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All Journal CESS (Journal of Computer Engineering, System and Science) Jurnal Keperawatan dan Fisioterapi (JKF) Jurnal Kesmas dan Gizi (JKG) INFOKUM LOFIAN: Jurnal Teknologi Informasi dan Komunikasi Jurnal Pengmas Kestra (JPK)
Beny Irawan, Beny
Institut Kesehatan Medistra Lubuk Pakam
Computer Science & IT Health Professions Nursing Public Health Other

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Analysis of Elearning Quality Measurement With Webqual Method at Politeknik MBP Medan Erwin Daniel Sitanggang; Maradu Sihombing; Maranata Pasaribu; Beny Irawan
INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

The development of information technology today has also changed the lifestyle and way of life of many people. By using information technology, many people can explore the world without being limited by space and time through the internet. Information technology has become a tool that has the power as a driving force that changes business, economics, socio-politics and other fields without limits. One of the things that has experienced major changes in lifestyle and way of life in the field of education is teaching and learning activities. The Politeknik MBP Medan college, which was also affected by Pandami, had to change the teaching-learning method using the Learning Management System service which is the right teaching-learning method to provide learning materials to students, in this case called students. In order to obtain the quality of this service, first, the satisfaction level of service users is measured based on the standard of comparison (gap) between reality and the expectations of users of the service. Based on the results of quality measurements from e-learning at the Politeknik MBP Medan for the academic year 2020/2021 in the even semester using the Webqual method, it was concluded that the Webqual method along with its attributes can provide analytical results to be used in improving the performance quality of e-learning. The results of measuring the quality of the data processing of respondents' answers are obtained that the User Satisfaction Level Score is -0.18, this indicates that the quality of e-learning as a whole is not in line with the expectations of users. The results of the analysis of 22 statement attributes from the Webqual method show that all attributes get the results of the "Tingkatkan" pattern analysis and none of the statement attributes get the "Pertahankan" pattern.
The College Academic Service Decision Support System Uses Service Quality and Importance-Performance Analysis Methods Beny Irawan; Raden Aldri Kurnia; Erwin Daniel Sitanggang; Misdem Sembiring
INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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The impact of the Covid-19 pandemic that has hit the world affects human needs in utilizing technology to be able to solve the problems they face. Likewise, universities that want to improve the quality of academic services during a pandemic sometimes have problems with accuracy and speed in data processing when measuring the level of student satisfaction whose information will be used as support in making decisions to improve services. It is better to develop a computerized system that can replace all activities in the process of implementing the measurement of academic service quality from distributing questionnaires to getting the results of Service Quality (Servqual) and Importance-Performance Analysis (IPA) analysis using the Unified Modeling Language (UML) approach. The design of the decision support system used in this design, namely: Use Case Diagrams, Class Diagrams, Activity Diagrams, Sequence Diagrams and Deployment Diagrams. By using a computerized decision support system, the process of measuring the level of student satisfaction with academic services can be carried out quickly, precisely and accurately compared to using word processing and spreadsheet software and provides easy-to-understand information and suggestions for improvement. academic services based on the attributes of the questionnaire accurately using the Service Quality (Servqual) method on Gap 5 and Importance-Performance Analysis (IPA).
Analysis of Higher Education Academic Service Satisfaction Levels using the Service Quality and Importance-Performance Analysis methods Beny Irawan
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

The academic services of the college today have undergone very significant changes in a very fast time. For these changes, and evaluation of academic services is carried out by measuring the performance of the services provided. To obtain the level of satisfaction, the Service Quality (Servqual) method is used, and to obtain performance from the attributes of the questionnaire to improve its performance, the Importance-Performance Analysis (IPA) method is used. The results of the analysis and data processing using the servqual method at gap 5 showed the gap score gap of each variable so that the Guarantee variable with a score of -0.27, Reliability -0.31, Empathy -0.34, Date Power -0.42 and Tangibles with a score of -0.49. Overall the gap score is -0.37. This shows that any level of service satisfaction expected by students for academic services has not met expectations, as well as the variables of the servqual method. To determine the proposed service improvement based on the attributes of the questionnaire using the Importance-Performance Analysis (IPA) method, 8 attributes are in quadrant I that need to be prioritized for improvement. The attributes are attribute number 4 with a respondent suitability rate of 84.70%, attribute number 5 with a respondent suitability rate of 85.90%, attribute number 10 with a respondent suitability rate of 88.59%, attribute number 15 with a respondent suitability rate of 89.88%, attribute number 16 with a respondent suitability rate of 87.62%, attribute number 17 with a respondent suitability rate of 90.14%, attribute number 18 with a respondent conformity rate of 89.22% and attribute number 27 with a respondent conformity rate of 88.87%.
Co-Authors Anggi Isnani Parinduri Atika Sari Lubis Erwin Daniel Sitanggang Erwin Daniel Sitanggang Erwin Daniel Sitanggang Irmayani Irmayani Iskandar Markus Sembiring Maradu Sihombing Maranata Pasaribu Misdem Sembiring Misdem Sembiring Munthe, Novita Br Ginting Raden Aldri Kurnia Rahmad Gurusinga Sayed Achmady Sitanggang, Erwin Daniel Sri Wulan