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All Journal ComEngApp : Computer Engineering and Applications Journal ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Indonesian Journal of Information System Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Nasional Teknik Elektro dan Teknologi Informasi
MUHAMMAD KHAERUL NAIM MURSALIM
Program Studi Teknik Telekomunikasi Universitas Universal
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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ANALISIS PERBANDINGAN KINERJA METODE SUPERPIXEL DAN GRADIEN BERBASIS EDGE DETECTOR PADA PENDETEKSIAN OBJEK BERGERAK MURSALIM, MUHAMMAD KHAERUL NAIM; VERDIAN, IHSAN
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 8, No 2 (2020): ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektro
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v8i2.362

Abstract

ABSTRAKSalah satu bagian dalam algoritma pemrosesan citra adalah proses segmentasi yang menjadi tahap pra-pemrosesan untuk ekstraksi fitur objek. Superpixel menjadi salah satu solusi pada proses segmentasi dengan mendefenisikan kumpulan piksel yang mempunyai kesamaan karekterisitik sehingga membawa banyak informasi mengenai fitur objek. Adapun tantangan yang dihadapi dalam mendeteksi objek bergerak adalah ketidakmampuan untuk memisahkan objek bergerak dari background objek. Sehingga, pada citra yang dideteksi akan dikelilingi oleh wilayah yang terdapat derau. Pada penelitian ini, diusulkan metode superpixel berbasis deteksi tepi untuk mendeteksi objek bergerak. Selanjutnya, kinerja metode superpixel diuji dengan membandingkan dengan metode deteksi tepi yang berbasis gradient. Hasilnya menunjukkan bahwa metode yang diusulkan mampu meminimalisir derau lebih baik dan hasil perhitungan MSE, RMSE, dan PSNR hanya berbeda 0.06% dan 0.1% dari metode Sobel dan Prewitt.Kata kunci: Deteksi tepi, Objek bergerak, Proses Segmentasi, Superpixel ABSTRACTOne part of the image processing is the segmentation which becomes the preprocessing stage for feature extraction. Superpixel becomes solutions in the segmentation process by defining a collection of pixels that have the same characteristics ang bringing the information about the object's features. The challenge faced in detecting moving objects is the inability to separate moving objects from the object's background. Thus, the detected image will be surrounded by an area with noise. In this study, a superpixel-based edge detection method is proposed to detect moving objects. Furthermore, the performance of the superpixel method is tested by comparing it to the gradient-based edge detection method. The results show that the proposed method is able to minimize noise better and the results of MSE, RMSE, and PSNR calculations differ only 0.06% and 0.1% from the Sobel and Prewitt methods.Keywords: Edge detection, Moving objects, Segmentation, Superpixels
Detection of Vessel on UAV based on Segmentation Using Edge Based Dilation Muhammad Khaerul Naim Mursalim; Noor Falih
Computer Engineering and Applications Journal Vol 7 No 2 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (718.854 KB) | DOI: 10.18495/comengapp.v7i2.256

Abstract

UAV usually is used in military field for reconnaissance, surveillance, and assault. To detect a moving object in real-time like vessel, there are complex processes than to detect the object that does not moving. There are some issues that faced in detection process of moving object in UAV, called constraint uncertainty factor (UCF) such as environment, type of object, illumination, camera of UAV, and motion. One of the practical problems that become concern of researchers in the past few years is motion analysis. Motion of an object in each frame carries a lot of information about the pixels of moving objects which has an important role as the image descriptor. In this paper, we use SUED (Segmentation using edge-based dilation) algorithm to detect vessel. The concept of the SUED algorithm is combining the frame difference and segmentation process to obtain optimal results. This research showed that the SUED method having problem to detect the vessel even though we combine it with sobel operator. using the combination of wavelet and Sobel operator on the detection of edges obtained increasing in the number of DR about 3%, but then FAR also increased from 41.23% to 52.09%.
Pendeteksian dan Pelacakan Objek Bergerak pada UAV berbasis Metode SUED Muhammad Khaerul Naim Mursalim Mail
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 1: Februari 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1541.165 KB)

