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All Journal Jurnal CoreIT Journal Software, Hardware and Information Technology RISTEC : Research in Information Systems and Technology Abdi Akommedia : Jurnal Pengabdian Masyarakat
dwi yunita, hilda
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Computer Science & IT Education Mathematics Physics Other

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Penerapan Aplikasi Simulasi Ujian Akhir Semester Pada SMU Negeri I Tanjung Raja Berbasis Online dwi yunita, hilda; Tarnando, Kiki; Winarko, Triyugo
Journal Software, Hardware and Information Technology Vol 3 No 2 (2023)
Publisher : Jurusan Sistem Informasi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/shift.v3i2.93

Abstract

The exam is a form of evaluation that is used to assess the achievement of the lessons taught by the teacher to students. In addition to the national exam, there is an end-of-semester exam at the school. Where the end of semester exams are still carried out conventionally or in writing such as at Tanjung Raja 1 Public High School. This resulted in a slow assessment process carried out by the teacher and a waste of paper and ink in doubling questions. Therefore, an application was created that can be used to carry out online final semester exam simulations. So that it can overcome all the problems that exist in the final semester exams at SMA Negeri 1 Tanjung Raja, North Lampung.
Peningkatan Literasi Digital dan Penggunaan Teknologi Open Source untuk UMKM di Era Transformasi Digital Fahurian, Fatimah; Dwi Yunita, Hilda; Zuhri, Khozainuz; Ikhwan, Ahmad; Hartanto, M.Budi
ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT Vol. 2 No. 4 (2024)
Publisher : ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT

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Abstract

Era transformasi digital menghadirkan tantangan sekaligus peluang bagi Usaha Mikro, Kecil, dan Menengah (UMKM). Namun, banyak UMKM yang menghadapi hambatan dalam mengadopsi teknologi digital karena keterbatasan literasi digital dan tingginya biaya perangkat lunak berlisensi. Program pengabdian masyarakat ini bertujuan untuk meningkatkan literasi digital UMKM di Bandar Lampung dengan memperkenalkan teknologi open-source seperti GnuCash untuk manajemen keuangan dan Odoo untuk pengelolaan inventaris. Alat ini menyediakan solusi yang terjangkau yang dapat meningkatkan efisiensi bisnis, merampingkan operasional, dan meningkatkan daya saing di pasar digital. Program ini mencakup sesi pelatihan dan pendampingan teknis berkelanjutan untuk memastikan keberlanjutan adopsi teknologi The digital transformation era presents both challenges and opportunities for Micro, Small, and Medium Enterprises (MSMEs). However, many MSMEs face obstacles in adopting digital technologies due to limited digital literacy and high costs of proprietary software. This community service program aims to enhance digital literacy among MSMEs in Bandar Lampung by introducing open-source technologies such as GnuCash for financial management and Odoo for inventory control. These tools provide affordable solutions that can improve business efficiency, streamline operations, and increase competitiveness in the digital marketplace. The program includes training sessions and ongoing technical assistance to ensure the sustainability of technology adoption.
Analysis of Information System Security in the Context of Cyber Attacks on Business Organizations Marliana, Iin; Eko Hendro Pramono, Doni; Yuniarthe, Yodhi; Dwi Yunita, Hilda; Zuhri, Khozainuz
RISTEC : Research in Information Systems and Technology Vol. 5 No. 2 (2024): RISTEC: Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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Abstract

Cyberattacks have become a significant threat to business organizations in the digital era. This study aims to analyze the security of information systems in mitigating cyber threats targeting businesses. The research employs a systematic literature review method to explore various cyberattack techniques, identify vulnerabilities in information systems, and propose effective prevention and mitigation strategies. Findings indicate that cyberattacks are increasingly sophisticated, necessitating adaptive and multi-layered security approaches to safeguard information systems. The study concludes that proactive measures, including robust authentication, encryption, and user training, are essential for enhancing cybersecurity resilience in business organizations.
Big Data Processing with Neural Networks on RESTful API for Product Recommendation Using Python hartanto, budi; Fahurian, Fatimah; Dwi Yunita, Hilda; Winarko, Triyugo
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.34704

Abstract

The exponential growth of e-commerce data has created an urgent need for efficient and scalable systems that provide personalized product recommendations. This study addresses that challenge by integrating big data processing with neural networks and delivering recommendations via RESTful APIs. The primary objective is to develop a system capable of handling large datasets and providing real-time recommendations to enhance user engagement. The methodology involves using Apache Spark for distributed big data processing and feature engineering, followed by the implementation of neural networks in Python using TensorFlow to generate recommendations. The system integrates the model with a RESTful API to support seamless interaction with external applications. Extensive testing was conducted on a dataset containing over a million user-item interactions to evaluate performance and scalability. The results show that the proposed system achieves better recommendation accuracy compared to traditional machine learning approaches. It processes high-dimensional data efficiently and maintains latency below 200 milliseconds per API request, making it suitable for real-time applications. The novelty of this research lies in the end-to-end design that combines a big data framework with neural networks and RESTful APIs for practical implementation. This research provides a scalable and adaptive solution for e-commerce platforms and serves as a foundation for the advancement of real-time recommendation systems in the future.
Co-Authors Budi Hartanto Eko Hendro Pramono, Doni Fahurian, Fatimah Hartanto, M.Budi ikhwan, Ahmad Khozainuz Zuhri marliana, iin Tarnando, Kiki Triyugo Winarko, Triyugo Yodhi Yuniarthe