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All Journal JIKA (Jurnal Informatika) Jurnal Minfo Polgan (JMP)
Dinar Ajeng Kristiyanti
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Computer Science & IT Decision Sciences, Operations Research & Management Library & Information Science Mathematics Social Sciences

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PENERAPAN METODE SIMPLE ADDITIVE WEIGHTING PADA SISTEM PENDUKUNG KEPUTUSAN PENENTUAN BEASISWA DAN REKOMENDASI MAGANG Dinar Ajeng Kristiyanti
Jurnal Informatika Vol 5, No 2 (2021): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v5i2.4534

Abstract

In educational institutions such as universities, scholarships and apprenticeship programs are mandatory, likewise at Trisakti University. Students who receive scholarships must meet predetermined criteria. The problem that often occurs is the provision of scholarships and inappropriate apprenticeship opportunities. The application of the decision support system used is Simple Additive Weighting (SAW) with Multiple Attribute Decision Making (FMADM) is expected to help the university in determining outstanding students who are entitled to receive scholarships and internship recommendations by assessing each student, looking for a weighted addition of the rating performance on each alternative on all attributes. This is useful for making it easier for decision makers related to the problem of selecting outstanding students, so that students who are most worthy of an award will be found in the form of scholarships or recommendations for internships using the criteria for Student Activity Portfolio Aspects, Mastery of English, Creative Ideas Scientific Writing, and National Insights. Based on the results of calculations using the Simple Additive Weighting method by taking into account the existing criteria, students who get the highest score will be selected for scholarships and internship recommendations.
Analisis Sentimen Terhadap Vaksin Covid-19 Menggunakan Algoritma Naïve Bayes Classifier Angga Aditya Permana; Muhammad Wisnu Prayuda; Rohmat Taufiq; Dinar Ajeng Kristiyanti
Jurnal Minfo Polgan Vol. 11 No. 2 (2022): Article Research
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v11i2.12346

Abstract

Pada tahun 2020 bahkan hingga sekarang masyarakat ramai berbincang tentang sebuah virus yang bernama Corona Virus atau COVID-19 yang akan di cegah dengan sebuah vaksinasi, sehingga dari kasus tersebut bermunculan opini yang pro dan kontra tentang vaksin ini. Penelitian ini bertujuan untuk membangun model untuk dapat melihat opini masyarakat yang mengandung sentimen positif, netral, dan negatif. Algoritma yang digunakan dalam penelitian ini adalah algoritma Naïve Bayes Classifier, tahapan penelitian dilakukan dengan cara pengumpulan data tweet atau crawling data, preprosesing, lalu klasifikasi. Penelitian ini menggunakan aplikasi Jupyter Notebook dengan Bahasa python, hasil dari penelitian ini memiliki tingkat akurasi sebesar 58%, masih diperlukan riset tambahan untuk meningkatkan akurasi dari model yang dihasilkan.
Co-Authors Angga Aditya Permana Muhammad Wisnu Prayuda Rohmat Taufiq