PREDIKSI KETERLAMBATAN PEMBAYARAN IURAN SANTRI MENGGUNAKAN ALGORITMA DECISION TREE

PUSPA ANGGRAINI, NPM 2208100116 (2026) PREDIKSI KETERLAMBATAN PEMBAYARAN IURAN SANTRI MENGGUNAKAN ALGORITMA DECISION TREE. Skripsi thesis, Universitas Labuhanbatu.

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Abstract

Penelitian ini dibuat karena adanya masalah di Pondok Pesantren Darussholihin Labuhanbatu, di mana banyak wali santri yang telat membayar iuran bulanan. Padahal, uang iuran ini sangat penting untuk membiayai kegiatan belajar dan operasional pesantren sehari-hari. Selama ini, pihak pesantren biasanya baru bergerak menagih kalau pembayarannya sudah lewat tanggal jatuh tempo. Cara ini kurang efektif karena memakan banyak waktu dan tenaga. Oleh karena itu, penelitian ini mencoba mencari cara supaya pesantren bisa memprediksi santri mana saja yang kira-kira bakal telat bayar sebelum waktunya tiba. Caranya adalah dengan menggunakan teknik "Data Mining" melalui algoritma bernama Decision Tree C4.5. Algoritma ini bekerja dengan cara mempelajari data pembayaran santri di masa lalu untuk menemukan pola tertentu. Tujuannya adalah untuk membangun sebuah sistem peringatan dini agar pesantren bisa lebih proaktif dalam mengelola keuangan. Dengan sistem ini, pihak manajemen bisa tahu faktor apa saja yang paling sering membuat pembayaran telat dan bisa mengambil tindakan pencegahan lebih awal. Harapannya, keuangan pesantren jadi lebih stabil dan kegiatan belajar mengajar santri tidak terganggu. Kata Kunci : Data Mining, Decision Tree C4.5, Pondok Pesantren, Prediksi Pembayaran, Sistem Peringatan Dini ================================================================================================ This research was conducted due to issues at the Darussholihin Islamic Boarding School in labuhanbatu, where many guardians are late in paying monthly fees. These fees are critical for funding daily educational activities and boarding school operations, previously, the administration typically took action to collect payments only after the due date had passed. This method proved ineffective as it was time consuming and labor-intensive. Therefore, this study aims to find a way for the school to predict which students are likely to be late with there is achieved by utilizing “Data Mining” techniques though the Decision Tree C4.5 algoritma. This algorithm works by analysing past student pay ment data to identify specific patterns. The objective is to build early warning system that allows the boarding school to be more proactive in financial management. With this system, management can identify the most frequent factors causing late payments and take preventive measures earlier. It is hoped that the school’s finances will become more stable and that the students’ learning activities will remain undisturbed Keywords : Data Mining, Decision Tree C4.5, Boarding School(Pesantren), Payment Prediction, Early Warning System

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	Data Mining, Decision Tree C4.5, Pondok Pesantren, Prediksi Pembayaran, Sistem Peringatan Dini=================Data Mining, Decision Tree C4.5, Boarding School(Pesantren), Payment Prediction, Early Warning System
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Divisions:	Fakultas Sains Dan Teknologi > Teknologi Informasi
Depositing User:	Unnamed user with email repository@ulb.ac.id
Date Deposited:	20 May 2026 02:35
Last Modified:	20 May 2026 02:35
URI:	http://repository.ulb.ac.id/id/eprint/2348

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