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All Journal Agrin : Jurnal Penelitian Pertanian Jurnal Teknologi dan Riset Terapan (JATRA) Spizaetus: Jurnal Biologi dan Pendidikan Biologi kawanad Jurnal Polimesin Forest and Nature
Dirhamsyah, Muhammad
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Immunology & microbiology Materials Science & Nanotechnology Mechanical Engineering Other

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Journal : Jurnal Polimesin

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Visual place recognition for autonomous mobile robot navigation using LoFTR and MAGSAC++ Aulia, Udink; Hasanuddin, Iskandar; Dirhamsyah, Muhammad; Nasaruddin, Nasaruddin
Jurnal Polimesin Vol 22, No 2 (2024): April
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v22i2.4992

Abstract

Autonomous mobile robots are defined as robotic entities capable of independent movement and intelligent decision-making, relying on their ability to perceive and analyze their surroundings, including objects in their environment. In Simultaneous Localization and Mapping (SLAM) systems, loop closure is often achieved through visual place recognition techniques, where the system compares the current visual input with previously observed scenes to identify matches. In computer vision applications, Speeded-Up Robust Features (SURF) and Scale-Invariant Feature Transform (SIFT) are popular feature extraction algorithms used for such as key point detection, matching, and image registration tasks. The choice of inlier threshold should be based on the specific characteristics of the application and the nature of the images being processed. It often requires experimentation and tuning to find the optimal balance between robustness and accuracy. It Utilizes the pre-trained Local Feature Transformer (LoFTR) and MAGSAC++ estimator to address these drawbacks by employing the number of inliers to determine the similarity between two images for visual place recognition. Our experiment demonstrates that the number of inliers can determine the similarity of locations between two images. Scale variations and translation in location significantly influence the resulting number of inliers. Comparing images from the same location and from different locations yields varying numbers of inliers. The number of inliers significantly influences the similarity of locations. At the same location, the number of inliers is above 150, while at different locations, the number is below 150.
Effect of Perforated Aluminum on Calotropis Gigantea Fiber Material’s Ability to Absorption Sound suhaeri, suhaeri; Husaini, Husaini; Dirhamsyah, Muhammad; Hasanuddin, Iskandar
Jurnal Polimesin Vol 22, No 4 (2024): August
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v22i4.5245

Abstract

Plants fibers such as Calotropis gigantea (CG) are very suitable as noise reduction material. Therefore, this research aims to determine the sound absorption coefficient of CG in the 20 mm test sample and the effect of the perforated aluminum layer on its ability. It was carried out using a test sample made with a thickness of 20 mm and 100 mm in diameter. The thickness of aluminum was 0.3 mm with hole diameters of 1 mm, 1.5 mm, and 2.5 mm. During the experiment, every sample was heated and pressed in a mold for 10 minutes at 200oC. The test equipment used is a Bruel Kjaer Type 4206 impedance tube with 100 mm in diameter. The sample was tested using the transfer function method ISO 10534-2:1998 at a frequency of 1/1 octave. The results indicated that the uncoated sample absorbed noise α = 0.01-0.07 (1-7)% higher than the sample coated with perforated aluminum. This showed that the Noise Reduction Coefficient (NRC) without aluminum coating can reduce noise by 29%, and the measured sample is categorized in class D.
Effect of Scirpus grossus fiber density on acoustic absorption characteristics for insulation use Suhaeri, Suhaeri; Husaini, Husaini; Dirhamsyah, Muhammad; Hasanuddin, Iskandar; Tajuddin, Tajuddin
Jurnal Polimesin Vol 23, No 3 (2025): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v23i3.7012

Abstract

Noise control is essential for achieving comfortable living and working environments. Natural fibers such as Scirpus Grossus offer a sustainable approach for sound absorption applications. This study investigates the effect of varying fiber densities of Scirpus grossus on sound absorption performance. Test specimens were fabricated at three density levels; 636.9 kg/³, 318.5 kg/m³, and 212.3 kg/m³. Each had a fixed mass of 50 grams, a diameter of 100 mm, and varying thicknesses of 10 mm, 20 mm, and 30 mm. The samples were hot-pressed at 200°C for 10 minutes. Sound absorption coefficients (SACs) were measured using a Brüel Kjær Impedance Tube Type 4206, following the transfer function method (ISO 10534-2:1998) over third-octave bands. The results show that fiber density significantly affects the sound absorption coefficient (SAC). A decrease in density to 212.3 kg/m³ led to a SAC increase of 0.12 points (approximately 20% relative to the initial SAC value of 0.5428 at 636.9 kg/m³), particularly at 4000 Hz. This indicates that lower-density samples exhibit better acoustic absorption behavior. The average Noise Reduction Coefficient (NRC) across all samples was around 45%, confirming their effectiveness in sound control. Based on SAC values, the samples are classified as Sound Absorption Class D. These findings suggest that Scirpus grossus fiber mats have strong potential for eco-friendly acoustic insulation materials, suitable for applications in building panels or vehicle interiors.
Co-Authors ahmad yani Alkhadi Azwar Calaudianus Feri, Yosep Dina Setyawati Farah Diba Fathul Yusro Hasan Ashari Oramahi Hasanuddin, Iskandar Husaini Husaini Jamil, M. Mahmud Masri Ibrahim Muhammad Riski, Muhammad Muslimsyah Nasaruddin Nasaruddin Novandri, Andri Nurhaida Nurhaida Putra, T. Edisah Samsul Bahri Sariyusda Suhaeri Suhaeri, Suhaeri Tajuddin Tajuddin, Tajuddin Udink Aulia Wahdina, Wahdina Yanti Hikma Yeni Mariani Yuwaldi Away Zulfadli