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ANALISIS SENTIMEN ULASAN PENGGUNA APLIKASI IDENTITAS KEPENDUDUKAN DIGITAL MENGGUNAKAN ALGORITMA NAIVE BAYES DENGAN PEMBOBOTAN TF-IDF Aprianti Safarani Aprianti Safarani; Budiman; Dadan Zaliluddin
SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Vol 10 (2026)
Publisher : Universitas Majalengka

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Abstract

Research on the Digital Population Identity (IKD) application found a dominant negative sentiment of 74.81% based on an analysis of 10.308 clean reviews from 10,842 raw data collected through web scraping on the Google Play Store from January 2025 to March 2026. This indicates that the level of public satisfaction is still low. Technical obstacles during the registration process and system stability that is often disrupted after application updates are the main user concerns. This study successfully created a sentiment classification model with an accuracy of 87.88% and a negative class recall of 0.99 using the Naive Bayes algorithm and Frequency Term-Inverse Document Frequency (TF-IDF) weighting. The results of the word feature extraction recommend that the registration system architecture should be thoroughly evaluated, each software update should be thoroughly tested, and server capacity should be increased to provide a more stable and efficient user experience in the future in population administration services.
APLIKASI KASIR DAN INVENTORY BERBASIS WEB DENGAN PENERAPAN EXPONENTIAL SMOOTHING Erlangga Kusdinar; Dadan Zaliluddin
SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Vol 10 (2026)
Publisher : Universitas Majalengka

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Abstract

This study aims to design and implement a web-based cashier and inventory application equipped with the Single Exponential Smoothing forecasting method to improve the efficiency of stock and margin management at Toko Satari. Conventional manual recording often leads to human errors, stock discrepancies, and delayed financial reporting. To overcome these issues, a digital system is developed using the Waterfall methodology. The Exponential Smoothing algorithm, with an alpha value of 0.3, is integrated to predict future stock needs based on historical sales data, thus avoiding overstock and understock situations. The results show that the application successfully automates transaction processing, accurately updates inventory in real-time, and provides reliable sales forecasts. The system enhances operational efficiency and supports data-driven decision-making.
IMPLEMENTASI PROGRESSIVE WEB APP PADA APLIKASI PENGADAAN ATK BERBASIS LARAVEL Varhan Dani; Dadan Zaliluddin
SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Vol 10 (2026)
Publisher : Universitas Majalengka

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Abstract

The office supply procurement process at CV Anugrah Pratama Sunarya was previously conducted manually, leading to challenges in inventory management, data recording, and order processing. This research aims to implement a web-based office supply procurement application integrated with Progressive Web App (PWA) technology to enhance the effectiveness and accessibility of procurement services. The system was developed using the Extreme Programming (XP) software development methodology, encompassing planning, design, coding, and testing phases. The application was built using the Laravel framework and a MySQL database, while PWA technology was implemented to enable installation on user devices, faster access, and an improved user experience through browser-based application features. System testing involved Black Box Testing to evaluate functional requirements and White Box Testing to analyze the application's logic and control flow. Implementation results demonstrate that all system functionalities—including product management, procurement transactions, inventory management, and order processing—operate in accordance with established requirements. Furthermore, the integration of PWA technology allows users to access the system more efficiently without the need for installation via app stores. Consequently, the developed system supports the digitalization of procurement activities and enhances the company's operational efficiency.