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Home > Volume 2, Number 2, December 2019 > Sofyan
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Asep Rusyana
Department of Statistics, Faculty of Mathematics and Natural Sciences, Syiah Kuala University
Jalan Syech Abdurrauf No.3, Kopelma Darussalam, Banda Aceh 23111, Aceh, Indonesia
Email: jda@unsyiah.ac.id
Mobile Phone: +6281360635965

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Analisis Kepuasan Pengguna Aplikasi RWikiStat 3.0

Hizir Sofyan, Rasudin Rasudin, Miftahuddin Miftahuddin, Kurnia Saputra, Marzuki Marzuki, Muhammad Iqbal, Doddy Maulana

Abstract

RWikiStat 3.0 adalah aplikasi android untuk pebelajaran statistika berbasis RWeb dan Teknologi Wiki. Aplikasi ini merupakan pengembangan dari RWikiStat 2.0. Kepuasan pengguna aplikasi RWikiStat 3.0. dianalisis dalam tulisan ini. Performa yang dianalisis adalah tampilan aplikasi, tingkat responsif, dan kemanfaatan aplikasi. Data penelitian diperoleh dengan metode survei. Survei dilakukan setelah pelatihan penggunaan aplikasi ini. Pelatihan tersebut dilakukan pada tiga perguruan tinggi di Banda Aceh, yaitu Universitas Serambi Mekkah (USM), Universitas Syiah Kuala (Unsyiah), dan Sekolah Tinggi Keguruan dan Ilmu Pendidikan Bina Bangsa Getsempena (STKIP BBG). Sampel diambil dengan menggunakan metode cluster random sampling dan Unsyiah terambil sebagai klaster penelitian. Jumlah sampel dari Unsyiah adalah sebanyak 37 responden. Responden diberikan angket yang mengandung 9 pertanyaan terkait dengan pendeskripsian secara umum tentang kepuasan responden sebagai pengguna terhadap aplikasi RWikiStat 3.0. Hasil analisis menghasilkan bahwa secara umum responden telah puas akan aplikasi RWikiStat 3.0. Kepuasan terhadap tampilan aplikasi, tingkat responsif, dan kebergunaan aplikasi cukup tinggi. Kemudian, responden memiliki keinginan yang besar untuk merekomendasikan aplikasi ke teman, kolega, atau lainnya.

 

RWikiStat 3.0 is an android application for RWeb and Wiki technological -based statistics learning. This application is the development of RWikiStat 2.0. User satisfaction of RWikiStat 3.0 application was analysed in this paper. Performance was analysed based on the application interface, responsiveness, and features of the application. The research data were obtained by survey method conducted after the training to use this application. The training was conducted at three universities in Banda Aceh, namely Serambi Mekkah University (USM), Universitas Syiah Kuala (Unsyiah), and the Higher School of Teacher Training and Education of Bina Bangsa Getsempena (STKIP BBG). Samples were taken using cluster random sampling method and Unsyiah was fetched as research clusters. The number of samples of Unsyiah were 37 respondents. Respondents were given a questionnaire containing nine questions related to the general description of respondent satisfaction as users for using the application of RWikiStat 3.0. The results of the analysis showed that the overall respondents were satisfied using the application of RWikiStat 3.0. There was higher satisfaction in the application interface, the level of responsiveness and usability of applications. Then, the respondents had a great intention to recommend the application to friends, colleagues, or others.

 Keywords

RWikiStat; android; pembelajaran statistika

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References

R Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, 2009, URL http://www.R-project.org.

http://www.math.montana.edu/Rweb/. Last access in January 2010.

Sofyan, H., Muttaqin, E., Subianto, M. 2012. RWikiStat 2.0: a Web Based Statistical Learning System. Proceedings of the Symposium of Japanese Society of Computational Statistics 26. Tokyo : Japanese Society of Computational Statistics.

Sofyan, H., Achsani, N.A., 2004, MM*INDO : Interactive Statistics Learning In Indonesian Language, STATISTIKA: Forum Teori dan Aplikasi Statistika, 4, p. 1411-5891..

Subianto, M., Sofyan, H. 2010. Interactive Statistics Learning with RWikiStat. Proceedings of the 2010 International Conference on Networking and Information Technology (ICNIT). Manila : IEEE.

DOI: https://doi.org/10.24815/jda.v2i2.16104

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About The Authors

Hizir Sofyan
Department of Statistics, Faculty of Mathematics and Natural Sciences, Syiah Kuala University
Indonesia

Rasudin Rasudin
Syiah Kuala University

Miftahuddin Miftahuddin
Syiah Kuala University

Kurnia Saputra
Syiah Kuala University

Marzuki Marzuki
Syiah Kuala University

Muhammad Iqbal
Syiah Kuala University

Doddy Maulana
Syiah Kuala University

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Keywords ARIMA Analisis Regresi Banda Aceh Biplot Canonical correlation analysis Computer Network Correspondence Development areas Forecasting Hybrid Kemiskinan Korelasi MANOVA Mean lingkage Multidimensional Nutritonal status Quality of Service Software-defined Network Spatial Regression Stunting Sumatera Island
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