Abstract

An unmanned aerial vehicle (UAV), commonly known as a drone, could be utilized to detect a moving object in real-time. However, there are some issues in detection process of moving object in UAV, called constraint uncertainty factor (UCF), such as environment, type of object, illumination, camera of UAV, and motion. One of practical problems that become concern of researcher in the past few years is motion analysis. Motion of an object in each frame carries a lot of information about the pixels of moving objects which has an important role as the image descriptor. In this paper, segmentation using edgebased dilation (SUED) algorithm is used to detect moving objects. The concept of the SUED algorithm is combining frame difference and segmentation process to obtain optimal results. The simulation results show the performance improvement of SUED algorithm using combination of wavelet and Sobel operator on edge detection: the number of frames for a true positive increased by 41 frames, then the false alarm rate decreased to 7% from 24% when only using Sobel operator. The combination of these two methods can also minimize noise region that affect detection and tracking process. The simulation results for tracking moving objects by Kalman filter show that there is decreasing of error between detection and tracking process.
Sosialisasi Internet of Things dan Multimedia Sebagai Peluang Karir di Bidang Teknologi KH, Musliadi; Kaharuddin, Kaharuddin; Mursalim, Muhammad Khaerul Naim
Reswara: Jurnal Pengabdian Kepada Masyarakat Vol 6, No 2 (2025)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v6i2.6632

Abstract

Perkembangan teknologi informasi yang pesat telah membuka berbagai peluang karier baru, khususnya di bidang Internet of Things (IoT) dan multimedia. Namun, kurangnya pemahaman generasi muda terhadap potensi karier di bidang tersebut menjadi kendala dalam menyiapkan sumber daya manusia yang adaptif terhadap era digital. Kegiatan pengabdian masyarakat ini bertujuan untuk memberikan sosialisasi dan edukasi mengenai konsep dasar, penerapan, serta peluang karier dalam bidang IoT dan multimedia kepada siswa di salah satu SMK Swasta di kota Batam sehingga mereka berminat untuk melanjutkan studi dengan mengambil jurusan komputer. Metode yang digunakan dalam kegiatan ini meliputi ceramah interaktif, demonstrasi teknologi, dan diskusi kelompok untuk meningkatkan partisipasi dan pemahaman peserta. Hasil dari kegiatan ini menunjukkan peningkatan signifikan pada seluruh aspek yang diukur. Berdasarkan angket (kuesioner) dengan menggunakan penilaian skala Likert 5, di mana rata-rata skor pemahaman tentang IoT dari angket yang diberikan meningkat dari 2,1 menjadi 4,2, pemahaman multimedia dari 2,5 menjadi 4,4, minat terhadap karier teknologi dari 3,0 menjadi 4,5, dan keyakinan melanjutkan studi di bidang teknologi dari 2,8 menjadi 4,3. Temuan ini menunjukkan bahwa kegiatan sosialisasi dan pelatihan yang dirancang secara kontekstual dan interaktif mampu memberikan dampak positif dalam membentuk persepsi serta motivasi pelajar terhadap karier di bidang teknologi. Kegiatan ini diharapkan dapat menjadi model pembinaan karier berbasis teknologi di tingkat pendidikan menengah yang mendukung pengembangan ekosistem digital nasional secara berkelanjutan.
Coral Detection based on Optimised Lightweight YOLO Model Saragih, Raymond Erz; Husin, Husna Sarirah; Mursalim, Muhammad Khairul Naim; Yodi
Indonesian Journal of Information Systems Vol. 8 No. 1 (2025): August 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v8i1.11628

Abstract

Coral reefs are essential marine ecosystems that face significant threats due to climate change, pollution, and overfishing. Effective monitoring is crucial for conservation efforts, but traditional methods are labor-intensive and inefficient. This study proposes a deep learning-based coral detection model built based on the YOLOv8 architecture, specifically for nano and small. In addition, the Ghost modules and Ghost bottlenecks were utilized to modify the original YOLOv8 small. The proposed model was trained on an underwater coral dataset and evaluated in terms of precision, recall, and mean Average Precision (mAP) metrics. Experimental results demonstrate that the YOLOv8 small model and YOLOv8 small model with Ghost modules achieved a mAP of 53.675% and 55.88%, respectively, while maintaining a compact model size. This work contributes to developing efficient and lightweight coral detection systems to support conservation efforts.
Co-Authors Husin, Husna Sarirah Kaharuddin Musliadi K H Noor Falih Saragih, Raymond Erz Verdian, Ihsan Yodi