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All Journal JURNAL INSTEK (Informatika Sains dan Teknologi) Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Pragmatik : Jurnal Rumpun Ilmu Bahasa dan Pendidikan International Journal of Information Engineering and Science
Muhammad Yordi Septian
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media

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Perencanaan Pengembangan Website Portofolio dengan Sistem Manaj Emen Konten (CMS) untuk Bisnis Fotografi Menggunakan Metode User Centered Design Fadhlan Zaki Darmansah; Muhammad Yordi Septian; Alya Putri Salsabila; Wien Kuntari
SABER : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Vol. 3 No. 1 (2025): Januari : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/saber.v3i1.2014

Abstract

The development of photography technology and the need for digital marketing have encouraged photographers to utilize online media as a promotional tool. This research aims to plan the development of a Content Management System (CMS)-based portfolio website for photography businesses using the User-Centered Design (UCD) approach. The UCD approach ensures that the website design meets the needs of users through iterative stages, including needs analysis, prototype design, and evaluation. The results show that the designed website is able to fulfill the main user needs, such as easy-to-update photo galleries, informative service pages, and responsive contact forms. WordPress CMS was chosen due to its ease of use and design flexibility. With the implementation of UCD, the user satisfaction score increased from 70% to 90%. However, improved security features are recommended to prevent unauthorized access to the photo gallery. This research contributes to the development of efficient digital media to improve the competitiveness of photography businesses in the digital era.
Automatic Passenger Counting System on Public Buses Using CNN YOLOv8 Model for Passenger Capacity Optimization Ari Dian Prastyo; Sharfina Andzani Minhalina; Surya Agung; Denty Nirwana Bintang; Muhammad Yordi Septian; Endang Purnama Giri; Gema Parasti Mindara
International Journal of Information Engineering and Science Vol. 1 No. 4 (2024): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i4.121

Abstract

This study presents the development and evaluation of an automatic passenger counting system for public buses using the YOLOv8 algorithm based on Convolutional Neural Networks (CNN). Accurate passenger counting plays a crucial role in optimizing public transportation operations, as it enables effective capacity management, reduces operational costs, and improves overall passenger comfort. Conventional manual counting methods are often inefficient, time-consuming, and prone to human error, particularly in high-density urban transportation environments. Therefore, an automated and intelligent solution is required to support real-time monitoring and operational decision-making. The proposed system employs deep learning-based object detection to identify and count passengers from video streams captured by cameras installed inside buses. Two camera positions, namely front and rear views, were evaluated to assess system performance under different visual conditions. The experimental results show that the system achieves high detection accuracy in the front camera view, with a confidence score of 0.82, indicating reliable performance in scenarios with minimal object occlusion. In contrast, the rear camera view demonstrates slightly lower accuracy, with a confidence score of 0.76, mainly due to increased object overlap and variations in lighting conditions. These findings emphasize the importance of appropriate camera placement and environmental consideration in improving detection reliability. In addition, the implementation of the proposed system enables real-time monitoring of passenger flow, which supports dynamic scheduling, demand-based route planning, and efficient fleet management. Accurate passenger data allows transportation operators to optimize service allocation, reduce congestion, and enhance overall service quality. Overall, this study contributes to the development of intelligent transportation systems by demonstrating the practical applicability of deep learning-based passenger counting solutions. The proposed approach offers strong potential for real-world deployment in smart city environments, supporting the creation of more sustainable, efficient, and passenger-oriented public transportation services.
EVALUASI FUNGSIONALITAS WEBSITE YUMA LAUNDRY MELALUI PENGUJIAN BLACK BOX DENGAN TEKNIK BOUNDARY VALUE ANALYSIS Sharfina Andzani Minhalina; Denty Nirwana Bintang; Ari Dian Prastyo; Surya Agung; Muhammad Yordi Septian; Wicaksono, Aditya; Muhammad Nasir
Jurnal INSTEK (Informatika Sains dan Teknologi) Vol 10 No 1 (2025): APRIL
Publisher : Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Alauddin, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/instek.v10i1.52797

