Claim Missing Document
Check
Articles

Found 2 Documents
Search

Modeling of Sea Surface Temperature through Fitting Linear Model with Interaction Miftahuddin Miftahuddin; Wanda Sri Noviana
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 1 (2021): September 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i1.13987

Abstract

Sea surface temperature (SST) is one of the attributes of the world climate system and global warming. The relationship between SST and other climate parameters can be represented in a linearity approach. Through this approach, SST variability shows monthly and yearly effects. Information on these two time effects is important for knowing the period of peak effect as well as other statistical measures in the linear fitting model. The models used include transformation and without covariate transformation, interaction and without covariate interaction, and with centering and with the addition of time covariates in the model. The linear fitting model chosen as the basis for construction is a model with a combination effect of covariate interaction and transformation giving an increase in the magnitude of multiple R2 (56.62%) and adjusted R2 (56.13%) respectively 0.31% and 0.43%. This indicates that the time covariate has a very strong significant effect on the model compared to the continuous covariate. In general, the model has a statistical significance of p-value < 2.2e-16, as well as for the time covariate. However, because the model has an autocorrelation and a large AIC value, this effect is removed by means of an autoregressive moving average. The obtained linear fitting model for SST data is the model with AIC 403.2987.
Analisis Kepuasan Pengguna Aplikasi RWikiStat 3.0 Hizir Sofyan; Rasudin Rasudin; Miftahuddin Miftahuddin; Kurnia Saputra; Marzuki Marzuki; Muhammad Iqbal; Doddy Maulana
Journal of Data Analysis Volume 2, Number 2, December 2019
Publisher : Department of Statistics, Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (266.833 KB) | DOI: 10.24815/jda.v2i2.16104

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.