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All Journal Momentum: Physics Education Journal Jurnal INFOTEL
Samsuryadi Samsuryadi
Universitas Sriwijaya, Indonesia
Computer Science & IT Electrical & Electronics Engineering Physics

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Improving the Accuracy of Concrete Mix Type Recognition with ANN and GLCM Features Based on Image Resolution Gasim Gasim; Rudi Heriansyah; Shinta Puspasari; Muhammad Haviz Irfani; Evi Purnamasari; Indah Permatasari; Samsuryadi Samsuryadi
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1201

Abstract

Concrete is an essential construction material that is often used due to its strength and durability, but its mix type identification often relies on conventional methods that are less efficient and accurate. This research aims to evaluate the effect of image resolution on the accuracy of concrete mix type recognition using Artificial Neural Network (ANN) and Gray-Level Co-Occurrence Matrix (GLCM) features. The method used involves analysing concrete images at various resolutions: 200 x 200, 300 x 300, 400 x 400, 500 x 500, 600 x 600, and 700 x 700 pixels. The experimental results show that higher image resolutions tend to improve recognition accuracy. all types of image sizes using 1,250 training data and 250 test data. Image sizes of 200 x 200 and 300 x 300 pixels give low accuracy of 42% and 45% respectively, while sizes of 400 x 400 and 500 x 500 pixels show an increase in accuracy to 60.5% and 62.5%. The higher resolutions of 600 x 600 and 700 x 700 pixels produced the highest accuracy of 68% and 70%, respectively. These results indicate that larger image resolutions are able to capture more details and characteristics required for more accurate concrete mix type recognition. This research has implications for improving efficiency and consistency in concrete inspection in the construction industry through the use of AI-based image recognition methods.
Developing Mobile Learning of Physics (MOBLEP) with android-based problem-based learning approach to improve students’ learning independence Apit Fathurohman; Murniati Murniati; Sukemi Sukemi; Esti Susiloningsih; Erni Erni; Lintang Auliya Kurdiati; Samsuryadi Samsuryadi
Momentum: Physics Education Journal Vol. 7 No. 1 (2023)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/mpej.v7i1.7980

Abstract

This development research aims to produce Mobile Learning of Physics (Moblep) by applying Android-based Problem Based Learning Approach to Increase Student Learning Independence which is valid and practical. The development model used is the Rowntree model modified with Tessmer's formative evaluation method. The tessmer's formative evaluation stages in this study include self-evaluation, expert review, one-to-one, and small group. At the expert review stage, data were collected through interviews, expert tests, and questionnaires using nine material experts, nine design experts, and eleven language experts. The one-to-one stage and the small group stage were carried out at SMA Negeri 1 Suak Tapeh. The results showed that the Mobile Learning of Physics (Moblep) with the Android-based Problem-Based Learning Approach that was developed, based on the results of the expert review, obtained a total percentage score of 94.73% from the validator and was included in the "very valid" category. Based on the results of the student response questionnaire at the one-to-one evaluation stage, the average percentage was 83.5%, and at the small group stage, the average percentage was 95.2%, so this Moblep was included in the "very practical" category.The implication of this research is that the results of this study can be applied as reference material and considered as additional references for further research.
Co-Authors Apit Fathurohman Erni Erni Esti Susiloningsih Evi Purnamasari Gasim Indah Permatasari Lintang Auliya Kurdiati Muhammad Haviz Irfani Murniati . Rudi Heriansyah Shinta Puspasari Sukemi Sukemi