PERTANIKA JOURNAL OF SOCIAL SCIENCES AND HUMANITIES

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• Alnaimat, A., Choy, L. K., & Jaafar, M. (2017). An assessment of current practices on landslides risk management: A Case of Kuala Lumpur Territory. Geografia, 13(2), 1-12.

• Althuwaynee, O. F., & Pradhan, B. (2017). Semi-quantitative landslide risk assessment using GIS-based exposure analysis in Kuala Lumpur City. Geomatics, Natural Hazards and Risk, 8(2), 706-732. https://doi.org/10.1080/19475705.2016.1255670

• Capitani, M., Ribolini, A., & Bini, M. (2013). The slope aspect: A predisposing factor for landsliding? Comptes Rendus Geoscience, 345(11-12), 427-438. https://doi.org/10.1016/j.crte.2013.11.002

• Department of Irrigation and Drainage. (2018). Laporan banjir tahunan 2017/2018 [Annual flood report 2017/2018]. Ministry of Natural Resources, Environment and Climate Change. http://h2o.water.gov.my/man_hp1/LBT2017-2018.pdf

• Department of Statistics Malaysia. (2020). Lateststatistics 2019. Prime Minister’s Department. https://www.mycensus.gov.my/

• Department of Statistics Malaysia. (2022). Malaysia current population estimates, 2021. Prime Minister’s Department. https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=155&bul_id=ZjJOSnpJR21sQWVUcUp6ODRudm5JZz09&menu_id=L0pheU43NWJwRWVSZklWdzQ4TlhUUT09#:~:text=Kuala%20Lumpur%20had%20the%20highest,1%2C691%20people)%20per%20square%20kilometre.

• Dhianaufal, D., Kristyanto, T. H. W., Indra, T. L., & Syahputra, R. (2018). Fuzzy logic method for landslide susceptibility mapping in volcanic sediment area in Western Bogor. AIP Conference Proceedings 2023, Article 020190. https://doi.org/10.1063/1.5064187

• Erener, A., & Duzgun, H. S. B. (2010). Improvement of statistical landslide susceptibility mapping by using spatial and global regression methods in the case of More and Romsdal (Norway). Landslides, 7, 55-68. https://doi.org/10.1007/s10346-009-0188-x

• Gue, S. S., & Tan, Y. C. (2003, August 19-20). The engineering aspects of hill-site development. [Paper presentation]. Hillside Development–Issues and challenges, Kuala Lumpur, Malaysia.

• Gue, S. S., & Wong, S. Y. (2009, August 26-27). Slope engineering design and construction practice in Malaysia. [Paper presentation]. CIE-IEM Joint Seminar on Geotechnical Engineering, Yilan, Taiwan.

• Hong, L. J., & Hong, K. A. (2016). Flood forecasting for Klang River at Kuala Lumpur using artificial neural networks. International Journal of Hybrid Information Technology, 9(3), 39-60. https://doi.org/10.14257/ijhit.2016.9.3.05

• Huang, H. F., Yi, W., Yi, Q. L., & Zhang, G. D. (2012). Analysis of landslide surface deformation using geographically weighted regression. Advanced Materials Research, 594-597, 2406-2409. https://doi.org/10.4028/www.scientific.net/amr.594-597.2406

• Ibrahim, M. B., Mustaffa, Z., Balogun, A. L., & Sati, H. H. I. (2022). Landslide risk analysis using machine learning principles: A case study of Bukit Antarabangsa landslide incidence. Journal of Hunan University Natural Sciences, 49(5), 112-126. https://doi.org/10.55463/issn.1674-2974.49.5.13

• Ismail, N. I., & Yaacob, W. Z. W. (2018). An investigation of landslides in Bukit Aman and Puncak Setiawangsa, Kuala Lumpur, Malaysia. AIP Conference Proceedings, 1940, Article 020031. https://doi.org/10.1063/1.5027946

• Jaafari, A., Najafi, A., Pourghasemi, H. R., Rezaeian, J., & Sattarian, A. (2014). GIS-based frequency ratio and index of entropy models for landslide susceptibility assessment in the Caspian Forest, Northern Iran. International Journal of Environment Science and Technology, 11, 909-926. https://doi.org/10.1007/s13762-013-0464-0

• Jebur, M. N., Pradhan, B., & Tehrany, M. S. (2014). Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale. Remote Sensing Environment, 152, 150-165. https://doi.org/10.1016/j.rse.2014.05.013

• Kyriou, A., Nikolakopoulos, K., Koukouvelas, I., & Lampropoulou, P. (2021). Repeated UAV campaigns, GNSS measurements, GIS, and petrographic analyses for landslide mapping and monitoring. Minerals, 11(3), Article 300. https://doi.org/10.3390/min11030300

• Lee, S., RyuRyu, J. H., Min, K, & WonWon, J. S. (2003). Landslide susceptibility analysis using GIS and artificial neural network. Earth Surface Processes and Landforms, 28, 1361-1376. https://doi.org/10.1002/esp.593

• Lee, S., & Thalib, J. A. (2005). Probabilistic landslide susceptibility and factor effect analysis. Environmental Geology, 47, 982-990. https://doi.org/10.1007/s00254-005-1228-z

• Mahmud, A. R., Awad, A., & Billa, R. (2013). Landslide susceptibility mapping using averaged weightage score and GIS: A case study at Kuala. Pertanika Journal of Science and Technology, 21(2), 473-486.

