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Yuhefizar
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jurnal.resti@gmail.com
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INDONESIA
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
ISSN : 25800760     EISSN : 25800760     DOI : https://doi.org/10.29207/resti.v2i3.606
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) menerima artikel ilmiah dengan lingkup penelitian pada: Rekayasa Perangkat Lunak Rekayasa Perangkat Keras Keamanan Informasi Rekayasa Sistem Sistem Pakar Sistem Penunjang Keputusan Data Mining Sistem Kecerdasan Buatan/Artificial Intelligent System Jaringan Komputer Teknik Komputer Pengolahan Citra Algoritma Genetik Sistem Informasi Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Topik kajian lainnya yang relevan
Articles 22 Documents
Search results for , issue "Vol 4 No 2 (2020): April 2020" : 22 Documents clear
Optimasi Nilai K pada Algoritma KNN untuk Klasifikasi Spam dan Ham Email Eko Laksono; Achmad Basuki; Fitra Bachtiar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 2 (2020): April 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (464.316 KB) | DOI: 10.29207/resti.v4i2.1845

Abstract

There are many cases of email abuse that have the potential to harm others. This email abuse is commonly known as spam, which contains advertisements, phishing scams, and even malware. This study purpose to know the classification of email spam with ham using the KNN method as an effort to reduce the amount of spam. KNN can classify spam or ham in an email by checking it using a different K value approach. The results of the classification evaluation using confusion matrix resulted in the KNN method with a value of K = 1 having the highest accuracy value of 91.4%. From the results of the study, it is known that the optimization of the K value in KNN using frequency distribution clustering can produce high accuracy of 100%, while k-means clustering produces an accuracy of 99%. So based on the results of the existing accuracy values, the frequency distribution clustering and k-means clustering can be used to optimize the K-optimal value of the KNN in the classification of existing spam emails.
Menentukan Matakuliah yang Efektif Belajar Daring (Belajar dan Ujian) dengan Metode Multi-Attribute Utility Theory (MAUT) Tonni Limbong; Janner Simarmata
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 2 (2020): April 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (875.39 KB) | DOI: 10.29207/resti.v4i2.1851

Abstract

The Corona pandemic in Indonesia forced the learning system into a drastic change into online learning. Many campuses that were previously quite comfortable with face-to-face learning were forced to be helpless because they had never prepared a backup plan when something unexpected happened, one of which was when the campus was forced to not be able to face-to-face. If the learning system continues to be done online, it might cause the quality of learners to decrease dramatically compared to face-to-face learning. Moreover, the courses that must be filtered include theories and practice courses. Most assignments given to students are not seriously done because of a lack of significant evaluation and supervision. The Faculty of Computer Science, Santo Thomas Catholic University, Medan supports this government policy by implementing online learning using the Zoom application for face-to-face and Edmodo for supplementary lecture material for online learning media. In one semester apart from studying there is a test period which is the Midterm Examination (UTS) and Final Examination Semester (UAS) where the current leadership must wisely determine the type and nature of the exams to be conducted online. To find out the effectiveness of the form of exam questions in online implementation, a Multi-Attribute Utility Theory (MAUT) method was conducted, the test results found that online learning with Zoom and Edmodo was very effective for theoretical courses with a value of 0.88, then the results of this calculation it is recommended that online tests be conducted in the form of theories such as multiple-choice, essay and analysis

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