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All Journal JTEV (Jurnal Teknik Elektro dan Vokasional Jurnal Sisfokom (Sistem Informasi dan Komputer) JURNAL PENDIDIKAN TAMBUSAI Jurnal Sosial dan Teknologi Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Knowbase : International Journal of Knowledge in Database Intellect : Indonesian Journal of Learning and Technological Innovation Journal of Information System and Education Development Jurnal SUTASOMA The Indonesian Journal of Computer Science Jurnal Rekayasa Perangkat Lunak
Maiyana, Efmi
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Desain dan Rancang Bangun Aplikasi Laporan KKN Berbasis Laravel dengan Visual Studio dan Database safutri, lisa; Maiyana, Efmi
Jurnal Rekayasa Perangkat Lunak Vol. 4 No. 2 (2025): Jurnal Rekayasa Perangkat Lunak (J-Rapa)
Publisher : Universitas Aisyah Pringsewu

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Abstract

Community Service Program (KKN) is an academic activity that must be undertaken by university students as a form of community engagement. In practice, the reporting process for KKN activities is often carried out manually, which is inefficient and prone to data loss. This research aims to design and develop a web-based KKN reporting application using the Laravel framework, supported by Visual Studio Code as the code editor and MySQL as the database management system. The method used is Research and Development (R&D), which includes literature study, requirement analysis, system design, development, and application testing. The result of this research is a web-based application that enables students to create and upload activity reports, and allows supervisors to provide assessments directly through the system. The application is tested based on functionality, user interface (UI/UX), and performance. This system is proven to improve efficiency, transparency, and accuracy in the KKN reporting process, while also simplifying monitoring for lecturers and administrators.
Perancangan Aplikasi Pembelajaran Tata Cara Sholat Berbasis Android Untuk Meningkatkan Keterampilan Praktik Ibadah Siswa Maiyana, Efmi; Hidayat, Wahyu; Martua Haholongan Sir, Sadar
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1634

Abstract

Technological advances in education provide opportunities to improve Islamic teaching, particularly in learning to read and practice prayer. MTsN 1 Bukittinggi experienced a problem, namely boredom among students due to the continued use of presentation slides and lecture-based teaching methods. Therefore, the researcher wanted to design a learning media application for prayer procedures. This study aims to design an Android-based application for learning prayer procedures as a medium to improve students' worship skills. The application was developed using the Research and Development (R&D) method with the ADDIE model, which includes needs analysis, design, development, implementation, and evaluation. The application design consisted of two stages, namely logical design using UML, which included use case diagrams, sequence diagrams, and activity diagrams, followed by physical design, where the application was developed using Android Studio and equipped with features such as prayer material, movement guides, audio recitations, and evaluations. The results of the black box media test showed that the application functioned properly. The designed learning media application provides features and supporting menus that offer practicality in using the learning media application for prayer procedures, such as the prayer menu, the Qur'an, and the determination of the qibla direction. Abstrak Pertumbuhan teknologi dalam bidang Pendidikan memberikan peluang untuk meningkatkan pembelajaran ajaran islam, khususnya dalam pembelajaran bacaan dan praktik sholat. Pada MTsN 1 Bukittinggi mengalami permasalahan yaitu rasa bosan yang timbul bagi siswa karena masih menggunakan media pembelajaran slide presentasi dengan metode ceramah sehingga peneliti ingin merancang sebuh aplikasi media pembelajaran tata cara sholat. Penelitian ini bertujuan merancang aplikasi pembelajaran tata cara salat berbasis Android sebagai media untuk meningkatkan keterampilan praktik ibadah siswa. Pengembangan aplikasi dilakukan dengan metode Research and Development (R&D) menggunakan model ADDIE yang meliputi analisis kebutuhan, perancangan, pengembangan, implementasi, dan evaluasi. Perancangan aplikasi terdiri dari dua tahapan yaitu perancangan secara logika menggunakan UML yang meliputi use case diagram, sequence diagram dan activity diagram, kemudian perancangan secara fisik dimana aplikasi dikembangkan menggunakan Android Studio dan dilengkapi fitur materi salat, panduan gerakan, audio bacaan, serta evaluasi. Hasil uji black box media menunjukkan bahwa aplikasi berfungsi dengan baik. Aplikasi media pembelajaran yang telah dirancang menghadirkan fitur dan menu – menu pendukung yang dapat memberikan kepraktisan dalam menggunakan aplikasi media pembelajaran tata cara sholat seperti menu do’a, Al – Qur’an dan penentuan arah kiblat.
ResNet50-Based Deep Learning Architecture with Focal Loss Optimization for Automated Fruit Ripeness Classification Putri, Stefani Hardiyanti; Nasrullah, Nasrullah; Maulana, Fefi; Rahmayanti, Prilia; Maiyana, Efmi
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 01 (2026): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i01.2449

Abstract

This study develops an Enhanced ResNet50 architecture with Focal Loss optimization for automated fruit ripeness classification. The research implements systematic modifications to the standard ResNet50 framework, incorporating attention mechanisms, strategic transfer learning with 20 trainable layers, and advanced class imbalance handling through Focal Loss function (α=[0.809, 1.904, 0.807], γ=2.0). The model processes RGB images (224×224×3) across three ripeness categories: Overripe, Ripe, and Unripe, utilizing the Kaggle Fruits Ripeness Classification Dataset containing 4,434 high-quality images. The Enhanced ResNet50 architecture achieves 97.22% classification accuracy with corresponding precision, recall, and F1-scores of 0.9722, demonstrating superior performance compared to standard ResNet50 (91.7%), VGG16 (89.2%), and EfficientNet-B0 (88.5%). The model exhibits efficient computational characteristics with 50-100ms inference time and 104.55 MB model size, while successfully addressing mild class imbalance (ratio 0.424) through systematic optimization techniques.
Co-Authors Ambiyar, Ambiyar Anugrah, Berry Asmar Yulastri Aulia, Wizra dona kurnia, dona Febrianda, Habib Maulana Ganefri Giatman Haholongan Sir, Sadar Martua Hansi Effendi Jalius, Nizwardi Martua Haholongan Sir, Sadar Maulana, Fefi Murni Astuti Muskhir, Mukhlidi Nasrullah Nasrullah Putri, Stefani Hardiyanti Rahmayanti, Prilia Ratna Sari Refdinal, Refdinal safutri, lisa Sarimah Sarimah, Sarimah Supratman Supratman, Supratman Uliyanti, Rinci Wahyu Hidayat Winda Lestari Siregar