• Majid, N. A., & Ibrahim, W. M. M. W. (2015, August 19-20). GIS in studying slope failure in Penang: Challenges and potential [Paper presentation]. Proceedings of International Conference on Development and Socio Spatial Inequalities, Penang, Malaysia.

• Majid, N. A., Rainis, R., & Ibrahim, W. M. M. W. (2017). Pemodelan ruangan pelbagai jenis kegagalan cerun di Pulau Pinang menggunakan kaedah nisbah kekerapan [Spatial modeling of various slope failures in Pulau Pinang using frequency ratio method]. Geografi, 5(2), 13-26.

• Majid, N. A., Rainis, R., & Ibrahim, W. M. M. W. (2018). Pemodelan ruangan pelbagai jenis kegagalan cerun menggunakan rangkaian saraf buatan (ANN) di Pulau Pinang, Malaysia [Spatial modeling various types of slope failure using artificial neural network (ANN) in Pulau Pinang, Malaysia]. Jurnal Teknologi, 80(4), 135-146.

• Majid, N. A., & Rainis, R. (2019). Application of geographical information systems (GIS) and discriminant analysis in modelling slope failure incidence in Pulau Pinang, Malaysia. Sains Malaysiana, 48(7), 1367-1381. http://dx.doi.org/10.17576/jsm-2019-4807-06

• Mandal, S., & Mondal, S. (2019). Artificial neural network (ANN) model and landslide susceptibility. In Statistical Approaches for Landslide Susceptibility Assessment and Prediction 4 (pp. 123-133). Springer. https://doi.org/10.1007/978-3-319-93897-4_5-

• Mersha, T., & Meten, M. (2020). GIS-based landslide susceptibility mapping and assessment using bivariate statistical methods in Simada area, northwestern Ethiopia. Geoenvironmental Disasters, 7, Article 20. https://doi.org/10.1186/s40677-020-00155-x

• NASA. (2020). Global landslide catalog: Rainfall-triggered landslide events around the world. Data World. https://data.world/nasa/global-landslide-catalog

• Naseer, S., Haq, T. U., Khan, A., Tanoli, J. I., Khan, N. G., Qaiser, F. R., & Shah, S. T. H. (2021). GIS-based spatial landslide distribution analysis of district Neelum, AJ&K, Pakistan. Nat Hazards, 106, 965-989. https://doi.org/10.1007/s11069-021-04502-5

• Palansamy, Y. (2021). DBKL: Seri Duta 1 condo unsafe after partial landslide, situation being monitored. Malay Mail. https://www.malaymail.com/news/malaysia/2021/12/27/dbkl-seri-duta-1-condo-unsafe-after-partial-landslide-situation-being-monit/2031312

• Paudel, U., Oguchi, T., & Hayakawa, Y. (2016). Multi-resolution landslide susceptibility analysis using a DEM and random forest. International Journal of Geosciences, 7(5), 1-18. https://doi.org/10.4236/ijg.2016.75056

• Pawluszek, K., & Borkowski, A. (2017). Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland. Natural Hazards, 86, 919-952. https://doi.org/10.1007/s11069-016-2725-y

• Pradhan, B., & Lee, S. (2009). Landslide risk analysis using artificial neural network model focussing on different training sites. International Journal of Physical Sciences, 4(1), 001-015.

• Psomiadis, E., Papazachariou, A., Soulis, K. X., Alexiou, D. S., & Charalampopoulos, I. (2020). Landslide mapping and susceptibility assessment using geospatial analysis and earth observation data. Land, 9(5), Article 133. https://doi.org/10.3390/LAND9050133

• Rahim, A. F. A., Rafek, A. G. M., Serasa, A. S., Abdullah, R. A., Rahim, A., Sami, W. H. W., Foong, S. W., Abdurrahman, M., Lee, K. E., Nguyen, X. H., Tran, V. X., & Goh, T. L. (2022). Application of a comprehensive rock slope stability assessment approach for selected Malaysian granitic rock slopes. Sains Malaysiana, 51(2), 421-436. http://doi.org/10.17576/jsm-2022-5102-08

• Rahman, A. A. A., Majid, N. A., & Selamat, S. N. (2020). A comprehensive deriving the factors of landslide happened in Malaysia. International Journal on Emerging Technologies, 11(5), 310-314.

