Study of Student Satisfaction Level in the Faculty Based on Performance Assessment and Interest Level

Autor: Achmad Fauzan, Muhammad Hasan Sidiq Kurniawan, Jaka Nugraha
Rok vydání: 2019
Předmět:
Zdroj: Eksakta: Jurnal Ilmu-Ilmu MIPA, Vol 19, Iss 1, Pp 83-97 (2019)
EKSAKTA: Jurnal Ilmu-ilmu MIPA; VOLUME 19, ISSUE 1, February 2019; 83-97
ISSN: 2716-0459
2720-9326
2503-2364
1411-1047
Popis: One way to evaluate various services at the university is seen from the level of student satisfaction. The purpose of this study is to measure how much the level of student satisfaction in the university environment, especially in the Faculty of Mathematics and Natural Sciences, Universitas Islam Indonesia (FMIPA UII) and future expectations of students focusing on their respective study programs. 6 aspects were used to find out how much satisfaction the students had, namely: (1) Tangible, (2) Reliability, (3) Responsiveness, (4) Assurance, (5) Empathy, and (6) Information. The research method used is descriptive analysis method related to satisfaction represented by the Cartesian diagram. The study was conducted in a period of 3 months with the sample used being active students in the 2016 and 2017 FMIPA classes proportionally in each study program (study program). The data used are primary data consisting of 2 main assessments, namely performance assessment and importance assessment. The results of the level of satisfaction / suitability are classified into the Cartesian diagram which consists of 4 priorities, namely: top priority, achievement priority, low priority, and excessive. The results of the study obtained overall levels of satisfaction in Mathematics as much as 90% of students were satisfied with the level of performance provided. However, there are still 2 indicators that are included in the priority, namely problems in the key-in process and ease of communication for parents of students to consult. In addition to the contents of each indicator, an analysis of suggestions for improvement in the FMIPA environment using text mining based on barplot and wordcloud is associated with the dominant words appearing to describe the general expectations of students
Databáze: OpenAIRE