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All Journal Jurnal Transformatika JOIV : International Journal on Informatics Visualization JOURNAL OF APPLIED INFORMATICS AND COMPUTING Technologia: Jurnal Ilmiah Bukhori: Kajian Ekonomi dan Keuangan Islam
Fatihia, Wifda Muna
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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UI/UX Optimization of GOBIS Suroboyo Application with User Centered Design Approach and Short User Experience Questionnaire Mayangsari, Mustika Kurnia; Fatihia, Wifda Muna
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9859

Abstract

GOBIS Suroboyo is a mobile application designed to assist Suroboyo Bus passengers in accessing route information, schedules, and general bus details. Despite its potential, the application has lacked systematic user experience evaluation, resulting in usability issues that require improvement. This study aims to optimize the user interface (UI) and user experience (UX) of the GOBIS Suroboyo application using the User-Centered Design (UCD) approach. The research was conducted through four main stages: analysis of the existing application, identification of user needs, redesign of the interface, and evaluation of the resulting prototype. The usability evaluation was performed using the Short User Experience Questionnaire (UEQ-S), which assessed both hedonic and pragmatic qualities. The results showed mean scores of 1.69 for hedonic quality and 1.425 for pragmatic quality, which fall into the "Excellent" and "Above Average" categories, respectively, based on the benchmark scale. These results indicate that the redesigned prototype is engaging, motivating, efficient, and user-friendly. This study concludes that the UCD approach, with active user involvement, is effective in enhancing the user experience of mobile applications.
Comparison of Text Vectorization Methods for IMDB Movie Review Sentiment Analysis Using SVM Mulyawan, Rifqi; Naparin, Husni; Fatihia, Wifda Muna
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10372

Abstract

Sentiment Analysis is a scientific study in the field of Machine Learning that focuses on classifying opinions expressed in text. IMDb is a platform widely used to provide information and share viewpoints among moviegoers worldwide, where audience reactions often serve as a benchmark for a movie’s success. This research aims to classify positive and negative sentiments by applying and evaluating the effectiveness of Support Vector Machine (SVM) with four different feature representation methods: (a) Bag of Words (BoW), (b) TF-IDF, (c) Word2Vec, and (d) Doc2Vec. After preprocessing the textual data, each method was employed to extract features for model training. The experimental results demonstrate that the combination of SVM with Word2Vec achieved the best overall performance with an F1-Score of 0.8607 and an Accuracy of 0.8607, while also being the fastest in training time (75.0s). In comparison, BoW reached an F1-Score of 0.8219, TF-IDF achieved 0.8520, and Doc2Vec obtained 0.8440. These findings highlight that Word2Vec provides the most effective feature representation for sentiment classification using SVM in this study.
Co-Authors Amidatus Sholihat jamil Ansori , Moh. Armiah Armiah Arna Fariza Bustami, Mohammad Reevany Bustomi, Abu Amar Imam Maksum Mayangsari, Mustika Kurnia Mulyawan, Rifqi Naparin, Husni Rahmawati, Oktavia Citra Resmi Razani, Tsania Ursila Sokhi Huda Tita Karlita Wardani, Deyana Kusuma