Abstract

Studi ini mengevaluasi fungsionalitas situs web Yuma Laundry menggunakan metode Blackbox Testing dengan teknik Boundary Value Analysis (BVA). Situs web ini dikembangkan untuk meningkatkan aksesibilitas layanan dan efisiensi operasional dalam pengelolaan data pelanggan untuk bisnis laundry. Penelitian ini bertujuan untuk menguji kemampuan sistem dalam menangani berbagai skenario masukan kritis dengan berfokus pada batasan masukan di beberapa bidang. Proses pengujian melibatkan evaluasi bidang-bidang penting seperti nama pelanggan, jumlah barang, dan jenis layanan, memastikan semuanya sesuai dengan batas masukan yang telah ditentukan sebelumnya. Hasilnya menunjukkan tingkat keberhasilan 60% dari 20 kasus uji, dengan validasi efektif di bidang terkait tanggal, sementara kekurangan diamati dalam penanganan masukan untuk nama pelanggan, jumlah barang, dan jenis layanan. Masalah-masalah ini terutama terkait dengan pesan kesalahan yang tidak jelas atau hilang ketika masukan dibiarkan kosong atau melampaui batas yang ditentukan. Temuan tersebut mengungkapkan area-area di mana validasi masukan sistem perlu ditingkatkan. Rekomendasi mencakup penyempurnaan mekanisme validasi dan penyediaan pesan kesalahan yang lebih jelas untuk meningkatkan keandalan sistem dan pengalaman pengguna secara keseluruhan. Studi ini berkontribusi pada pengembangan sistem informasi berbasis web yang andal bagi penyedia layanan lokal, memastikan akurasi yang lebih tinggi dan interaksi pengguna yang lebih baik bagi administrator dan pelanggan.
Studi Komparatif Efektivitas Pembelajaran Bahasa Jepang melalui LuvLingua dan YouTube di Era Belajar Mandiri Digital Kayla Attya Ramadhani; Fikri Saputra; Muhammad Yordi Septian; Fadhlan Zaki Darmansyah; Humannisa Rubina Lestari
Pragmatik : Jurnal Rumpun Ilmu Bahasa dan Pendidikan  Vol. 3 No. 3 (2025): Juli: Pragmatik : Jurnal Rumpun Ilmu Bahasa dan Pendidikan
Publisher : Asosiasi Periset Bahasa Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/pragmatik.v3i3.1707

Abstract

The rapid advancement of digital technology has transformed the landscape of language learning, particularly in the post-pandemic era where self-directed learning through mobile applications and online platforms is increasingly common. This study explores the effectiveness of two popular digital tools LuvLingua and YouTube in supporting independent Japanese language learning among Indonesian university students. LuvLingua offers a structured, gamified approach suitable for beginners, while YouTube provides authentic and contextual exposure through real-life content. Using a descriptive quantitative method, this research involved twelve students from non-language majors who actively use both platforms to study Japanese. The findings reveal that each platform has distinct advantages: LuvLingua excels in foundational vocabulary and pronunciation, whereas YouTube significantly enhances listening skills and cultural understanding. The combination of both platforms yields optimal learning outcomes, although success heavily depends on learners’ motivation, discipline, and time management. This study contributes to the growing body of research on technology-assisted language learning and provides practical recommendations for learners, educators, and content developers.
Co-Authors Aditya Wicaksono Alya Putri Salsabila Ari Dian Prastyo Denty Nirwana Bintang Endang Purnama Giri Fadhlan Zaki Darmansah Fadhlan Zaki Darmansyah Fikri Saputra Gema Parasti Mindara Humannisa Rubina Lestari Kayla Attya Ramadhani Kuntari, Wien Muhammad Nasir Sharfina Andzani Minhalina Surya Agung