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All Journal Jurnal Teknik Informatika C.I.T. Medicom Jurnal Info Sains : Informatika dan Sains
Sulastri Sulastri
STMIK Pelita Nusantara
Computer Science & IT

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PERAMALAN JUMLAH MAHASISWA BARU DENGAN PENDEKATAN REGRESI LINIER Yulia Utami; Desi Vinsensia; Aura Nissa; Sulastri Sulastri
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol14.2022.231.pp10-15

Abstract

Forecasting models are the result of developments in the field of science and technology that provide convenience in predicting future events. This paper aims to develop a linear regression model to predict the number of new students in the next year. The data to be used in this study is the total of students majoring in informatics engineering and information management during the last 5 years. Based on result obtained the number of student for department of Informatics Engineering is 198 people with a MAPE (Mean Absolute Percentage Error) score of 16.5%, and for the new students department of Informatic Management is 8 people with a MAPE score of 16.1%.
Analysis Of Student Sentiment On Lecturers Teaching Using The Fuzzy Tsukamoto Method Wira Apriani; Sulastri Sulastri; Finna Maulidina
Jurnal Info Sains : Informatika dan Sains Vol. 13 No. 02 (2023): Jurnal Info Sains : Informatika dan Sains , Edition September  2023
Publisher : SEAN Institute

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Abstract

Analysis of student sentiment on lecturer teaching performance This study aims to analyze student sentiment on lecturer teaching performance in a good university. The method used in this research is sentiment analysis using the Fuzzy Tsukamoto Method. The data were obtained from the results of a questionnaire conducted on students regarding the teaching performance of lecturers in the last semester. The data is then processed and analyzed using a classification algorithm to classify student sentiment into positive, negative, or neutral towards lecturer teaching performance. is student sentiment towards lecturers, from the teaching quality testing data = 2 positive words (8), Material Availability = 2 neutral words (7), Student and lecturer interaction = 1 negative word (4), Lecturer Feedback Quality = 2 negative word (3) from the input the output result is a value of 3 and is in the negative set, so the result of the test is negative sentiment
Co-Authors Aura Nissa Finna Maulidina Utami, Yulia Vinsensia, Desi Wira Apriani