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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Manajemen Informatika dan Sistem Informasi Inovasi Sosial: Jurnal Pengabdian Masyarakat
Danny Oka Ratmana
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering

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RANCANG BANGUN APLIKASI PENCATAT KEHADIRAN ASISTEN BERBASIS ANDROID DENGAN METODE AGILE UNTUK LABORATORIUM KOMPUTER UNIVERSITAS DIAN NUSWANTORO Naufal Fawwazi; Rohman, Muhammad Syaifur; Nurul Anisa Sri Winarsih; Yani Parti Astuti; Danny Oka Ratmana
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 7 No. 2 (2024): MISI EDISI JUNI 2024
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/misi.v7i2.1154

Abstract

Perkembangan teknologi, khususnya popularitas smartphone, telah membawa perubahan signifikan dalam manajemen kehadiran, sebuah elemen administrasi penting dalam berbagai konteks, seperti pendidikan dan pekerjaan. Untuk meningkatkan efektivitas pencatatan kehadiran, penelitian ini bertujuan untuk merancang dan mengembangkan aplikasi pencatat kehadiran asisten berbasis Android dengan menerapkan metode Agile di Laboratorium Komputer Universitas Dian Nuswantoro. Mengadopsi metode Agile, penelitian ini mencakup seluruh siklus pengembangan, dengan melibatkan pengguna secara aktif. Proses perancangan dan pengembangan melibatkan pengguna dalam keperluan merancang antarmuka aplikasi dan desain alur kerja sistem, serta mengembangkan sistem dengan bahasa pemrograman Kotlin. Pengujian berlangsung selama tujuh hari efektif dengan implementasi langsung di lingkungan laboratorium komputer, dengan hasil User Acceptance Test (UAT) menunjukkan tingkat kesesuaian fungsional aplikasi mencapai rata-rata 98,17%. Penggunaan aplikasi ini diharapkan dapat meningkatkan efisiensi manajemen kehadiran asisten laboratorium dan memberikan kontribusi positif pada operasional Laboratorium Komputer Universitas Dian Nuswantoro. Kesimpulan penelitian ini menegaskan keberhasilan penerapan metode Agile dalam pengembangan aplikasi pencatat kehadiran asisten berbasis Android.
Penerapan Pelatihan Scratch untuk Meningkatkan Literasi Digital pada Siswa Sekolah Dasar melalui Pembelajaran Pemrograman Visual Muhammad Syaifur Rohman; Galuh Wilujeng Saraswati; Nurul Anisa Sri Winarsih; Filmada Ocky Saputra; Danny Oka Ratmana; Adhitya Nugraha
Inovasi Sosial : Jurnal Pengabdian Masyarakat Vol. 2 No. 3 (2025): Agustus : Inovasi Sosial : Jurnal Pengabdian Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/inovasisosial.v2i3.2021

Abstract

The rapid development of technology has made it increasingly important for the younger generation to acquire digital literacy skills at an early age. As technology becomes an integral part of daily life, it is essential to introduce fundamental programming concepts to students to prepare them for the future. This community service program aims to introduce 5th-grade students at Elementary School Emmaus Kediri to basic programming concepts using the Scratch platform. The program adopted the Project-Based Learning (PjBL) method, which emphasizes interactive learning through hands-on activities. The one-day session involved 17 students, who underwent a structured process consisting of a pre-test, material delivery, hands-on practice of creating simple animations, and a post-test. The learning materials included an introduction to the Scratch interface, how to use sprites, and basic coding blocks to develop simple animation projects. The evaluation results indicated a significant increase in students' understanding of basic programming concepts. The majority of participants successfully created simple animation projects using coding blocks and sprites, demonstrating their ability to apply the learned concepts. The students showed high enthusiasm throughout the learning process, indicating a strong interest in digital learning and coding. The high level of engagement further supports the potential for expanding similar programs in the future. This community service activity proved effective in introducing computational thinking and fostering creativity among elementary school students. It also demonstrated the effectiveness of interactive and hands-on learning approaches in enhancing students' digital literacy. As a result, this program has the potential to be implemented in other schools to promote early exposure to programming and support the development of digital skills among young learners
OPTIMASI MODEL U-NET BACKBONE RESNET50 PADA SEGMENTASI CITRA BANJIR MENGGUNAKAN SEQUENTIAL HYPERPARAMETER TUNING Moh Adzka Fawaid; Ricardus Anggi Pramunendar; Nurul Anisa Sri Winarsih; Muhammad Syaifur Rohman; Danny Oka Ratmana
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7377

Abstract

Flooding is a natural disaster that has become increasingly frequent and causes significant impacts on urban environments, highlighting the need for rapid and accurate mapping of affected areas. Deep learning–based image segmentation, particularly using the U-Net architecture, has been widely applied for this purpose. However, model performance is not determined solely by network architecture, but is also strongly influenced by the selection of training hyperparameters. This study aims to optimize the performance of a U-Net model with a ResNet50 backbone for flood image segmentation using a Sequential Hyperparameter Tuning approach based on a one-factor-at-a-time scheme. The dataset consists of approximately 3,400 RGB flood images with corresponding binary ground truth masks at an original resolution of 512 × 512 pixels, which are resized to 256 × 256 pixels and preprocessed using CLAHE, gamma correction, and unsharp masking to enhance contrast and boundary clarity of inundated areas. The optimization focuses on optimizer selection, batch size, learning rate, and number of training epochs, as these parameters directly affect convergence stability and segmentation accuracy. Hyperparameter tuning is performed sequentially by evaluating model performance on the validation set using Intersection over Union (IoU) and Dice Similarity Coefficient. Based on this process, the optimal configuration employs the AdamW optimizer, a batch size of 8, a learning rate of 0.00015, and 100 training epochs. Final evaluation is conducted on the test set through retraining with three different random seeds, and performance is reported using mean values. The optimized model achieves a mean IoU of 0.7664 and a mean Dice score of 0.8499, with low standard deviation, indicating stable performance and good generalization capability. These findings demonstrate that systematic hyperparameter optimization plays a crucial role in improving the performance of U-Net ResNet50 for flood image segmentation and provides practical insights for remote sensing–based flood mapping systems.
Co-Authors Adhitya Nugraha Filmada Ocky Saputra Moh Adzka Fawaid Muhammad Syaifur Rohman Naufal Fawwazi Ricardus Anggi Pramunendar Rohman, Muhammad Syaifur Saraswati, Galuh Wilujeng Winarsih, Nurul Anisa Sri Yani Parti Astuti