IDENTIFIKASI ANALISIS BANTUAN BEASISWA MENGGUNAKAN ALGORITMA C4.5 (STUDI KASUS SD NEGERI 100540)

ULFA UPRONA RAMBEY, NPM 2209100131 (2026) IDENTIFIKASI ANALISIS BANTUAN BEASISWA MENGGUNAKAN ALGORITMA C4.5 (STUDI KASUS SD NEGERI 100540). Skripsi thesis, Universitas Labuhanbatu.

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Abstract

Penentuan penerima bantuan beasiswa di sekolah memerlukan proses seleksi yang objektif agar bantuan dapat diberikan kepada siswa yang benar-benar memenuhi kriteria. Proses seleksi yang masih dilakukan secara manual berpotensi menimbulkan ketidaktepatan dalam pengambilan keputusan sehingga diperlukan pemanfaatan teknologi untuk mendukung proses tersebut. Data mining merupakan salah satu teknik yang mampu menggali informasi dari sekumpulan data untuk menghasilkan pengetahuan yang bermanfaat dalam proses pengambilan keputusan. Algoritma C4.5 merupakan metode klasifikasi yang membentuk pohon keputusan berdasarkan nilai entropy dan information gain sehingga mampu menghasilkan aturan keputusan yang mudah dipahami. Penelitian ini menggunakan metode kuantitatif dengan mengumpulkan data calon penerima beasiswa berdasarkan atribut pendapatan orang tua, jumlah tanggungan, nilai rapor, dan kehadiran. Analisis dilakukan melalui perhitungan entropy, information gain, pembentukan decision tree, serta implementasi menggunakan aplikasi Orange Data Mining. Hasil penelitian menunjukkan bahwa atribut Pendapatan Orang Tua memiliki nilai information gain tertinggi sebesar 0,655 sehingga menjadi akar (root) dalam pembentukan pohon keputusan. Model yang dihasilkan mampu mengklasifikasikan siswa ke dalam kategori layak dan tidak layak menerima bantuan beasiswa berdasarkan aturan keputusan yang terbentuk secara sistematis. Penerapan algoritma C4.5 terbukti mampu membantu proses seleksi penerima bantuan beasiswa menjadi lebih objektif, transparan, dan tepat sasaran. Hasil penelitian ini diharapkan dapat menjadi pendukung pengambilan keputusan bagi pihak SD Negeri 100540 dalam menentukan penerima bantuan beasiswa secara lebih efektif dan berbasis data. Kata Kunci : Data Mining; Algoritma C4.5; Klasifikasi; Bantuan Beasiswa; Decision Tree. ====================================================================== Determining scholarship recipients in schools requires an objective selection process to ensure that assistance is provided to students who truly meet the criteria. The manual selection process has the potential to lead to inaccuracies in decision-making, necessitating the use of technology to support the process. Data mining is a technique capable of extracting information from a data set to generate useful knowledge in the decision-making process. The C4.5 algorithm is a classification method that forms a decision tree based on entropy and information gain values, thus producing easily understood decision rules. This study used a quantitative method by collecting data on prospective scholarship recipients based on attributes such as parental income, number of dependents, report card grades, and attendance. Analysis was carried out through entropy calculations, information gain calculations, decision tree formation, and implementation using the Orange Data Mining application. The results showed that the Parental Income attribute had the highest information gain value of 0.655, thus becoming the root in the decision tree formation. The resulting model was able to classify students into eligible and ineligible categories for scholarship assistance based on systematically formed decision rules. The application of the C4.5 algorithm has been proven to help the scholarship recipient selection process become more objective, transparent, and targeted. The results of this study are expected to support decision-making for SD Negeri 100540 in determining scholarship recipients more effectively and based on data. Keywords : Data Mining; C4.5 Algorithm; Classification; Scholarship Assistance; Decision Tree.

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	Data Mining; Algoritma C4.5; Klasifikasi; Bantuan Beasiswa; Decision Tree. ===================================== Data Mining; C4.5 Algorithm; Classification; Scholarship Assistance; Decision Tree.
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General)
Divisions:	Fakultas Sains Dan Teknologi > Sistem Informasi
Depositing User:	Unnamed user with email repository@ulb.ac.id
Date Deposited:	07 Sep 2026 03:14
Last Modified:	07 Sep 2026 03:14
URI:	http://repository.ulb.ac.id/id/eprint/2770

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