Jurnal Sistem Informasi (JUSIN)

PERANCANGAN UI/UX WEBSITE E-COMMERCE PT. DECORMART BANGUN KREASI MENGGUNAKAN METODE DESIGN THINKING

Mon, 29 Jun 2026 00:00:00 +0700

This study aims to design a user interface and user experience (UI/UX) for the e-commerce website of PT Decormart Bangun Kreasi to improve user comfort, usability, and effectiveness in accessing and conducting online purchase transactions. The UI/UX design process uses the Design Thinking method, which emphasizes a user-centered design approach through five main stages: Empathize, Define, Ideate, Prototype, and Testing.

The Empathize stage was conducted to understand user needs and problems through interviews. The Define stage formulated key issues based on user data analysis. During the Ideate stage, various design solutions were developed and implemented as an e-commerce website prototype, including navigation structure and interface layout.

The Testing stage evaluated the usability of the design using the System Usability Scale (SUS) method involving 14 respondents. The results showed a SUS score of 95, categorized as Excellent or Grade A+. These findings indicate that the proposed UI/UX design offers very high usability and meets user needs. Therefore, the UI/UX design is considered suitable for further development as the company’s official website.

PERANCANGAN ULANG USER INTERFACE WEBSITE TRI HITA BALI MENGGUNAKAN METODE DESIGN THINKING

Rifki Rafii, I Gede Putu Krisna Juliharta, Eka Grana Aristyana Dewi — Mon, 29 Jun 2026 00:00:00 +0700

This study focuses on evaluating and redesigning the Tri Hita Bali website using the System Usability Scale (SUS) method. The website serves as a platform providing information about natural-material lampshades but is suboptimal in terms of user interface (UI) and user experience (UX). Identified issues include navigation difficulties, the absence of an online ordering feature, and challenges users face in accessing information.

The research aims to assess user ease, efficiency, satisfaction, and error rates, provide redesign recommendations based on SUS evaluation results, and compare usability results before and after improvements. The redesign recommendations are created using Figma software with a high-fidelity prototype.

The study's findings are expected to enhance user experience and improve business processes at Tri Hita Bali, while also offering insights into UI/UX evaluation and development for websites.

PENGEMBANGAN REPRESENTASI DATA RUMAH SAKIT DI INDONESIA MENGGUNAKAN EXPLORATORY FACTOR ANALYSIS

Mon, 29 Jun 2026 00:00:00 +0700

The increasing availability of hospital data through national health information systems offers significant opportunities for data-driven analysis. However, hospital datasets are often characterized by high dimensionality and numerous interrelated variables, which may lead to information redundancy, increased computational complexity, and reduced interpretability. This study proposes a feature engineering framework based on Exploratory Factor Analysis (EFA) to develop a structured representation of hospital data in Indonesia. Data were collected from the Hospital Information System (SIRS) managed by the Ministry of Health of the Republic of Indonesia, covering various aspects such as human resources, service capacity, healthcare services, and infrastructure. The proposed methodology includes data acquisition, pre-processing, and factor extraction using EFA. The extracted latent factors are expected to capture the underlying dimensions of hospital characteristics while reducing data complexity. The findings are expected to provide a more interpretable representation of hospital profiles and serve as a foundation for future hospital segmentation and machine learning-based healthcare analytics. The proposed framework may also support evidence-based decision-making in healthcare planning and resource management.

PENERAPAN SUPPORT VECTOR MACHINE DAN ANALISIS ASOSIASI UNTUK ANALISIS ULASAN APLIKASI E-TICKETING (STUDI KASUS: TIKET.COM)

Fikri Haikal, Diana Yusuf , Fahrul Razi — Mon, 29 Jun 2026 00:00:00 +0700

The development of digital technology has driven the wider adoption of e-ticketing systems on the Tiket.com application, which is increasingly used by the public. However, the increasing number of users doesn't always correlate directly with satisfaction levels, as evidenced by the diverse user reviews on the Google Play Store. This research is urgent for analyzing user sentiment as a basis for improving service quality. The purpose of this research is to classify reviews into positive and negative sentiments using the Support Vector Machine (SVM) algorithm and to analyze dominant word patterns thru the Apriori algorithm. The research data consists of 5,000 Indonesian-language reviews collected between 2023 and 2025, which were then processed thru preprocessing, TF-IDF weighting, SVM classification, association analysis with Apriori, and result visualization using Streamlit. The research results show that SVM produces a high level of accuracy in sentiment classification, while association analysis reveals dominant words that reflect user satisfaction and complaints. The integration of these two methods provides a more comprehensive understanding of user opinions and is expected to serve as a basis for developing service improvement strategies and as a reference for further research in the field of machine learning-based sentiment analysis.

IMPLEMENTASI WEBGIS UNTUK PEMETAAN FASILITAS UMUM KOTA TANGERANG SELATAN

Nurul Hazmi, Shevti Arbekti Arman, Widi Hastomo Adi Saputro — Mon, 29 Jun 2026 00:00:00 +0700

The availability of accurate and easily accessible public facility information is a crucial need for the public to support their mobility and daily activities. This research aims to design and implement a web-based geographic information system capable of interactively mapping public facilities in the South Tangerang city . The system was built using QGIS software for mapping, PHP and MySQL programming languages for data management, and HTML, CSS, and JavaScript for the user interface. The system development method used was Rapid Application Development (RAD), with stages including planning, design, development, and implementation. Data were collected through field observations, interviews, documentation, and literature review. The resulting system presents spatial data and public facility attributes such as name, type, address, operating hours, and parking availability. Testing was conducted using the black box method to ensure system functionality ran as expected. Evaluation results indicate that this system can assist the public and government in accessing public facility location information effectively and efficiently.

PENERAPAN NATURAL LANGUAGE PROCESSING UNTUK ANALISIS SENTIMEN ULASAN APLIKASI ALLO BANK MENGGUNAKAN ALGORITMA SVM

Singgih Adhi Prasetyo, Diana Yusuf, Muhajir Syamsu — Mon, 29 Jun 2026 00:00:00 +0700

The rapid growth of digital banking applications in Indonesia requires companies to pay close attention to user perceptions and satisfaction. This research focuses on analyzing the sentiment of user reviews of the Allo Bank application obtained from the Google Play Store, applying the Support Vector Machine (SVM) algorithm combined with a Natural Language Processing (NLP) approach. A total of 5,100 reviews in the Indonesian language were collected using web scraping methods. The analysis involved several stages, including text preprocessing, term weighting with TF-IDF, sentiment classification into three categories (positive, negative, and neutral), and performance evaluation of the model. The findings reveal that most user reviews express positive sentiment, with frequently appearing words such as "easy,” "secure,” and "good.” Negative sentiments are commonly represented by words like "complicated,” "lag,” and "slow,” while neutral reviews often include expressions such as "adequate” and "okay.” The SVM model achieved strong performance, with an accuracy of 96%, precision of 97%, recall of 75%, and an F1-score of 79%, indicating high effectiveness despite limited sensitivity to minority classes. These classification results can provide valuable insights for identifying areas that need improvement or should be maintained by the application developers. Therefore, this study is expected to serve as a reference for strategic decision-making based on user feedback to enhance the quality of digital banking services.