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All Journal Jurnal ULTIMA InfoSys Jurnal ULTIMATICS Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks
Monika Evelin Johan
Universitas Multimedia Nusantara
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Medicine & Pharmacology Social Sciences Other

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Journal : Jurnal ULTIMA InfoSys

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Aspect-Based Sentiment Analysis on Application Review using Convolutional Neural Network Putri Arta Aritonang; Monika Evelin Johan; Iwan Prasetiawan
ULTIMA InfoSys Vol 13 No 1 (2022): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v13i1.2684

Abstract

As an obligatory application during the COVID-19 pandemic by Indonesians, PeduliLindungi must have provided outstanding quality services to its users. However, as of December 2021, users’ sentiment toward the quality and service of the PeduliLindungi application was still low, with an application rating of 3.6 out of 5 on the Google Play Store. This study uses text mining techniques for the Aspect-Based Sentiment Analysis (ABSA) task in the PeduliLindungi application review, a sentiment analysis task based on the aspect category of the application. This study aims to classify the users’ sentiment on aspects of the application and provide insight and knowledge to improve the quality of the PeduliLindungi application. The ABSA method used in this study is the classification of aspects and sentiments using the Convolutional Neural Network (CNN) algorithm. The results showed that the CNN model could produce such good performance with an f1 score of 92.23% in the aspect classification and 95.13% in the sentiment classification. The results of user sentiment modelling showed the dominance of negative sentiment in the eight aspects of the application, namely Visual Experience, Scan – Check-in/Out, Vaccine Certificate, eHac, COVID Test, Register/Login, Performance and Stability, and Privacy, Data, and Security. Index Terms—Aspect-Based Sentiment Analysis, Convolution Neural Network, PeduliLindungi, Text Classification, Text Mining.
Web-based Decision Support System for Characters Selection in Game Genshin Impact with SAW Method Patricia Altanny; Monika Evelin Johan
Ultima InfoSys : Jurnal Ilmu Sistem Informasi Vol 14 No 1 (2023): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v14i1.3207

Abstract

Genshin Impact is a game that has lots of amazing playable and time-limited characters. Many F2P players are in a dilemma most of the time, and can’t choose the characters they should draw. This research’s aim is to design and develop a web-based decision support system capable of ranking the best characters based on five combat roles to help F2P fans or player to select the best character, using the SAW (Simple Additive Weighting) method. SAW is capable of choosing the desired criteria (DPS, Heal, Shield, Buff, and Elemental) and each of their weight. The result of the recommendation is for Genshin Impact fans to be able to make a decision on whom they should pull-based. The implementation of this method is in the form of a prototype of a website making it easier for users to use the system anywhere and anytime.
Co-Authors Andreas Yogi Brata Andrew Brillyant Fenina Twince Tobing Hari Santoso Iwan Prasetiawan Jansen Wiratama Johan Setiawan Patricia Altanny Putri Arta Aritonang Rian Rudi Sutomo Samuel Ady Sanjaya