https://journal.unipdu.ac.id/index.php/register/issue/feedRegister2024-02-25T13:32:34+00:00Nisa Ayundaregister@ft.unipdu.ac.idOpen Journal Systems<hr /> <table> <tbody> <tr> <td align="left"><strong>Original title</strong></td> <td>:</td> <td> Register: Jurnal Ilmiah Teknologi Sistem Informasi</td> </tr> <tr> <td align="left"><strong>English title</strong></td> <td>:</td> <td> Register: Scientific Journals of Information System Technology</td> </tr> <tr> <td align="left"><strong>Short title</strong></td> <td>:</td> <td>Register</td> </tr> <tr> <td align="left"><strong>Abbreviation</strong></td> <td>:</td> <td> regist. j. ilm. teknol. sist. inf.</td> </tr> <tr> <td align="left"><strong>Frequency</strong></td> <td>:</td> <td> 2 issues per year (January & July)</td> </tr> <tr> <td align="left"><strong>No. of articles per issue</strong></td> <td>:</td> <td> 10 research articles and reviews per issue</td> </tr> <tr> <td align="left"><strong>DOI</strong></td> <td>:</td> <td> 10.26594/register</td> </tr> <tr> <td align="left"><strong>PISSN</strong></td> <td>:</td> <td><a title="PISSN" href="http://u.lipi.go.id/1459272853" target="_blank" rel="noopener"> 2503-0477</a></td> </tr> <tr> <td align="left"><strong>EISSN</strong></td> <td>:</td> <td><a title="EISSN" href="http://u.lipi.go.id/1452153290" target="_blank" rel="noopener"> 2502-3357</a></td> </tr> <tr> <td align="left"><strong>EIC</strong></td> <td>:</td> <td> Nisa Ayunda</td> </tr> <tr> <td align="left"><strong>Publisher</strong></td> <td>:</td> <td> Faculty of Science and Technology, Universitas Pesantren Tinggi Darul Ulum (Unipdu)</td> </tr> <tr> <td align="left"><strong>Citation Analysis</strong></td> <td>:</td> <td><a title="Scopus" href="https://www.scopus.com/sourceid/21101037310" target="_blank" rel="noopener"> Scopus</a>, <a title="Sinta" href="https://sinta.kemdikbud.go.id/journals/detail?id=1911" target="_blank" rel="noopener">Sinta</a>, <a title="GS" href="https://scholar.google.co.id/citations?user=0O9jqQkAAAAJ" target="_blank" rel="noopener">Google Scholar</a>, <a title="Dimensions" href="https://app.dimensions.ai/discover/publication?and_facet_journal=jour.1314504&and_facet_source_title=jour.1314504" target="_blank" rel="noopener">Dimensions</a>, <a title="wizdom.ai" href="https://www.wizdom.ai/journal/register_jurnal_ilmiah_teknologi_sistem_informasi/research-overlap/2503-0477" target="_blank" rel="noopener">wizdom.ai</a>, <a title="Garuda" href="http://garuda.ristekdikti.go.id/journal/view/8624" target="_blank" rel="noopener">Garuda</a></td> </tr> <tr> <td align="left"><strong>Language</strong></td> <td>:</td> <td> English</td> </tr> <tr> <td align="left"><strong>Discipline</strong></td> <td>:</td> <td> Information Technology, Information Systems Engineering, Intelligent Business Systems, and <a title="Discipline" href="https://journal.unipdu.ac.id/index.php/register/scope" target="_blank" rel="noopener">others</a></td> </tr> </tbody> </table> <hr /> <p><span lang="id"><strong>Register: Scientific Journals of Information System Technology</strong> is an international, peer-reviewed journal that publishes the latest research results in Information and Communication Technology (ICT). The journal covers a wide range of topics, including Enterprise Systems, Information Systems Management, Data Acquisition and Information Dissemination, Data Engineering and Business Intelligence, and IT Infrastructure and Security. The journal has been accredited with grade “<a title="Sinta Register" href="https://sinta.ristekbrin.go.id/journals/detail?id=1911"><strong>SINTA 1</strong></a>” by the Director Decree (<a title="SK Akreditasi 2021" href="https://drive.google.com/file/d/1s8Qi7JjNE5NZg8O3Cjzt0zVgJPm0JqBW/view?usp=sharing">B/1796/E5.2/KI.02.00/2020</a>) as a recognition of its excellent quality in management and publication.</span></p>https://journal.unipdu.ac.id/index.php/register/article/view/3397Measuring Resampling Methods on Imbalanced Educational Dataset’s Classification Performance2023-08-21T05:49:56+00:00irfan pratamairfanp@mercubuana-yogya.ac.idPutri Taqwa Prasetyaningrumputri@mercubuana-yogya.ac.idAlbert Yakobus Chandraalbert.ch@mercubuana-yogya.ac.idOzzi Suriaozzisuria@mercubuana-yogya.ac.id<p>Imbalanced data refers to a condition that there is a different size of samples between one class with another class(es). It made the term “majority” class that represents the class with more instances number on the dataset and “minority” classes that represent the class with fewer instances number on the dataset. Under the target of educational data mining which demands accurate measurement of the student’s performance analysis, data mining requires an appropriate dataset to produce good accuracy. This study aims to measure the resampling method’s performance through the classification process on the student’s performance dataset, which is also a multi-class dataset. Thus, this study also measures how the method performs on a multi-class classification problem. Utilizing four public educational datasets, which consist of the result of an educational process, this study aims to get a better picture of which resampling methods are suitable for that kind of dataset. This research uses more than twenty resampling methods from the SMOTE variants library. as a comparison; this study implements nine classification methods to measure the performance of the resampled data with the non-resampled data. According to the results, SMOTE-ENN is generally the better resampling method since it produces a 0,97 F1 score under the Stacking classification method and the highest among others. However, the resampling method performs relatively low on the dataset with wider label variations. The future work of this study is to dig deeper into why the resampling method cannot handle the enormous class variation since the F1 score on the student dataset is lower than the other dataset.</p>2024-02-25T00:00:00+00:00Copyright (c) 2024 irfan pratama, Putri Taqwa Prasetyaningrum, Albert Yakobus Chandra, Ozzi Suria