Orphan Adoption Management System using Machine Learning Approach

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Author(s)

R. Kaladevi 1,* Jeevitha B 2 Jeevitha V 2 Madhumitha P 2 Shanmugasundaram Hariharan 3 Andraju Bhanu Prasad 3

1. Saveetha Engineering College, Chennai

2. Department of Computer Science and Engineering, Saveetha Engineering College, Chennai

3. Department of Computer Science and Engineering, Vardhaman College of Engineering, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijeme.2022.05.03

Received: 14 Jun. 2022 / Revised: 18 Jul. 2022 / Accepted: 17 Aug. 2022 / Published: 8 Oct. 2022

Index Terms

SVM algorithm, Orphan, Record management, Machine Learning.

Abstract

According to UNICEF, the latest estimate states that there are about 2.7 million children in orphanages. Orphanage is a residence for people who are without parental support or any moral support from anyone. Such orphans require help from people who are in a good financial state to donate them. Generally, in orphanage records are usually maintained for future reference, retrieval, and easy management. The objective of this paper is to help the orphans from different orphanages to get help from the donors who wish to donate them by using our web application. The proposed system helps the staff in reducing manual paper work and enhances tidiness in record keeping since the existing one uses manual keeping, i.e., the use of files and papers. The system allows the orphanage owner to add and modify the orphan records. The system provides suggestions for assignment of these orphans to the caretakers/donors by using SVM (Support Vector Machine) algorithm. Donor can select the orphan and request for adoption from the orphanage owner. The Orphanage owner can accept or reject help from the donor. The proposed system is aimed to facilitate donors with the details of an orphan and providing fund specifically to that orphan.

Cite This Paper

R. Kaladevi, Jeevitha B, Jeevitha V, Madhumitha P, Shanmugasundaram Hariharan, Andraju Bhanu Prasad, "Orphan Adoption Management System using Machine Learning Approach", International Journal of Education and Management Engineering (IJEME), Vol.12, No.5, pp. 18-23, 2022. DOI:10.5815/ijeme.2022.05.03

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