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All Journal International Journal Of Science, Technology & Management (IJSTM)
Martua , Rifki Agus
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Analysis Of Student Satisfaction Level In The Faculty Of Science And Technology Using The Convolution Neural Network Method Martua , Rifki Agus; Irmayani , Deci; Yanris, Gomal Juni
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1178

Abstract

The Faculty of Science and Technology at Labuhanbatu University is one of the leading faculties that focuses on the development of science and technology. This faculty offers various study programs designed to prepare students to face the challenges of the digital era and industrial revolution 4.0. This research, using survey and interview methods, aims to collect accurate and objective data regarding student perceptions and experiences in various aspects, such as the quality of educational services, quality of teaching, and available supporting facilities such as extracurricular activities, seminars and research projects, ease of access. information and academic support from optimal staff and teaching staff.
Co-Authors Irmayani , Deci Yanris, Gomal Juni