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Journal : Nuansa Informatika

Perancangan Prototype User Interface Dan Pengujian User Experience Aplikasi Rental Mobil Berbasis Menggunakan Metode Design Thinking ( Studi Kasus : Pt Trans Berjaya Khatulistiwa) Titan, Titan Parama Yoga; Budiman; Efendi Putra, Jilan Hafizh Ferdiansyah
NUANSA INFORMATIKA Vol. 17 No. 2 (2023): Volume 17 No 2 Tahun 2023
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v17i2.9

Abstract

PT Trans Berjaya Khatulistiwa or commonly called Tiketux is a travel ticket booking service company, and mobile and web application developer. Currently Tiketux is developing a web application regarding car rental, to get the results of a UI/UX design that are right on target with user needs using the design thinking method. The design stage in this method is to take an approach that does not only focus on what is seen (the user interface) and felt by the user, but also focuses on the user experience. The research method used is a mix method, namely conducting observations, distributing questionnaires, and searching for data literature through books or journals related to research. The results obtained in this car rental application have good usability for users. This can be seen from the SUS trial regarding the designed user interface prototype
Audit Keamanan Sistem Informasi Puskesmas Dengan Standar ISO/IEC 27001:2013 Dan Framework COBIT 5 Titan, Titan Parama Yoga; Vani Maharani; Naufal Dwi Maulana
NUANSA INFORMATIKA Vol. 18 No. 1 (2024): Nuansa Informatika 18.1 Januari 2024
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v18i1.56

Abstract

One of the problems of a company is the security of information systems. High security is needed to maintain the confidentiality and misuse of information within the organization. To improve the security of business operations and the quality of information technology resources, it is necessary to evaluate the security of existing information technology assets. Just like one of the systems at PT Infokes Indonesia, namely the Health Center Information System, this is a multi-functional application based on a web base so that it can be used by more than one user at the same time as patient recording is done electronically. The purpose of this study was to conduct a security audit of the Health Center Information System at PT. Infokes Indonesia uses ISO/IEC 27001:2013 and the COBIT 5 framework to document audit findings of information system audits at PT. Infokes Indonesia to make an audit report. Based on the results of research that has been conducted through interviews and questionnaires using the COBIT 5 framework and using the APO13 sub domain, the results show that Existing Capability is at level 1 while the expected Capability Level is at level 3 so that the Capability Gap is 2.
A Bidirectional GRU Approach with Hyperparameter Optimization for Sentiment Classification in Game Reviews : Pendekatan GRU Dua Arah dengan Optimasi Hiperparameter untuk Klasifikasi Sentimen dalam Ulasan Game Alamsyah, Nur; Titan Parama Yoga; Budiman; Imannudin Akbar; Hendra, Acep; Januantara Prima, Alif
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.399

Abstract

Sentiment analysis plays a vital role in understanding user perspectives, especially in domains such as game reviews where user feedback influences product perception and engagement. This study presents a comparative approach using Gated Recurrent Unit (GRU), hyperparameter-tuned GRU, and Bidirectional GRU models to classify sentiments in a dataset of game reviews. The experiment begins with standard preprocessing and tokenization steps, followed by vectorization and supervised training. Hyperparameter optimization is conducted using Keras Tuner to identify the most effective configuration of embedding dimensions, GRU units, dropout rates, and learning rates. The best model, a Bidirectional GRU with tuned parameters, achieves a validation accuracy of 85.37% and shows superior performance across key metrics such as precision, recall, and F1-score. Despite the relatively small and imbalanced dataset, the Bidirectional GRU model demonstrates robust generalization. This study also highlights future directions, including class balancing techniques and the integration of pretrained word embeddings to further improve model performance.