Classification of Student Aspiration Using Naïve Bayes Classifier

Ifan Rizqa, Christy Atika Sari, Mohamed Doheir

Abstract


Students aspiration are various demands from the student that packed in creative idea to propose changing process of a thing. Mostly, aspiration delivered in complaints and expectation. Aspiration is used for evaluating the laxity and early detection in university quality system for the better. This activity took place in Dian Nuswantoro University, and Student Representative Council (SRC) is the unit to manage the students aspiration. Aspiration is obtained through predetermined mechanism such as manual questionnaire distribution and or using google form. The provided questionnaire requires student to fill the content according to the provided aspiration categories. However, the problem is sometimes the student choose the wrong category according to the content. Therefore it is needed to create an application that can classified the students aspiration automatically. Document text classification become the best way to determine the category based on the content of the students aspiration. Naïve bayes classifier method is used because it is capable to produce high accuracy. With 1000 data training document of each category, "facilities and infrastructure" (facilities), "lecturers" (attitudes, teaching methods, material delivered), "staffing and the academic system"(attitudes, ways of working, providing information), and "suggestions and feedback". This experiment achieved 90.20% accuracy. It can be said that this method is worth to implement in this research.

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DOI: https://doi.org/10.33633/jais.v6i1.4459

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Journal of Applied Intelligent System (e-ISSN : 2502-9401, p-ISSN : 2503-0493) is published by Department of Informatics Universitas Dian Nuswantoro Semarang and IndoCEISS.

  

 

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