Penerapan Data Mining Untuk Memprediksi Penerimaan Peserta Didik Baru Menggunakan Algoritma C4.5

Winanjaya, Riki; Amir, Faisal; Doni, Rahmad

doi:10.30645/senaris.v1i0.1

Cited by 5 publications

(6 citation statements)

References 2 publications

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“…Kendala muncul dalam pemilihan siswa baru karena ketidak-konsistenan dan sifat subjektif penilaian. Oleh karena itu, diperlukan metode identifikasi calon siswa baru di sekolah [3].…”

Section: Pendahuluanunclassified

Analisis Data Penerimaan Peserta Didik Baru Menggunakan Cross Validation Dan Algoritma Decision Tree Di Sma Negeri 1 Bandung

Andriyani,

Kurniawan,

Arie Wijaya

2024

jati

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Setiap tahun, SMA Negeri 1 Bandung menerima calon peserta didik baru melalui tiga jalur pendaftaran: penelusuran minat, Prestasi Akademik (PA), dan ujian tertulis. Namun, proses seleksi dalam Penerimaan Peserta Didik Baru (PPDB) menghadapi kendala dalam menetapkan kriteria kelulusan. Untuk mengatasi masalah ini, diperlukan prediksi data guna meningkatkan kualitas penerimaan siswa. Tujuan penelitian ini adalah menganalisis data PPDB untuk menyederhanakan proses seleksi calon siswa dengan menerapkan teknik data mining, khususnya algoritma Decision Tree. Metode ini menghasilkan pohon keputusan yang membantu mengidentifikasi siswa yang lolos dan tidak lolos dengan lebih efisien. Hasil penelitian menggunakan aplikasi RapidMiner Studio menunjukkan bahwa dari 282 data, sebanyak 86 data tidak lolos dan 191 data lolos, dengan tingkat akurasi mencapai 98.24%, precision 97.45%, dan recall 94.51%. Pemahaman faktor-faktor yang mempengaruhi keberhasilan akademik siswa juga dapat membantu pengembangan strategi pendidikan yang lebih efektif. Melalui teknik Cross-Validation, validitas model Decision Tree diuji untuk memastikan kinerjanya yang tinggi dalam berbagai lingkungan. Dengan demikian, penelitian ini berpotensi memberikan kontribusi yang signifikan terhadap kebijakan penerimaan siswa baru yang efisien dan berkualitas di SMA Negeri 1 Bandung.

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“…Kendala muncul dalam pemilihan siswa baru karena ketidak-konsistenan dan sifat subjektif penilaian. Oleh karena itu, diperlukan metode identifikasi calon siswa baru di sekolah [3].…”

Section: Pendahuluanunclassified

Analisis Data Penerimaan Peserta Didik Baru Menggunakan Cross Validation Dan Algoritma Decision Tree Di Sma Negeri 1 Bandung

Andriyani,

Kurniawan,

Arie Wijaya

2024

jati

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“…Berkali-kali ditemukan bahwa bermacam-macam informasi menjadi sia-sia sehingga muncul ungkapan "data tombs" yang menyiratkan kuburan informasi. (Winanjaya et al, 2019).…”

Section: Data Miningunclassified

Analisis Tingkat Kepuasan Karyawan Terhadap Fasilitas Hunian Perkebunan Ptpn IV Unit Marjandi Dengan Menggunakan Algoritma C4.5

Yusril Firas Alfaridzi Harahap,

Riki Winanjaya

2023

SAINTEK

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Residential is a place to live or everything related to a place to live and in a narrow sense can be interpreted as a residential area or residential building. In connection with the quality of residential facilities, employee satisfaction is an important aspect in improving the quality of the provided residential facilities. If the satisfaction of the residential facilities provided to employees is not met, the employees will feel uncomfortable and will sue the plantation of PTPN IV Marjandi Unit. Analyze the level of employee satisfaction with the quality of the residential provided by the plantation to its employees is The purpose of this study. One of the efforts to find out the satisfaction of employees of residential facilities is to use the C4.5 algorithm classification, where Dataset is obtained through the Questionnaire technique that will be given to employees at PTPN IV Marjandi Unit. As for the satisfaction of employees of residential facilities in terms of aspects (1) water facilities, (2) electricity facilities, (3) kitchen conditions, (4) bedroom conditions, (5) toilet conditions in dwellings inhabited by PTPN IV Unit plantation employees Marjandi. Data processing is assisted using Microsoft Excel software and to validate study data using a rapidminer tool. It is hoped that this research can provide solutions or become a reference for plantations to improve the quality of residential facilities provided to PTPN IV Marjandi Unit employees..

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“…[4] Data Mining with C4.5 Algorithm can be used to make predictions and classifications of prospective new students in school by making decision trees based on existing data and predicting new prospective students who want to go to SMKS Al-Akhyar II Jakarta. [5] Using this improved algorithm C4.5, the decision tree model is produced and the classification rules are extracted. [6] In algorithm C4.5 is also compares the accuracy of each algorithm so its have a good accurancy.…”

Section: A Data Miningmentioning

confidence: 99%

Application for New Student Admission at SMKS Al-Akhyar II Jakarta with C4.5 Algorithm

Eka Meilan,

Tri,

Bagus

2023

ijaste

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Al-Akhyar II Jakarta Vocational High School (Smk) is a school that has been accredited with A superior. However, the application of new student admissions still has some difficulties in knowing the potential of prospective students who will attend school. This makes schools have to selectmore students who will be accepted at Smks Al-Akhyar IIJakarta.Therefore,a method is needed to identify prospective new students at school. Data Mining with the C4.5 Algorithm can be used to select and classify prospective new students at school by making a decision tree based on existing data and selecting prospective students. Data on prospective students whoregisterandtaketests in the 2019 academic year, 2020 and 2021 will be selected using theC4.5method whichwill latersee students who are accepted at Smks Al-Akhyar IIJakarta. The resultsthat have been tested using training data and comparing thetraining dataandtestingdatahaveanaccuracyof97%using theC4.5method.Testswere also carried out on 89 respondents who agreed that this design was carried out to overcome problems at Smks Al-Akhyar II Jakarta.

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Penerapan Data Mining Untuk Memprediksi Penerimaan Peserta Didik Baru Menggunakan Algoritma C4.5

Cited by 5 publications

References 2 publications

Analisis Data Penerimaan Peserta Didik Baru Menggunakan Cross Validation Dan Algoritma Decision Tree Di Sma Negeri 1 Bandung

Analisis Data Penerimaan Peserta Didik Baru Menggunakan Cross Validation Dan Algoritma Decision Tree Di Sma Negeri 1 Bandung

Analisis Tingkat Kepuasan Karyawan Terhadap Fasilitas Hunian Perkebunan Ptpn IV Unit Marjandi Dengan Menggunakan Algoritma C4.5

Application for New Student Admission at SMKS Al-Akhyar II Jakarta with C4.5 Algorithm

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