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It evaluates logistic regression, random forest, and XGBoost, while testing PCA-based feature reduction and log transformation to enhance predictive performance. Results indicate that log transformation improves model accuracy, and XGBoost outperforms linear regression and random forest.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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Putri Raflesia1, Dinda Lestarini1,2, Rizka Dhini Kurnia3, Dinna Yunika Hardiyanti1,4  \n1Department of Computerized Accounting, Faculty of Computer Science, Universitas Sriwijaya, Palembang, Indonesia 2Database and Big Data Laboratory, Faculty of Computer Science, Universitas Sriwijaya, Palembang, Indonesia 3Department of Information Management, Faculty of Computer Science, Universitas Sriwijaya, Palembang, Indonesia 4Electronic Data Processing and Decision Support System Laboratory, Faculty of Computer Science, Universitas Sriwijaya,  \nPalembang, Indonesia  \nArticle history:  \nReceived Nov 15, 2022 Revised Dec 12, 2022 Accepted Jan 19, 2023  \nKeywords:  \nCrowdfunding Linear regression Prediction Random forest XGBoost  \nCorresponding Author:  \nCrowdfunding is a concept that emerged due to difficulties in raising funds for community business projects, social activities, micro-enterprises, and start-ups conventionally. Crowdfunding uses internet technology as a bridge between the donor and the recipient of funds so that it can reach a wider range of donors. This study aims to compare the performance of machine learning approaches in predicting crowdfunding campaign success. Three machine learning algorithms were employed to predict crowdfunding campaign success, namely logistic regression, random forest, and extreme gradient boosting (XGBoost) . The dataset used in this study contains data about all projects posted on Kickstarter from January 2020 to September 2022. To improve the prediction model's performance, experiments using principal component analysis (PCA) feature reduction and log transformation were conducted. The results show that the implementation of log transformation on the dataset can increase the prediction model's performance. Meanwhile, XGBoost algorithm performs better than linear regression and random forest.  \nThis is an open access article under the CC BY-SA license.  \nDinda Lestarini  \nDepartment of Computerized Accounting, Faculty of Computer Science, Universitas Sriwijaya 30862 Indralaya, Palembang, Sumatera Selatan, Indonesia  \nEmail: [dinda@unsri.ac.id](dinda@unsri.ac.id)  \nArticle Info ABSTRACT  \n1. INTRODUCTION  \nThe use of information technology to assist human activities is currently very massive. One of technology that is used massively and connecting human is internet. The emergence of the internet as one of the impacts of technological developments makes people can easily and quickly find whatever they are looking for. Starting from social media, shopping, studying, and discussing, to the internet as a medium toreap benefits as digital influencers. The use of internet technology has provided an understanding for some groups that the internet can be maximally utilized to get people's attention quickly and a lot. Not only done locally but also worldwide [1]–[3] . In the development of the industrial revolution 4.0, more innovations have been carried out in various fields including financial technology such as mobile payments, crowdfunding, peer-to-peer (P2P) lending, insurance, and wealth management [4] . In this research, the technology product that will be discussed is crowdfunding.  \nStarting from the difficulty of raising funds for community business projects, social activities, micro-enterprises, and start-ups, in recent years a platform called crowdfunding has emerged [5], [6] . Crowdfunding is an alternative form of traditional funding. Crowdfunding can be used to fund various  \nprojects and is open to any individual or group. The principle of crowdfunding is the same as conventional funding, but what makes the difference is the use of the internet as a bridge between the donor and the recipient of funds [7], [8] . Using the internet, fundraisers can easily go viral, allowing large amounts of money to be raised. In addition, the internet allows information about projects to be funded to spread quickly. Crow","cbCailaSHMMHdye5","https://ap.wps.com/l/cbCailaSHMMHdye5","pdf",339683,"English","# Keywords\n# Corresponding Author\n# ABSTRACT\n# 1. INTRODUCTION\n## Crowdfunding definition and models\n## Kickstarter background and dataset scope\n# 2. METHOD","[{\"question\":\"What is the goal of this research on crowdfunding?\",\"answer\":\"To compare machine learning approaches for predicting the success of crowdfunding campaigns on Kickstarter.\"},{\"question\":\"Which algorithms are used to predict crowdfunding success?\",\"answer\":\"The study uses logistic regression, random forest, and extreme gradient boosting (XGBoost).\"},{\"question\":\"Why is XGBoost highlighted in the findings?\",\"answer\":\"XGBoost achieves better performance than linear regression and random forest on the prepared dataset.\"}]","Using machine learning approach towards successful crowdfunding prediction - Article history, keywords, and method | PDF",1789641784]