Crowdfunding 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.

Sarifah Putri Raflesia

Dinda Lestarini

Rizka Dhini Kurnia

Dinna Yunika Hardiyanti

Bulletin of Electrical Engineering and Informatics

Bulletin of Electrical Engineering and Informatics publishes original papers in the field of electrical, computer and informatics engineering which covers, but not limited to, the following scope:    Computer Science, Computer Engineering and Informatics[...]  Electronics[...]    Electrical and Power Engineering[...]    Telecommunication and Information Technology[...]Instrumentation and Control Engineering[...]

The Bulletin of Electrical Engineering and Informatics publishes original papers in the fields of electrical, computer, and informatics engineering. The scope includes, but is not limited to: Computer Science, Computer Engineering, and Informatics; Electronics; Electrical and Power Engineering; Telecommunication and Information Technology; Instrumentation and Control Engineering.

《Bulletin of Electrical Engineering and Informatics》期刊发表电气、计算机和信息工程领域的原创论文，涵盖但不限于以下范围：计算机科学、计算机工程和信息学；电子学；电气与电力工程；电信与信息技术；仪器与控制工程等。

Using machine learning approach towards successful crowdfunding prediction

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