CLASSIFICATION OF PROSPECTIVE STUDENTS WHO ARE ELIGIBLE TO RECEIVE KIP MERDEKA LECTURE USING THE CART ALGORITMA APPROACH - Alwin Fau; Eferoni Ndruru; Fince Tinus Waruwu; Efori Bu’ulolo (Journal of Islamic, Social, Economics and Development, 2023)
To help prospective students who have academic potential but have economic limitations, the government through the Ministry of Education, Culture, Research and Technology of the Republic of Indonesia has programs namely the Smart Indonesia Program (PIP), one of which is KIP Lecture Merdeka. Every year Budi Darma University gets an allocation of KIP Lecture quotas from the Higher Education Service Institute (LLDikti) region I North Sumatra, in the process of determining prospective students who are eligible to receive KIP Lectures Merdeka Budi Darma University often experiences difficulties because the quota is very limited and also prospective students who there are a lot of people who want to go to college with the Merdeka Lecture KIP pathway. For this reason, a technique is needed in classifying KIP selection data for previous lectures, the aim is to assist the management of the Merdeka Lecture KIP at Budi Darma University in making a decision on a name that is truly worthy of receiving the Merdeka Lecture KIP. One of the classification techniques in data mining is the cart algorithm. The cart algorithm classifies the previous Lecture KIP selection data based on criteria variables and is associated with data labels. The results of the classification are prospective students who do not have a Prosperous Family Card (KKS) and are not accepted and prospective students who do have a KKS, their acceptance status as a student on the Merdeka Lecture KIP pathway must be based on exam results, if the exam results are low then they are not accepted and if the exam results are medium and high then accepted. One of the classification techniques in data mining is the cart algorithm. The cart algorithm classifies the previous Lecture KIP selection data based on criteria variables and is associated with data labels. The results of the classification are prospective students who do not have a Prosperous Family Card (KKS) and are not accepted and prospective students who do have a KKS, their acceptance status as a student on the Merdeka Lecture KIP pathway must be based on exam results, if the exam results are low then they are not accepted and if the exam results are medium and high then accepted. One of the classification techniques in data mining is the cart algorithm. The cart algorithm classifies the previous Lecture KIP selection data based on criteria variables and is associated with data labels. The results of the classification are prospective students who do not have a Prosperous Family Card (KKS) and are not accepted and prospective students who do have a KKS, their acceptance status as a student on the Merdeka Lecture KIP pathway must be based on exam results, if the exam results are