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All Journal Jurnal Informatika Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Ekonomi Manajemen Sistem Informasi International Journal of Multidisciplinary Approach Research and Science
Fauzi, Esa
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Economics, Econometrics & Finance Immunology & microbiology Social Sciences

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Pengembangan dan Pendampingan Aplikasi Absensi QR Code Untuk Monitoring Kehadiran Guru di SD Muhammadiyah Calingcing Prasetyo, Bagus Alit; Purnama, Adi; Rahman, Atep Aulia; Fauzi, Esa
Jurnal Ekonomi Manajemen Sistem Informasi Vol. 6 No. 3 (2025): Jurnal Ekonomi Manajemen Sistem Informasi (Januari - Februari 2025)
Publisher : Dinasti Review

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jemsi.v6i3.3842

Abstract

Proses absensi guru di SD Muhammadiyah Calingcing masih dilakukan secara manual dengan mencatat kehadiran pada buku absensi. Untuk mengatasi permasalahan tersebut, dirancang dan diimplementasikan aplikasi absensi berbasis QR Code. Sistem ini melibatkan dua platform utama, yaitu aplikasi mobile untuk guru yang digunakan dalam pemindaian QR Code guna mencatat kehadiran, dan aplikasi berbasis web untuk pemantauan dan pembuatan laporan otomatis oleh kepala sekolah atau staf administrasi. Tahapan kegiatan meliputi konsultasi untuk memetakan kebutuhan, pengembangan aplikasi yang melibatkan integrasi melalui RESTful API, dan simulasi ilmu pengetahuan dan teknologi melalui pelatihan penggunaan serta uji coba sistem secara langsung. Hasil kegiatan menunjukkan bahwa sistem ini berhasil meningkatkan efisiensi, akurasi, dan kemudahan dalam pengelolaan kehadiran guru. Dampak positifnya meliputi digitalisasi proses absensi, penguatan kapasitas teknologi bagi pengguna, dan kemudahan Pemantauan real-time, yang mendukung transformasi digital di sektor pendidikan. Sistem ini juga memberikan peluang untuk dikembangkan lebih lanjut, seperti integrasi dengan sistem manajemen sekolah yang lebih luas. Kegiatan ini tidak hanya memberikan solusi teknologi yang strategis untuk kebutuhan sekolah tetapi juga memberikan kontribusi pada penguatan sektor riil masyarakat melalui penerapan teknologi modern yang relevan dengan perkembangan zaman.
Implementing PSO-based Image Segmentation for Detecting Sweet Potato Leaf Disease Purnama, Adi; Fauzi, Esa; Prasetyo, Bagus Alit
International Journal of Multidisciplinary Approach Research and Science Том 3 № 02 (2025): International Journal of Multidisciplinary Approach Research and Science
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/ijmars.v3i02.1482

Abstract

Sweet potato (Ipomoea batatas) is an important global crop, but its production is threatened by various leaf diseases, requiring accurate and efficient disease detection methods. Traditional manual inspection is labor-intensive and error-prone, making automated image processing techniques a promising alternative. This study implements Particle Swarm Optimization (PSO)-based image segmentation to detect diseased leaf regions by optimizing threshold selection in HSV color space. In the classification phase, leaves are classified into healthy and diseased classes using a Euclidean distance-based classifier. The proposed method achieved an average classification accuracy of 88.1%, with an accuracy of 95.8% for diseased leaves and 80.4% for healthy leaves, demonstrating its effectiveness in discriminating infected regions. The results confirm that PSO is a robust and efficient segmentation technique that improves the accuracy of disease detection. This research highlights the potential of PSO-based segmentation in smart agriculture, enabling early disease detection to help farmers take timely action and minimize crop losses. Compared to traditional methods, PSO reduces computational complexity while maintaining high segmentation accuracy, making it a valuable tool for agricultural disease monitoring. Future work can integrate deep learning models to refine disease classification and expand datasets to improve system performance under different environmental conditions.
Analisa Kasus Covid-19 Menggunakan Metode Agglomerative Hierarchical Clustering pada Tingkat Kematian Nurlaila; Fauzi, Esa
Jurnal Informatika Vol 24 No 2 (2024): Jurnal Informatika
Publisher : Institut Informatika Dan Bisnis Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v24i2.427

