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All Journal JUITA : Jurnal Informatika Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini JURNAL MEDIA INFORMATIKA BUDIDARMA JURIKOM (Jurnal Riset Komputer)
Miftahurrahma Rosyda
Universitas Ahmad Dahlan, Yogyakarta
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering

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Journal : JURNAL MEDIA INFORMATIKA BUDIDARMA

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Sentiment Analysis Tweet Pilkada 2020 Saat Pandemik COVID-19 di Media Sosial Twitter Menggunakan Metode 1D Convolutional Neural Network Ganjar Tata Pangestu; Miftahurrahma Rosyda
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3765

Abstract

Pilkada 2020 is a debate since it takes place in the midst of the COVID-19 pandemic. The emergence of comments from several social media such as Twitter. There are various public opinions that agree that the Pilkada will still be held, there are also other public opinions that support the postponement of the Pilkada until the COVID-19 pandemic ends. These different opinions require Sentiment Analysis which aims to obtain or find out the general opinion of the 2020 Regional Head Election during the Coronavirus pandemic. A total of 200 data in the form of tweets which are divided into 2 data, namely 20% test data and 80% training data obtained by retrieving data from Twitter using the twint library, based on predetermined keywords. The resulting data set is classified into three classes namely positive, neutral, and negative. In this test or research, deep learning uses the Convolutional Neural Network classification, because it has been proven effective in the case of natural language processing and can get good results in grouping sentences. From this research, the accuracy result is 72.50% with the epoch used is 25 epoch. From the increase in epochs, there is an increase in accuracy of 7-12% from the previous epoch variations.
Sistem Pendukung Keputusan Penentuan Profesi Mahasiswa Informatika Menggunakan Metode WP-RIASEC Raihan Aqila Taufik; Miftahurrahma Rosyda
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 3 (2022): Juli 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4312

Abstract

Informatic Program in Ahmad Dahlan University engaged in the field of informatics/computer science. At the Informatic Program in Ahmad Dahlan University, there are still many students who are confused when they want to decide which profession to pursue when they graduate. This is based on a questionnaire distributed to final semester students from the Informatics Program in Ahmad Dahlan University. From the distributed questionnaires, the results of the questionnaire were obtained, namely more than 50 percent of respondents were still confused in determining the professional field to be occupied when they graduated. In addition, in an interview conducted with a psychologist, he said that personality is very influential on a person's work. To help Ahmad Dahlan University Informatics Students in determining a profession, a decision support system was created that can help students of the department in determining the appropriate professional field based on the value of the course and their personality. The method used in this research is WP and RIASEC. The WP method plays a role in calculating the weight of each course value. While the RIASEC method plays a role in determining a person's personality which is the basis for determining appropriate professional alternatives based on their personality. The results of system testing that have been carried out on 10 respondents consisting of 7 students and 3 alumni from the Informatics Program in Ahmad Dahlan University have obtained test results with a value of 84.5, which means the system is running well and meets the existing standards.
Co-Authors Avanti Vera Risti Pramudyani Ganjar Tata Pangestu Murinto Murinto Prima Suci Rohmadheny Raihan Aqila Taufik Tri Suryo Wahyu Aji