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Journal : Jurnal Informatika

PERANCANGAN ANTARMUKA ONLINE COURSE PADA PERANGKAT MOBILE MENGGUNAKAN TEORI USABILITY Elia Zakharia; Djoko Budiyanto Setyohadi; Y. Sigit Purnomo W. P.
Jurnal Informatika Vol 12, No 1 (2016): Jurnal Teknologi Komputer dan Informatika
Publisher : Universitas Kristen Duta Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (783.059 KB) | DOI: 10.21460/inf.2016.121.468

Abstract

E-learning model can be developed into various forms according to the context of development. All of e-learning model aims to support learning process. The main objective of this study was to design online course interface that runs in mobile device using the theory of usability ISO 9241-11 in UAJY (Universitas Atma Jaya Yogyakarta). Data was collected from 55 undergraduate students of UAJY. It is used as initial state in design process. Furthermore, online course interface design created with use case diagram that adapted to activities of HTA. Nevertheless, in the design process components of interface created by the user persona and mobile device pattern, as well as guided by MGQM, which is also adapted to the limitations of this study and the conditions in UAJY. In addition, using log data collection to handle part of MGQM, which related with time, steps, resources.
ANALISIS SENTIMEN PADA TWITTER MAHASISWA MENGGUNAKAN METODE BACKPROPAGATION Robet Habibi; Djoko Budiyanto Setyohadi; Erna Wati
Jurnal Informatika Vol 12, No 1 (2016): Jurnal Teknologi Komputer dan Informatika
Publisher : Universitas Kristen Duta Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (279.257 KB) | DOI: 10.21460/inf.2016.121.462

Abstract

In a learning environment, emotional factors influence student motivation. Students emotion have an important role in students' capability to learn. The tendency of the students emotion are not easily recognizable in a short time. Twitter is a popular micro-blogging system especially for students. Students post tweet about activities, experiences, their feelings anywhere, anytime and in real time. Sentiment analysis on twitter produce content sentiment that represents the feelings and emotions of students. Sentiment analysis system was built using backpropagation method at the stage of classification. In this research backpropagation network and the classification results were tested using WEKA with multilayer perceptron classifier. The results of sentiment analysis with 30 student respondents are 33.33% tendency of positive emotions, neutral emotions tendency 53.33% and 13:33% negative motional tendencies. The results are used as reference in providing the appropriate treatment of the students during the process of learning.