Implementasi Algoritma C4.5 Untuk Menentukan Penerima Beasiswa Di STT Harapan Medan

Rismayanti, Rismayanti

doi:10.37676/jmi.v12i2.413

Cited by 13 publications

(12 citation statements)

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“…Larose argues that, data mining is a computational process in artificial intelligence to find patterns, relationships and trends from a set of similar large data. Data mining is about extracting related patterns from a set of data to create a data forecasting model [1], [11], [13], [14]. Kusnawi argues that data mining is a combination of technology that uses traditional analytical methods and sophisticated algorithms to process large amounts of data.…”

Section: Data Miningmentioning

confidence: 99%

Classification and Regression Trees (CART) Algorithm for Employee Selection

Rahmawati

Affandi²,

Aprillia³

et al. 2022

JAIS

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Recruitment is the main key in an effort to improve the quality of human resources in a company. Good or bad employees greatly affect the quality of the company. Therefore, it is necessary to be thorough and take a long time in screening applicants in order to get competent, professional and as expected prospective employees. The absence of professional staff to conduct employee selection is the background of this research. So the researcher uses the CART algorithm for the classification of employee recruitment, so it is hoped that it can help companies in conducting employee selection. The dataset was obtained from the selection of freelance daily workers at the Pati Regency Civil Service Police Unit in 2018, totaling 290 prospective employees. Based on calculations on 5-fold cross validation, the resulting accuracy is 98.27%, precision is 99.13% and recall is 96.88%.

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Section: Data Miningmentioning

confidence: 99%

Classification and Regression Trees (CART) Algorithm for Employee Selection

Rahmawati

Affandi²,

Aprillia³

et al. 2022

JAIS

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“…Dalam penelitian ini, algoritma yang digunakan adalah algoritma C4.5. Algoritma C4.5 merupakan metode klasifikasi dan prediksi yang digunakan untuk membentuk Decission Tree berdasarkan data training [6]. Decission tree adalah struktur flowchart yang memiliki Tree (Pohon), dimana setiap simpul internal menandakan suatu tes atribut, setiap cabang merepresentasikan hasil tes dan simpul daun merepresentasikan kelas atau distribusi kelas [7].…”

Section: Pendahuluanunclassified

Data Mining Prediksi Minat Calon Mahasiswa Memilih Perguruan Tinggi Menggunakan Algoritma C4.5

Nas¹

2021

JAMIKA

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The city of Cirebon has many diverse private universities and offers a variety of majors. Due to a large number of existing private universities, the competition between universities to attract prospective new students is very tight. So to be able to compete with these universities, the campus needs to predict the interest of prospective new students by knowing what factors are driving prospective new students to choose colleges. The purpose of this study was to predict the interest of prospective students in choosing a college. In this study, the data processed are the results of a survey conducted on prospective new students in the D3-Informatics Management Study Program. There are 25 sample data as training datasets with 5 assessment data. The data will be processed using the Data Mining process with the Classification Method. Furthermore, with the C4.5 algorithm in the Classification method, iterations are obtained up to node 4 with 3 assessment data which are factors in determining the interest of prospective students in the study program. Furthermore, the results of data processing using the classification method with the C4.5 algorithm were tested using Rapid Miner Software, which obtained a 100% accuracy rate with 120 testing datasets. The final result of using Data Mining with the C4.5 algorithm has been able to predict the interest of prospective new students based on assessment factors in choosing universities.

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“…Algoritman ini menggunakan metode klasifikasi dan prediksi yang sangat kuat dan terkenal . Konsep dari decision tree yaitu merubah data menjadi decision tree dan aturan-aturan keputusan atau disebut dengan decision rules dan merupaka pengembangan dari Algoritma ID3 [10]. Ada beberapa tahap yang digunakan dalam penerapan decision tree dengan Algoritma C4.5, berikut tahapannya [11]…”

Section: Metode Penelitian 21 Sistem Pendukung Penelitianunclassified

Decision Tree dalam Menganalisis Data Pengunjung Wisata Danau Poso untuk Pengambilan Keputusan

Pa'o

Hendry

2021

json

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This study uses a classification system in managing its data. In classification there are several methods provided, one of which is the decision tree method with the C4.5 algorithm this method means a decision tree where the structure is the same as a flowchart where each node signifies an attribute test, each branch presents the test results and the leaf node represents the class or class distribution. The data used is the data of Lake Poso Tourism visitors from 2009 to 2020, then the method used in this study is divided into several stages, namely the data being studied, analyzing the data, transforming data and designing a decision tree with the C4.5 algorithm. The results achieved from this study are that the number of visitors more than 28,984 has a description of "Much" which is dominated by local tourists, while the value with the name "Less" is in foreign tourists. This is one of the important points in determining the right strategy for developing tourism in Lake Poso.

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Implementasi Algoritma C4.5 Untuk Menentukan Penerima Beasiswa Di STT Harapan Medan

Cited by 13 publications

References 0 publications

Classification and Regression Trees (CART) Algorithm for Employee Selection

Classification and Regression Trees (CART) Algorithm for Employee Selection

Data Mining Prediksi Minat Calon Mahasiswa Memilih Perguruan Tinggi Menggunakan Algoritma C4.5

Decision Tree dalam Menganalisis Data Pengunjung Wisata Danau Poso untuk Pengambilan Keputusan

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