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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) MEDIA KOMUNIKASI TEKNIK SIPIL Jurnal Sains dan Teknologi Jurnal Informatika Jurnal Teknik Sipil dan Perencanaan APTEK Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Journal of Degraded and Mining Lands Management Rekayasa Sipil Proceedings ACES (Annual Civil Engineering Seminar) Fondasi: Jurnal Teknik Sipil Jurnal Teknik Sipil Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Journal of Geoscience, Engineering, Environment, and Technology Teras Jurnal International Journal of Artificial Intelligence Research Journal of the Civil Engineering Forum SIKLUS: Jurnal Teknik Sipil Jurnal Rekayasa Sipil Astonjadro Jurnal Infrastruktur Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Pelita Masyarakat IGKOJEI: Jurnal Pengabdian Masyarakat Civil Engineering Collaboration Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Makara Journal of Technology J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal Jalan Jembatan
Soewignjo Agus Nugroho
Universitas Riau
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Social Sciences Transportation Veterinary

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Journal : Journal of Geoscience, Engineering, Environment, and Technology

 1 
Water and Reinforced Effects on Slope: Case Study on District Koto Panjang, Riau, Indonesia Nugroho, Soewignjo Agus; Yusa, Muhamad; Sujatmoko, Bambang; Ongko, Andarsin
Journal of Geoscience, Engineering, Environment, and Technology Vol. 9 No. 2 (2024): JGEET Vol 09 No 02 : June (2024)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2024.9.2.12604

Abstract

This paper discussed a study case related to slope stability and its analysis. The observation and also research object was a hill side on border area between West Sumatera-Riau, Indonesia. This border area consists of numerous slopes with heterogeneous soil characteristics. This location is also susceptible for having landslides, especially on rainy season. The schemes of this research consisted of collecting samples, laboratory tests, finite element method analysis, and slope`s reinforcement planning with anchors or geosynthetic plates. The soil samples were tested on their actual condition and liquid limit condition. This purposed to predict the failures on slope. Afterwards, some reinforcement plannings need to be done. The results of this researach have shown that on existing condition, the safety factor was 1.262. If the soil reach its liquid limit, the safety factor decreased to 0.568. After the reinforcement planning was done, the safety factor went up to 1.120 and the slope stability could be maintained.
Sensitivity Analysis Based on Physical Properties to Permeability Coefficient of Cohesive Soil Using Artificial Neural Network Fatnanta, Ferry; Suprayogi, Imam; Nugroho, Soewignjo Agus; Satibi, Syawal; Saputra, Riola
Journal of Geoscience, Engineering, Environment, and Technology Vol. 9 No. 1 (2024): JGEET Vol 09 No 01 : March (2024)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2024.9.1.13536

Abstract

Permeability is the ability of a soil to allow liquids to pass through. Of course the soil has a physical characteristic that can be known by laboratory testing. This study aims to determine the physical properties that most affect the coefficient of cohesive soil permeability using the Artificial Neural Network (ANN) tool, the results obtained will later be matched with actual conditions according to the context of engineering geology. The research method begins with an influence or sensitivity analysis using ANN which will produce a correlation coefficient (R). Then, these results will be compared with the influence analysis based on the value of the coefficient of determination (R2). After that, accuracy and error tests will be carried out using the Mean Absolute Percentage Error (MAPE), the highest accuracy values is categorized as the most influential physical property of the 7 physical property parameters, namely liquid limit, plastic limit, plasticity index, %sand, %fines, %silt, and %clay. Based on the result of the analysis, %fines is the parameter that most influences permeability and is able to make very strong predictions with an R value using an ANN of 0.9941875, an R2 value of 0.6336, an accuracy of 99.6962%, and a MAPE of 0.3038%. These results are compared with the existing empirical equations with an accuracy of 96.4393% and MAPE of 3.5607%. It can be concluded that ANN is more effective and optimal in making predictions. In this case, in the context of engineering geology, the more %fines, the smaller the permeability coefficient of the soil.
Correlation of CBR Values and Mackintosh Probe on Clay Soil with Variations of Bentonite, Kaolin and Sand Nugroho, Soewignjo Agus; Fatnanta, Ferry; Wibisono, Gunawan; Muliyono
Journal of Geoscience, Engineering, Environment, and Technology Vol. 10 No. 4 (2025): JGEET Vol 10 No 04 : December (2025)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2025.10.4.24252

