Implementasi Decision Tree Untuk Prediksi Kelulusan Mahasiswa Tepat Waktu

Dengen, Christin Nandari; Kusrini, Kusrini; Luthfi, Emha Taufiq

doi:10.30700/jst.v10i1.484

Cited by 11 publications

(10 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Penelitian-penelitian sebelumnya yang menggunakan Metode C4.5 adalah implementasi Decision Tree untuk prediksi kelulusan mahasiswa tepat waktu [8]. Memprediksi mahasiswa yang berpotensi non aktif menggunakan Data Mining dalam DecisionTree dan Algoritma C4.5 [9].…”

Section: Pendahuluanunclassified

Prediksi Hasil Belajar Siswa Secara Daring pada Masa Pandemi COVID-19 Menggunakan Metode C4.5

2021

View full text Add to dashboard Cite

Student learning in schools has changed since the Covid-19 pandemic. Student learning in normal conditions is carried out face-to-face and turns into online or online learning. The research was conducted to predict student learning outcomes during the COVID-19 pandemic so that the results of this study can be used as a reference in policymaking in schools. The C4.5 method was used in the study to classify the data for class XII of the Multimedia Department at SMKN 2 Padang Panjang and the classification results could predict student learning outcomes during the pandemic. Processed student value data were taken from 1 (one) subject as the research data sample. Analysis of the value of student learning outcomes using the C4.5 Method to obtain new knowledge from student learning outcomes data carried out during the COVID-19 pandemic. The data analyzed consisted of attributes of attendance, assignments, daily tests, and test scores which influenced the decision criteria for student learning outcomes in online learning. The learning outcome decision criteria consist of "Satisfactory" and "Not Satisfactory" which refer to the Minimum Completion Criteria. Tests conducted on the training data of learning outcomes show that the value of the Daily Test is the most influential attribute in decision making. Implementation of the results using the RapidMiner Studio 9.2.0 software and produces an accuracy of 83.33% of the test data testing with the rules of data analysis training results. The results of the C4.5 classification testing method in this study can be used to predict student learning outcomes. The test results with an accuracy of 83.33% can be recommended to help schools in making policies

show abstract

Section: Pendahuluanunclassified

Prediksi Hasil Belajar Siswa Secara Daring pada Masa Pandemi COVID-19 Menggunakan Metode C4.5

2021

View full text Add to dashboard Cite

show abstract

“…Penggalian Data adalah sebuah proses untuk memperoleh suatu informasi yang memiliki nilai dari basis data besar. Proses pada data mining akan menghasilkan rule atau aturan untuk menghasilkan suatu informasi seperti menentukan prediksi kelulusan mahasiswa [5]. Algoritma C4.5 merupakan algoritma pohon keputusan, dan sudah banyak mengalami perkembangan akan tetapi yang sering digunakan yaitu ID3 dan C4.5 dimana ini sama-sama membangun suatu pohon keputusan.…”

Section: Pendahuluanunclassified

Prediksi Tingkat Kepuasan Pelayanan Online Menggunakan Metode Algoritma C.45

Lestari

Defit²,

Yuhandri

2021

INFEB

View full text Add to dashboard Cite

Online service is a service that uses the help of the internet. This service can solve various types of business without having to meet directly with employees. This can be done quickly and on time. Especially when we are currently experiencing the Covid-19 pandemic, all existing services are carried out online and this is increasingly being done by many parties, because they can maximize in helping people's affairs online. This service makes it easier for the public to register which will be done online during this pandemic. The data that will be processed in this online service from 2019 to 2020 is about data about people who do not understand online services, negative community responses, positive community expectations. The method used in this study is the method with the C4.5 algorithm where this is one of the algorithms that will be used to determine a classification or group of data and will be predictive. The advantage of this algorithm is that it can produce a decision tree which will make it easier to implement and will have an acceptable level of accuracy. The results of this study are able to predict a value or determine the level of community satisfaction in 2021 appropriately. Therefore, this study can be used as a reference to determine the level of satisfaction at the Padang City Population and Civil Registration Office. The method used in this study is the prediction method using the C4.5 algorithm by using as many as 14 attributes. The data used in this study is sourced from data from online questionnaires and stored in the Disdukcapil database which has as many as 50 community data which have been presented in a CSV file. The analysis in this study uses the help of tools in the form of rapid miner software version 5.3,000. The results of this study are that there are 3 rules from the data processing process using the C4.5 algorithm where the rule is the final result of the decision tree form.

show abstract

“…Penelitian Christin dkk (2020) untuk memprediksi kelulusan mahasiswa tepat waktu. Dari penelitian ini didapatkan hasil menggunakan metode decision tree menghasilkan nilai akurasi sebesar 60% [15]. Penelitian Sembiring dkk (2018) untuk memprediksi hasil belajar mahasiswa.…”

Section: Pendahuluanunclassified

Prediksi Potensi Relawan Pendonor Darah Menjadi Pendonor Darah Tetap dengan Penerapan Metode Klasifikasi Decision Tree

Adha

Yuhandri

Nurcahyo

2021

jidt

View full text Add to dashboard Cite

Donor darah merupakan kegiatan penting untuk memperoleh darah sebagai bahan baku ke dalam rantai suplai darah. Jika darah di dalam tubuh manusia tidak cukup maka kelangsungan hidup akan terancam, untuk beberapa kondisi diperlukan tindakan untuk melakukan transfusi darah, seperti kecelakaan, proses melahirkan atau demam berdarah pada grade tertentu. UTD PMI Kota Pekanbaru merupakan badan penyelenggara kegiatan donor darah dalam proses membantu dan melayani kebutuhan darah bagi masyarakat. Berdasarkan data pada Kementrian Kesehatan pada tahun 2019 Kota Pekanbaru mengalami kekurangan stok darah sebanyak 32,4 persen yang mana seharusnya pesediaan stok darah terbaik pada Kota Pekanbaru adalah sebanyak 130.019. Hal tersebut membuat beberapa Rumah Sakit kesusahan untuk memenuhi persediaan stok darah. Penyebab sedikitnya persediaan stok darah pada Kota Pekanbaru terjadi karena jumlah relawan pendonor yang turun naik dan rendahnya minat masyarakat untuk menjadi relawan pendonor darah. Sehingga menjadi permasalah ketika jumlah permintaan darah meningkat sedangkan persediaan pada bank darah menipis. Metode yang digunakan pada penelitian ini yaitu metode Decision Tree. Algoritma yang dipilih pada penelitian ini yaitu Algoritma C.45. Dalam mengatasi permasalahan yang terjadi, dilakukannya analisa data relawan pendonor darah. Berdasarkan hasil analisa dari data testing sebanyak 50 record dihasilkan rule sebanyak 6 rule yang dapat disimpulkan umur diatas 19 tahun dengan pekerjaan wiraswasta berpotensi menjadi pendonor darah tetap.

show abstract

Implementasi Decision Tree Untuk Prediksi Kelulusan Mahasiswa Tepat Waktu

Cited by 11 publications

References 0 publications

Prediksi Hasil Belajar Siswa Secara Daring pada Masa Pandemi COVID-19 Menggunakan Metode C4.5

Prediksi Hasil Belajar Siswa Secara Daring pada Masa Pandemi COVID-19 Menggunakan Metode C4.5

Prediksi Tingkat Kepuasan Pelayanan Online Menggunakan Metode Algoritma C.45

Prediksi Potensi Relawan Pendonor Darah Menjadi Pendonor Darah Tetap dengan Penerapan Metode Klasifikasi Decision Tree

Contact Info

Product

Resources

About