Algortihm C4.5 in mapping the admission patterns of new Students in Engingeering Computer

Siregar, Yunita Sari; Sembiring, Boni Oktaviana; Hasdiana, Hasdiana; Dewi, Arie Rafika; Harahap, Herlina Jasa Putri

doi:10.33395/sinkron.v6i1.11154

Cited by 3 publications

(5 citation statements)

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“…Association Rules detect a set of attributes that appear together (co-occur) in frequent frequencies and form a number of rules of those sets. e. Sequential (Sequence Mining) Looking for a number of events that generally occur together (Siregar et al, 2021). Classification is the process of finding a model or function that describes and differentiates data classes or concepts.…”

Section: Iteration Iteration Requires the Designer To Always Think Ag...mentioning

confidence: 99%

“…Data mining actually has long roots in fields of science such as artificial intelligence, machine learning, statistics and databases. Some of the techniques that are often mentioned in the Data Mining literature include clustering, classification, association rule mining, neural network, and genetic algorithms (Siregar et al, 2021). Data mining is mining or discovering new information by looking for certain patterns or rules from a very large amount of data.…”

Section: Introductionmentioning

confidence: 99%

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Implementation Of The Data Mining Cart Algorithm In The Characteristic Pattern Of New Student Admissions

Siregar

Khairani

2023

CNAHPC

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University of Harapan Medan is one of the private universities in North Sumatra which has an Informatics Engineering Study Program with Good Accreditation. With better accreditation, the number of students who register is also increasing. At the admission of new students, the committee has a huge pile of data, making it difficult in the process of whether the student passed or did not pass. Therefore, in this study, we will implement data mining with the CART (Classification And Regression Tree) algorithm. Data mining is a technique to determine the characteristic pattern of a variable or data criteria with a large amount. In the CART method, the data is first converted into testing data, which will then be used to form a classification tree by calculating the value of information gain, Gini index and goodness of split. From the results obtained, it will be re-determined terminal nodes, marking class labels and finally pruning the classification tree which produces a decision tree. In this study, the number of testing data was 75 with 3 criteria, namely the average value of report cards, CAT test scores, and interview scores. The results of testing data testing using RapisMiner 5.3 software produce 23 number of characteristic pattern rules, where node 1 is the CAT test score, level 1 branch node is the interview score criteria and level 2 branch node is the average report card value.

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Section: Iteration Iteration Requires the Designer To Always Think Ag...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Implementation Of The Data Mining Cart Algorithm In The Characteristic Pattern Of New Student Admissions

Siregar

Khairani

2023

CNAHPC

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“…The C4.5 algorithm is an algorithm that processes data by calculating entropy and information gain. After the process of calculating the information gain value, the values obtained for each attribute will be compared (Siregar et al, 2021). The C4.5 algorithm is one of the algorithms contained in data mining classification and is a model or function that explains or differentiates concepts or data classes to estimate the unknown class of an object.…”

Section: Introductionmentioning

confidence: 99%

“…In general, the C4.5 algorithm for building a decision tree is to select an attribute as the root, create a branch for each value, divide the cases into branches, and then repeat the process for each branch until all cases in the branch have the same class. (Siregar et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Prediction of the Human Development Index for Equitable Development in West Sumatra Province Using the C4.5 Algorithm

Sirait,

Azizah

2023

SinkrOn

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Unequal development in Indonesia can be seen from the Human Development Index. The Human Development Index is a tool used to measure the attainment of the quality of life of a region or country and as material for economic policy on quality of life. It contains components of health level, education level and welfare level. In 2022, West Sumatra Province achieved the 9th highest Human Development Index in Indonesia, namely 73.26, with this figure the West Sumatra Province Human Development Index is above the national average. However, there are still regencies/cities in West Sumatra Province that have achievements below the national average. This factor causes the development conditions in West Sumatra Province to be uneven. Uneven human development conditions will make it difficult for the government to improve Human Resources (HR). In this research, the C45 Data Mining Algorithm was implemented to predict the Regency/City Human Development Index in West Sumatra Province. As is the method of the Central Bureau of Statistics in measuring the Human Development Index, the variables used from the Human Development Index indicators are Life Expectancy, Years of School Expectation, Average Length of Schooling, and Per Capita Expenditures. The Central Statistics Agency data used in this research covers all regencies/cities in West Sumatra during the period 2018-2022. Range levels are grouped into three groups, namely, low, medium, and high. Based on testing using RapidMiner software with the Cross Validation operator, an accuracy value of 86.61% was obtained.

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“…Data mining merupakan serangkaian proses untuk menggali nilai tambah dari suatu kumpulan data berupa pengetahuan yang selama ini tidak diketahui secara manual (Siregar et al, 2021). data mining digunakan untuk mendapatkan informasi penting dan mengetahui pola di dalam sebuah dataset yang didapatkan dari data lama agar dapat digunakan sebagai acuan untuk memprediksi data yang baru.…”

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Prediction System for Credit Eligibility Using C4.5 Algorithm

Puspita¹,

Aminah²,

Arif³

2022

JITE

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Independent Multipurpose Cooperative, Tasti, Pagar Alam City, currently granting credit, the data collection process for the selection of prospective members and prospective credit recipients is still done manually, so they must come to the cooperative to find out whether it is still eligible to receive credit or not, officers must evaluate the data. is to form a decision tree classification model for creditworthiness in cooperatives. The analytical method with the C4.5 Algorithm, the C4.5 Algorithm is one of the algorithms for performing data mining using data classification techniques. The C4.5 algorithm is used to search for knowledge in the data, by finding the relationship between input variables or criteria attributes with target variables or decision attributes. The resulting knowledge is converted into the form of a decision tree so that it is easy to understand. The C4.5 algorithm was chosen because it can make a decision to be able to predict whether a customer is eligible or not to be given credit. The attribute used is income with specified criteria. The results obtained from this study are predictive information on the feasibility of providing credit to cooperatives using the C4.5 algorithm by getting an accuracy value of 93% with an AUC value of 0.898 where this classification is classified as Good Classification or good.

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Algortihm C4.5 in mapping the admission patterns of new Students in Engingeering Computer

Cited by 3 publications

References 10 publications

Implementation Of The Data Mining Cart Algorithm In The Characteristic Pattern Of New Student Admissions

Implementation Of The Data Mining Cart Algorithm In The Characteristic Pattern Of New Student Admissions

Prediction of the Human Development Index for Equitable Development in West Sumatra Province Using the C4.5 Algorithm

Prediction System for Credit Eligibility Using C4.5 Algorithm

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