Abstract

Coronavirus disease was first discovered in the city of Wuhan, China in December 2019. Due to the impact of the new coronavirus infection, many infected patients have died including in the United States. Data obtained from the official web of Data Centers for Disease Control and Prevention shows a high mortality rate due to Covid-19. This study aims to analyze the Covid-19 mortality rate by region using the Agglomerative Hierarchical Clustering (AHC) method and find the optimal cluster validity using the Silhouette Index (SI) method. Clustering the Covid-19 death rate using the AHC method is needed to understand the pattern of death rates due to Covid-19 and assist in making policies for pandemic prevention and handling. This research resulted in the optimal number of clusters at n clusters = 2 with cluster-1 high mortality rate of 12,307 object and cluster-2 low mortality rate of 13,498 object. The results of this study can thoroughly analyze Covid-19 death data such as revealing some important findings and input that can be proposed to improve the quality of response to future pandemics.
Evaluation of Use of Linear Regression to Predict Profit, Selling Price, and Stock on HSR Wheels Platform Fauzi, Esa; Prasetyo, Bagus Alit; Purnama, Adi; Pangestu, Rizky Bagus
International Journal of Multidisciplinary Approach Research and Science Том 3 № 03 (2025): International Journal of Multidisciplinary Approach Research and Science
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/ijmars.v3i03.1967

Abstract

In the ever-evolving digital era, the e-commerce sector faces significant challenges in efficiently managing sales, selling prices, and inventory. This study aims to evaluate the effectiveness of a linear regression model in predicting sales, selling prices, and stock levels on the HSR Wheels e-commerce platform. A quantitative method was used by analyzing daily transaction data to identify the relationship between the time variable and sales, profit, and stock. The results showed that linear regression has limitations in modeling data complexity, with low R² scores and high Mean Absolute Error (MAE) values. These findings indicate the need for more advanced predictive models, such as machine learning algorithms, to improve prediction accuracy. This research is expected to contribute to developing more efficient and relevant sales strategies for e-commerce platforms.
Implementasi Sistem Informasi Zis Berbasis Web Untuk Transparansi Di Masjid Al-Ikhlas Bandung Rahman, Atep Aulia; Purnama, Adi; Indriani; Prasetyo, Bagus Alit; Fauzi, Esa; Kusramdani, Rizky; Candimadam; Tumaruk, Andry Septian Syahputra
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 8 No. 4 (2025): Oktober 2025
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v8i4.3923

Abstract

Abstract: This community service activity aims to improve the transparency and efficiency of zakat, infaq, and shadaqah (ZIS) management at Al-Ikhlas Mosque, Bandung Regency, through the implementation of a web-based information system. The main problem faced by the partner was the manual and unstructured recording and reporting process, as well as the low accessibility of information for congregants. The methods used included consultation to identify needs, science and technology substitution to implement modern systems, and technical training for mosque administrators. The results showed that the administrators were able to operate the system independently, with a level of understanding reaching 93.5% with an average evaluation score of 3.74 out of 4. The developed information system supports transaction recording, financial reporting, and transparent ZIS fund distribution. Additionally, the activity produced outputs in the form of a web application, digital training modules, and technical documentation that can be used sustainably. This program contributes significantly to strengthening accountability and congregational engagement in religious social fund management. Keywords: accountability; information system; training; web application; zakat Abstrak: Kegiatan pengabdian ini bertujuan untuk meningkatkan transparansi dan efisiensi pengelolaan zakat, infaq, dan shadaqah (ZIS) di Masjid Al-Ikhlas Kab. Bandung melalui implementasi sistem informasi berbasis website. Masalah utama yang dihadapi mitra adalah proses pencatatan dan pelaporan manual yang tidak terstruktur serta rendahnya akses informasi bagi jamaah. Metode yang digunakan meliputi konsultasi untuk identifikasi kebutuhan, substitusi ipteks untuk penerapan teknologi, serta pelatihan teknis untuk pengurus masjid. Hasil kegiatan menunjukkan bahwa pengurus masjid mampu mengoperasikan sistem secara mandiri dengan tingkat pemahaman mencapai 93.5% dengan skor rata-rata evaluasi sebesar 3.74 dari 4. Sistem informasi yang dikembangkan mendukung pencatatan transaksi, pelaporan keuangan, serta transparansi distribusi dana ZIS. Selain itu, kegiatan ini menghasilkan luaran berupa aplikasi web, modul pelatihan digital, dan dokumentasi teknis yang dapat digunakan secara berkelanjutan. Kegiatan ini memberikan kontribusi nyata dalam memperkuat akuntabilitas dan keterlibatan jamaah dalam pengelolaan dana sosial keagamaan. Kata kunci: akuntabilitas; aplikasi web; pelatihan; sistem informasi; zakat
Co-Authors Adi Purnama Bagus Alit Prasetyo Candimadam Indriani Kusramdani, Rizky Nurlaila Pangestu, Rizky Bagus Rahman, Atep Aulia Tumaruk, Andry Septian Syahputra