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  Published Paper Details:

  Paper Title

EMPLOYING MACHINE LEARNING CLASSIFIER TO ASSESS LABORATORY ASSISTANTS

  Authors

  Sulis Sandiwarno

  Keywords

learning, evaluation, machine learning classifiers.

  Abstract


The development of good information now triggers the use of very broad and very easy to use technology. In its development this technology is known as Information Technology (IT), where IT is a good tool in connecting the giver and recipient of information. An example of the application of IT that can measure the level of user satisfaction with the system is by using sentiment analysis. Measuring the level of satisfaction by using this sentiment analysis can also be applied in the field of learning. Previous research has been conducted to measure the level of student satisfaction with the learning process assisted by laboratory assistants based on questionnaires. However, the assessment of student satisfaction in previous studies is said to fail if only limited to questionnaires. We propose using sentiment analysis to evaluate the learning process for students assisted by laboratory assistants. In conducting research using the concept of sentiment analysis we use logistic regression (LR) and na�ve Bayes (NB) methods. As for several stages such as: first, collecting data about opinions or reviews from students whose learning process is assisted by laboratory assistants. Second, we will conduct training data with both methods. Third, we will make conclusions, what methods are best used in measuring the evaluation of learning carried out by laboratory assistants. The results of this study will provide results that NB is a good algorithm in evaluating student opinion levels with an accuracy value of 80.32%.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2007549

  Paper ID - 197275

  Page Number(s) - 5015-5021

  Pubished in - Volume 8 | Issue 7 | July 2020

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Sulis Sandiwarno,   "EMPLOYING MACHINE LEARNING CLASSIFIER TO ASSESS LABORATORY ASSISTANTS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 7, pp.5015-5021, July 2020, Available at :http://www.ijcrt.org/papers/IJCRT2007549.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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