Abstract

Coastal areas are typically characterized by non-uniform soil properties, often featuring soft, water-saturated soils with high plasticity, which frequently results in low soil bearing capacity. This study aims to investigate the relationship between California Bearing Ratio (CBR) values and Mackintosh Probe (MP) test results by utilizing a mixture of clay soil comprising bentonite and kaolin with sand in various compositions. These mixtures were prepared as laboratory test samples to simulate the soil conditions in these areas. The primary objective of this research is to develop a faster and more efficient alternative method for estimating soil bearing capacity in coastal regions. A total of 81 samples were prepared with variations in moisture content, compaction levels, and the composition of sand and clay mixtures. Testing was conducted using both CBR and MP methods. The analysis revealed a significant positive correlation between MP and CBR values, represented by the linear regression model: CBR = 0.7498 * MP, with a coefficient of determination (R²) of 0.9542. This indicates that approximately 95.42% of the variation in CBR values can be predicted from the MP test results. The model's accuracy was further validated through training and testing using 5 randomly selected data points from the sample set. The findings suggest that the Mackintosh Probe can serve as a preliminary tool for estimating soil bearing capacity in coastal areas, particularly in field conditions where laboratory equipment is limited. However, for broader applicability, further validation of this model is necessary to accommodate more complex soil conditions in the field.
Co-Authors ', Muhardi Aditia Siringoringo Adnan Ruziq Ihsan Agus Ika Putra Agus Ika Putra Al Ridho, Muhammad Faisal Alridho, Muhammad Faizal Andarsin Ongko Andius Dasa Putra Ari S. Sibarani Ari S. Sibarani Ari Sandhyavitri Ari Sandhyavitri Arie S Sibarani Arie S Sibarani Arisman Adnan Avrilly Zesthree Mauliza Azra Zulnasari Bahrul Junaidi Bambang Sujatmoko Enno Yuniarto Erik Azarya Ginting Ermiyati Ermiyati Ermiyati, Ermiyati Fadhilah, Randy Fajar Restuhadi Fakhri, Fakhri Fauzi, Manyuk Febrizal Ujang Fernando, Hendra Ferry Fatnanta Fikri Hidayat Giri Prayoga Gunawan Wibisono Gunawan Wibisono Gussyafri Hendra Fernando Ihsan, Adnan Ruziq Imam Suprayogi Inna Kurniati Inna Kurniati, Inna Irfan Hasan Jamili, M Joehari K Khairat Khairat, K Khairatu Zaro Khairul Umam Kikumoto, Mamoru Koichi Yamamoto, Koichi Lala Monang Robert Christian Zega Lala Monang Robert Christian Zega Zega Lembasi, Muhammad Khadafi Lingga Panji Subrata, Lingga Panji Lita Darmayanti M Faizal Alridho M. Shoffar Al Hafizh M. Yusuf Agustamar Mohammad Saeri Monita Olivia Muhamad Yusa Muhammad Khadafi Lembasi Muhammad Muhshi Muhammad Saeri, Muhammad Muhammad Yusa Muhardi Muhardi Muhardi Muliyono Novan, Andre Nurdin Nurdin Ongko, Andarsin Prayogo, Giri Puspa Ningrum Raflyatullah Raflyatullah Raflyatullah, Raflyatullah Ranata, Nicola Rabb Randhi Saily Reni Suryanita Rian Trikomara Iriana Rinaldi Rinaldi Rofika Ratna Ardiansyah Roni Indra Lesmana Rosma, Iswadi Hasyim Rudy Suryadi, Rudy Rugun Ermina S. Siswanto S. Siswanto Safridatul Audah Saputra, Riola Satibi, Syawal Satria, Zoni Sayoga, Davin Sutikno, Sigit Syamsu Herman Syamsu Herman Syamsul Arifin Unzi Marwan Usman, Fauzan Wulandari, Deny Yohanna Lilis H Zega, Christian Robert Zoni Satria Zulkifli Zulkifli Zulnasari, Azra