in the three knowledge dimensions.

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Section: The Effect Of Interaction Between Learning and Thinking Styl...supporting

confidence: 93%

Section: Matlab-based Learningmentioning

confidence: 99%

Effectiveness of Matlab-based Learning and Thinking Styles (Internal-External) on Students' Higher Order Thinking Skills

Meok,

Kamdi,

Sutadji

et al. 2024

INT J INSTRUCTION

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“…Matlab is a high-level programming language developed by MathWorks specifically for numerical computation, visualization, and programming. Matlab allows users to perform data analysis, develop algorithms, and build models and applications (Parinduri 2018). Matlab provides a special toolbox for fuzzy logic called the Fuzzy Logic Toolbox.…”

Section: Discussionmentioning

confidence: 99%

Application of Fuzzy Logic to Predict Rice Production Quantity in Bogor Regency

Suhaila,

Muhammad Hafizh Maulidan,

Muchammad Alifandhino Satrio

et al. 2024

JASTH

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This study aims to understand prediction methods using fuzzy Mamdani logic to conclude the quantity of rice production in the Bogor Regency area. Then in this study, we used quantitative methods and involved interviews with resource persons, namely rice mill workers and farmers. The data obtained from the interview is then fuzzyfication to be used in calculations. The main finding of this study is the elaboration of crop quantity from small, normal, and many, with the range of yields produced ranging from 0 to 3000 KG for little, 3000 to 6000 KG for normal, and 6000 to 10000 KG for many. Weather and humidity observations were found to significantly affect rice yields. The implications of these findings are improved accuracy in yield estimation, and the ability to address uncertainty and complexity in factors affecting crop growth. Despite the limitations of this study, such as limited data and remote study locations, the use of fuzzy logic can make a crucial contribution to determining the quantity of water needed for plant growth based on rainfall and weather conditions. This research is crucial because it can be a reference for future research that uses fuzzy logic to determine the quantity of rice production.

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“…Model merupakan representasi dari suatu objek, benda, atau ide-ide dalam bentuk yang disederhanakan, Model didefinisikan sebagai suatu deskripsi logis tentang bagaimana sistem bekerja atau komponen-komponen berinteraksi. dengan membuat model dari suatu sistem maka diharapkan dapat lebih mudah untuk melakukan analisis [4].…”

Section: Pendahuluanunclassified

Prediksi Tingkat Kunjungan Pasien dengan Menggunakan Metode Monte Carlo

Syaputra¹,

Eirlangga²

2022

jidt

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The increase in the number of patient visits that often occur at community health centers / puskesmas has caused some activities in health services to be slightly hampered, disturbed and less than optimal, resulting in some patients not getting comprehensive services and some even waiting too long in queues. The purpose of this study was to provide information to the health center about the prediction of an increase in the number of patient visits that might occur in the future. The data used in this study were patient visit data at the IX Koto Sungai Lasi health center from 2019, 2020, and 2021 to extract the data that was obtained. The method used in this study was the Monte Carlo method. The results of the study can predict patient visit rates in the following years with an average accuracy rate of 91%, in 2020, and 85% in 2021, the results of these predictions can be a reference for the Puskesmas to take action and policies to improve quality of service at the Puskesmas.

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Model dan Simulasi Rangkaian RLC Menggunakan Aplikasi Matlab Metode Simulink

Cited by 7 publications

References 0 publications

Effectiveness of Matlab-based Learning and Thinking Styles (Internal-External) on Students' Higher Order Thinking Skills

Effectiveness of Matlab-based Learning and Thinking Styles (Internal-External) on Students' Higher Order Thinking Skills

Application of Fuzzy Logic to Predict Rice Production Quantity in Bogor Regency

Prediksi Tingkat Kunjungan Pasien dengan Menggunakan Metode Monte Carlo

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