• Rahmati, O., Haghizadeh, A., Pourghasemi, H. R., & Noormohamadi, F. (2016). Gully erosion susceptibility mapping: The role of GIS-based bivariate statistical models and their comparison. Natural Hazards, 82, 1231-1258. https://doi.org/10.1007/s11069-016-2239-7

• Rasyid, A. R., Bhandary, N. P., & Yatabe, R. (2016). Performance of frequency ratio and logistic regression model in creating GIS-based landslides susceptibility map at Lompobattang Mountain, Indonesia. Geoenvironmental Disasters, 3(19), 1-16. https://doi.org/10.1186/s40677-016-0053-x

• Ritchie, H., Rosado, P., & Roser, M. 2014. Natural disasters. Our World in Data. https://ourworldindata.org/natural-disasters

• Saadatkhah, N., Kassim, A., & Lee, M. L. (2014). Spatial patterns of precipitation, altitude and monsoon directions in Hulu Kelang area, Malaysia. Electronic Journal of Geotechnical Engineering, 19(C), 521-534.

• Sanusi, M. S. M., Ramli, A. T., Hassan, W. M. S. W., Lee, M. H., Izham, A., Said, M. N., Wagiran, H., & Heryanshah, A. (2017). Assessment of impact of urbanisation on background radiation exposure and human health risk estimation in Kuala Lumpur, Malaysia. Environment International, 104, 91-101. https://doi.org/10.1016/j.envint.2017.01.009

• Selamat, S. N., Majid, N. A., Taha, M. R., & Osman, A. (2022). Landslide susceptibility model using artificial neural network (ANN) approach in Langat River Basin, Selangor, Malaysia. Land, 11(6), Article 833. https://doi.org/10.3390/land11060833

• Shahabi, H., & Hashim, M. (2015). Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment. Scientific Reports, 5, Article 9899. https://doi.org/10.1038/srep09899

• Sharir, K., Roslee, R., Lee, K. E., & Simon, N. (2017). Landslide factors and susceptibility mapping on natural and artificial slopes in Kundasang, Sabah. Sains Malaysiana, 46(9), 1531-1540. http://dx.doi.org/10.17576/jsm-2017-4609-23

• Silalahi, F. E. S., Pamela, Arifianti, Y., & Hidayat, F. (2019). Landslide susceptibility assessment using frequency ratio model in Bogor, West Java, Indonesia. Geoscience Letters, 6(10), 1-17. https://doi.org/10.1186/s40562-019-0140-4

• Sim, L. L., Adrian C., & Trisha N. (2018, December 4). Malaysia among countries especially prone to landslides. The Star. https://www.thestar.com.my/news/nation/2018/12/04/msia-ranks-highly-for-landslides-country-experienced-185-occurrences-annually-in-past-10-years#:~:text=Based%20on%20Nasa’s%20GLC%20website,)%20and%20Selangor%20(eight).

• Simon, N., De Roiste, M., Crozier, M., & Rafek, A. G. (2017). Representing landslides as polygon (areal) or points? How different data types influence the accuracy of landslide susceptibility maps. Sains Malaysiana, 46(1), 27-34. https://doi.org/10.17576/jsm-2017-4601-04

• Skilodimou, H. D., Bathrellos, G. D., Koskeridou, E., Soukis, K., & Rozos, D. (2018). Physical and anthropogenic factors related to landslide activity in the Northern Peloponnese, Greece. Land, 7(3), Article 85. https://doi.org/10.3390/land7030085

• Song, Z. C., Li, X., Lizárraga, J. J., Zhao, L., & Buscarnera, G. (2020). Spatially distributed landslide triggering analyses accounting for coupled infiltration and volume change. Landslides, 17, 2811-2824. https://doi.org/10.1007/s10346-020-01451-1

• The Start. (2022, January 6). 12 more landslide incidents reported, says NADMA. The Star. https://www.thestar.com.my/news/nation/2022/01/06/12-more-landslide-incidents-reported-says-nadma

• Wen, B. P., & Jiang, X. Z. (2016). Effect of gravel content on creep behavior of clayey soil at residual state: Implication for its role in slow-moving landslides. Landslides, 14, 559-576. https://doi.org/10.1007/s10346-016-0709-3

• Yuri, G., & Andrii, V. (2021). Implications of slope aspect for landslide risk assessment: A case study of Hurricane Maria in Puerto Rico in 2017. Geomorphology, 391, Article 107874. https://doi.org/10.1016/j.geomorph.2021.107874

• Yusoff, Z. M., Raju, G., & Nahazanan, H. (2016). Static and dynamic behaviour of Kuala Lumpur limestone. Malaysian Journal of Civil Engineering, 28(1), 18-25.

• Zhang, S., Bai, L., Li, Y., Li, W. L., & Xie, M. (2022). Learning models in landslide susceptibility mapping: A case study in Wenchuan County. Frontier in Environment Science, 10, Article 886841. https://doi.org/10.3389/fenvs.2022.886841