Penerapan Algoritma C4.5 Untuk Klasifikasi Penyakit Disk Hernia Dan Spondylolisthesis Dalam Kolumna Vertebralis

Handayani, Irma

doi:10.26905/jasiek.v1i2.3185

Cited by 4 publications

(7 citation statements)

References 2 publications

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“…d. 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 Classification is the process of finding a set of models/functions that describe and distinguish data into specific classes, with the aim of using that model in determining the class of an object of unknown class (Handayani, 2019). The purpose of classification is to find a model of a training set that distinguishes attributes into corresponding categories or classes, the model is then used to classify attributes whose classes have not been previously known (Azwanti, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

“…There are two classification processes consisting of: the learning/training process is to build a model using training data, where each record in the training data is analyzed based on its attribute values using the C4.5 algorithm to obtain the model. Then the testing process is to test the testing data using the model that has been obtained from the training process (Handayani, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Where after the process of calculating the information gain value, the values obtained for each attribute will be compared. And the ones that get the greatest value will (Handayani, 2019) Data mining is a series of processes to explore the added value of a set of data in the form of knowledge that has not been known manually. Data mining actually has long roots in fields of science such as artificial intelligence, machine learning, statistics and databases.…”

Section: Introductionmentioning

confidence: 99%

“…The C4.5 algorithm is one of the algorithms contained in data mining classification and is a model or function that explains or distinguishes concepts or data classes with the aim of estimating the unknown class of an object. In general, the C4.5 algorithm to build a decision tree is to choose an attribute as the root, create a branch for each value, divide the cases into branches, then repeat the process for each branch until all cases in the branch have the same class (Handayani, 2019) Previous research conducted by (Lukhayu Pritalia, 2018), concluded that data mining with the C4.5 algorithm can be implemented to determine the availability of e-commerce goods with two categories, namely the goods are not in a condition or not yet available for ordering goods for customers/backorders and goods are in available condition for ordering goods for customers and the results of the analysis using the C4.5 algorithm to determine the time of determining the availability of goods have an accuracy rate of 98.9%.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Siregar

Sembiring

Hasdiana

et al. 2021

SinkrOn

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University of Harapan Medan is one of the private universities in North Sumatra which has computer-based study programs such as Informatics Engineering and Information Systems. Every year this college receives many registrations from students who have completed their education at the school stage. The large number of incoming student data makes it difficult for the admin to select new students who will register. In this study using the C4.5 algorithm data mining method to map the pattern of student admissions selection in the field of Engineering and computers. The attributes used are the average value of report cards (high, enough, low), basic academic ability tests (very high, high, medium, low, very low), basic computer knowledge tests (very high, high, enough, low, very low) and interviews (good, bad). Data mining is a mathematical calculation process that uses algorithms and requires large data. While the C4.5 algorithm is an algorithm that processes data by calculating entrophy and information gain, where after the calculation process is carried out, those who get the largest information gain value will become nodes and branches. This C4.5 algorithm will describe a decision tree that will form a pattern in student selection. The results of this study indicate that in mapping the selection pattern of interview attributes into level 1 nodes, the attributes of the basic computer knowledge test become the level 1 branch, the attributes of the basic academic ability test become the level 2 branch and the attribute average value of report cards becomes the level 3 branch.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Siregar

Sembiring

Hasdiana

et al. 2021

SinkrOn

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“…Beberapa penelitian menggunakan algoritma C.45 menunjukkan hasil dan akurasi yang baik. Penelitian sebelumnya mengenai penerapan algoritma C4.5 pada klasifikasi penyakit disk hernia dan spondylolisthesis [13]. Pada penelitian ini brdasarkan pengujian akurasi didapatkan nilai akurasi sebesar 89% dan rata-rata lama waktu yang dibutuhkan untuk melakukan klasifikasi adalah 0,00912297 detik.…”

Section: Pendahuluanunclassified

Pengembangan Sistem Klasifikasi Tipe Kepribadian Siswa Secara Psikologis dengan Algoritma Decision Tree C.45

Nuraini

Hakim²,

Lisnawati³

et al. 2021

bits

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In the world of education knowing the personality type of students is very important. This is because a person's personality is influential in his learning activities and how he digests and captures the material presented by the teacher. For this reason, knowing the classification of students' personalities needs to be identified so that teachers or students themselves can optimize self-change in a better and positive direction. This study aims to develop a psychological classification system for student personality types using the C.45 decision tree algorithm. The personality type used as a class in the classification is based on psychology, including: Sanguine, Phlegmatic, Choleric and Melancholic. In this study, a web-based system was developed, so that it is easy to use for teachers and students to recognize the personality of these students. To determine the personality of students psychologically, students answer questions in the system, then the system will classify based on the answers from these students. The C.45 decision tree algorithm serves to find knowledge or patterns of characteristic similarity in a particular group or class. From the test results, the pecision value is 90%, the recall is 85% and the accuracy is 88%. This shows that the C.45 decision tree algorithm can perform personality type classification well

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Untitled

Abednigo,

Raharja

2023

JLK

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Penyakit Ginjal Kronis adalah penyakit yang umum di masyarakat dengan jumlah penderita yang terus meningkat. Penyakit ini menyerang ginjal yang mengakibatkan ginjal tidak bisa berfungsi dengan dengan baik. Data mining adalah proses untuk mengekstrak data dengan tujuan mendapatkan informasi yang berharga, salah satunya metode data mining adalah klasifikasi. Algoritma Decision Tree adalah salah satu algoritma klaifikasi yang bisa digunakan untuk melakukan klasifikasi penyakit ginjal kronis. Pada penelitian ini, klasifikasi diakukan dengan Decision Tree yang digabungkan dengan seleksi fitur menggunakan Forward Selection. Forward Selection digunakan untuk mengurangi fitur yang tidak relevan terhadap target klasifikasi. Dataset yang digunakan adalah Chronic Kidney Disease dataset dari Kaggle. Pada hasil pengujian Decision Tree dengan bantuan library sklearn dari python dengan cross validation sebanyak 10 fold didapatkan bahwa seleksi fitur dengan forward selection berhasil meningkatkan hasil akurasi, presisi, recall, dan f1 score secara berurutan adalah 99.5%,

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Penerapan Algoritma C4.5 Untuk Klasifikasi Penyakit Disk Hernia Dan Spondylolisthesis Dalam Kolumna Vertebralis

Cited by 4 publications

References 2 publications

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

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

Pengembangan Sistem Klasifikasi Tipe Kepribadian Siswa Secara Psikologis dengan Algoritma Decision Tree C.45

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