[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126405-en":3,"doc-seo-126405-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":11,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},126405,962085571259,"Theodora","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Groundwater Potential Mapping Using Frequency Ratio and Random Forest Machine Learning Technique","Groundwater is a critical freshwater source supporting humans, animals, and plants, while declining groundwater availability can harm industrial and agricultural sectors. This thesis determines groundwater potential areas in Kedah using Frequency Ratio (FR) and Random Forest (RF) machine learning. Fifteen conditioning parameters—such as terrain, TWI, drainage density, geology, lithology, aquifers, tube well distribution, distance to fault, rainfall, soil type, and land use—are compiled from multiple sources. FR derives random sampling points and builds groundwater/non-groundwater pixels for model training and testing with a 70:30 split. The resulting maps classify zones into five suitability levels and show ROC(AUC) of 81.4% for FR and 82.4% for RF, indicating stronger predictive performance for RF.","GROUNDWATER POTENTIAL MAPPING USING FREQUENCY RATIO AND RANDOM FOREST MACHINE LEARNING TECHNIQUE  \nSYARIFAH RAIHANA BINTI SYED ZABIDI  \n2021491738  \nCOLLEGE OF BUILT ENVIRONMENT UNIVERSITI TEKNOLOGI MARA PERLIS  \nAUGUST 2023  \nGROUNDWATER POTENTIAL MAPPING USING FREQUENCY RATIO AND RANDOM FOREST MACHINE  \nLEARNING TECHNIQUE  \nSYARIFAH RAIHANA BINTI SYED ZABIDI  \n2021491738  \nThesis submitted to the Universiti Teknologi MARA Malaysia in partial fulfilment for the award of the degree of the Bachelor of Surveying Science and Geomatics (Honours)  \nAUGUST 2023  \nDECLARATION  \nI declare that the work on this project/dissertation was carried out in accordance with the regulations of Universiti Teknologi MARA (UiTM) . This project/dissertation is original and it is the result of my work, unless otherwise indicated or acknowledged as referenced work.  \nIn the event that my project/dissertation be found to violate the conditions mentioned above, I voluntarily waive the right of conferment of my degree of the Bachelor of Surveying Science and Geomatics (Honours) and agree be subjected to the disciplinary rules and regulations of Universiti Teknologi MARA.  \nName of Student Student’s ID No Project/Dissertation Title  \nSignature and Date  \n: Syarifah Raihana Binti Syed Zabidi: 2021491738  \n: Groundwater Potential Mapping Using Frequency  \nRatio and Random Forest Machine Learning Technique  \n:  \n09/08/2023  \nApproved by:  \nI certify that I have examined the student’s work and found that they are in accordance with the rules and regulations of the School and University and fulfils the requirements for the award of the degree of Bachelor of Surveying Science and Geomatics (Honours) .  \nName of Supervisor : Sr. Hajah Sharifah Norashikin Binti Bohari  \nSignature and Date :   \n09/08/2023  \nABSTRACT  \nGroundwater is an important source of water for humans, animals, and also plants. The shortage of groundwater will decrease the economy of a country as it will affect many sectors such as industrial and agricultural. Therefore, to prevent this problem from happen, groundwater potential mapping must be conduct in order to determine the groundwater potential area. This study is aim to determine the groundwater potential area in Kedah by using Frequency Ratio (FR) and Random Forest (RF) machine learning technique. There were 15 groundwater conditioning parameters which are slope, aspect, elevation, topographical wetness index (TWI), plan curvature, drainage density, geomorphology, geology, lithology, aquifers, tube well distribution, distance to fault, rainfall, soil types and land use that has been obtained through various resources and departments. The groundwater potential map was determined by using FR method to define the relationship between dependent variables and independent variables. Then, 2,611 random points were generated through FR method. A total of 88,2782-pixel that contains the location for groundwater and nongroundwater has been extracted into each of the random points. These points were randomly partitioned into 70:30 for training and testing model using random forest machine learning technique. The maps of groundwater potential using FR and RF were classified into five different classes which are very high, high, medium, low and very low. It is found that the ROC(AUC) value for FR were 81.4% and RF were 82.4% respectively. It indicates that the validation of RF gives a high prediction rate compared to FR. The outcome of this study will help the state government of Kedah and any related agencies in control the additions and subtractions of the groundwater sources for the groundwater sustainable planning. It will help to prevent any water shortages from happening as well as to ensure that the residents in Kedah get to use the water sufficiently.  \nTABLE OF CONTENTS  \nCHAPTER TITLE PAGE  \nDECLARATION ⅰ  \nABSTRACT ⅱ  \nACKNOWLEDGEMENT ⅲ  \nTABLE OF CONTENTS ⅳ  \nLIST OF TABLES ⅶ  \nLIST OF FIGURES ⅷ  \nLIST OF ABBREVIATIONS ⅺ  \n1 INTRODUCTIO","cbCaidN021pYFdEs","https://ap.wps.com/l/cbCaidN021pYFdEs","pdf",208082,1,5,"English","en",105,"# Chapter 1 Introduction\n## Background of Study\n## Problem Statement\n## Research Questions\n## Aim\n## Objectives\n## Scope and Limitation\n## Significance of Study\n# Chapter 2 Literature Review\n## Introduction\n## Groundwater\n## Groundwater Potential Mapping Technology\n## Conventional Method\n## The Application of GIS and RS\n## Groundwater Potential Mapping Using Statistical Method\n## Groundwater Potential Mapping Using Machine Learning Method","[{\"question\":\"What is the purpose of groundwater potential mapping in this study?\",\"answer\":\"The study aims to determine groundwater potential areas in Kedah to support groundwater sustainable planning and reduce the risk of water shortages.\"},{\"question\":\"Which techniques are used to create the groundwater potential maps?\",\"answer\":\"Groundwater potential maps are produced using Frequency Ratio (FR) and Random Forest (RF) machine learning techniques.\"},{\"question\":\"How are model performance results evaluated and what do they indicate?\",\"answer\":\"Performance is evaluated using ROC(AUC), where FR reaches 81.4% and RF reaches 82.4%, indicating RF provides a higher prediction rate than FR.\"}]","Groundwater Potential Mapping Using Frequency Ratio and Random Forest Machine Learning Technique | PDF",1785904892,13,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"groundwater-potential-mapping-using-frequency-ratio-and-random-forest-machine-learning-technique","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/groundwater-potential-mapping-using-frequency-ratio-and-random-forest-machine-learning-technique/126405/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-23","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":11},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the purpose of groundwater potential mapping in this study?","Question",{"text":76,"@type":77},"The study aims to determine groundwater potential areas in Kedah to support groundwater sustainable planning and reduce the risk of water shortages.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Which techniques are used to create the groundwater potential maps?",{"text":81,"@type":77},"Groundwater potential maps are produced using Frequency Ratio (FR) and Random Forest (RF) machine learning techniques.",{"name":83,"@type":74,"acceptedAnswer":84},"How are model performance results evaluated and what do they indicate?",{"text":85,"@type":77},"Performance is evaluated using ROC(AUC), where FR reaches 81.4% and RF reaches 82.4%, indicating RF provides a higher prediction rate than FR.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":21,"slug":138},19,"General","general"]