Hybrid Decision Tree Method and C4.5 Algorithm for a Recommendation System in Determining Recipients of Direct Cash Assistance (BLT)

Rio Rizq Nur Bhactiar; Dwi Hartanti; Harsanto

doi:10.47709/cnahpc.v5i2.2414

Authors

Rio Rizq Nur Bhactiar S1 Program - Informatics Engineering, Duta Bangsa University, Surakarta, Indonesia
Dwi Hartanti Duta Bangsa University, Surakarta, Indonesia
Harsanto Duta Bangsa University, Surakarta, Indonesia

DOI:

10.47709/cnahpc.v5i2.2414

Keywords:

Recommendation System, BLT, C4.5 Algorithm, Decision Tree, Hybrid Method

Dimension Badge Record

Abstract

Development of a recommendation system to determine recipients of Direct Cash Assistance (BLT) using the C4.5 algorithm hybrid method and decision tree. In the current era of digitalization, the BLT program is a solution for the Indonesian government to help people affected by the COVID-19 pandemic. In this study, we propose a recommendation system that combines the C4.5 algorithm and a decision tree to increase accuracy and efficiency in determining BLT beneficiaries. Primary data was obtained through interviews and observations, while secondary data was obtained from the village administration, written reports, journals, theses and previous research. The results showed that the C4.5 algorithm and decision tree hybrid method gave good performance in determining BLT recipients. The C4.5 algorithm is used to calculate the accuracy of the training data and testing data with a ratio of 80% : 20%, while the decision tree is used to create a decision tree that classifies prospective BLT recipients. This research fills in the previous research gap regarding the recommendation system for determining BLT beneficiaries. The results of this study are expected to provide useful information for the government in making decisions regarding the BLT program, especially at the village or sub-district level. With an accurate and efficient recommendation system, financial assistance can be provided to those who really need it, helping to meet the basic daily needs of affected communities.

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Author Biography

Rio Rizq Nur Bhactiar , S1 Program - Informatics Engineering, Duta Bangsa University, Surakarta, Indonesia

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Abstract viewed = 208 times

References

Arumdani, N., Rahmania, S. N., Nafi’ah, Z., & Tukiman, T. (2021). Efektivitas Bantuan Langsung Tunai Dana Desa (BLTDD) di Desa Mojoruntut Kecamatan Krembung Kabupatensidoarjo. Jurnal Indonesia Sosial Teknologi, 2(5), 874–885. https://doi.org/10.36418/jist.v2i5.143

Harman, R. (2022). PENERAPAN ALGORITMA C4.5 UNTUK MEMPREDIKSI PROFIT PENJUALAN. 07(02).

Indonesia, B. (2023, Maret 29). Data Inflasi. Data Inflasi. https://www.bi.go.id/id/statistik/indikator/data-inflasi.aspx

Makbul, M. (2021). Metode Pengumpulan Data dan Instrumen Penelitian [Preprint]. Open Science Framework. https://doi.org/10.31219/osf.io/svu73

Muliawan, A., Badriyah, T., & Syarif, I. (2022). Membangun Sistem Rekomendasi Hotel dengan Content Based Filtering Menggunakan K-Nearest Neighbor dan Haversine Formula. Technomedia Journal, 7(2), 231–247. https://doi.org/10.33050/tmj.v7i2.1893

Munawar, Z. (2019). Aplikasi Registrasi Seminar Berbasis Web Menggunakan QR Code pada Universitas XYZ. TEMATIK, 6(2), 128–151. https://doi.org/10.38204/tematik.v6i2.246

Novianti Indah Putri, Rustiyana, Yudi Herdiana, & Zen Munawar. (2021). Sistem Rekomendasi Hibrid Pemilihan Mobil Berdasarkan Profil Pengguna dan Profil Barang. TEMATIK, 8(1), 56–68. https://doi.org/10.38204/tematik.v8i1.566

Nuastiko, R. I., Udjianto, D. W., & Sodik, J. (2022). Pengaruh Indikator Perekonomian di Sektor Ketenagakerjaan Terhadap Inflasi di Indonesia Tahun 1999 – 202.

Partogi, Y., & Pasaribu, A. (2022). Perancangan Metode Decision Tree Terhadap Sistem Perpustakaan STMIK Kuwera. Jurnal Sistem Informasi dan Teknologi (SINTEK), 1(2), 20–25. https://doi.org/10.56995/sintek.v1i2.4

Prasetio, A. (2021). Simulasi Penerapan Metode Decision Tree (C4.5) Pada Penentuan Status Gizi Balita. Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI), 4(3), 209–214. https://doi.org/10.32672/jnkti.v4i3.2983

Putri, S. U., Irawan, E., & Rizky, F. (2021). Implementasi Data Mining Untuk Prediksi Penyakit Diabetes Dengan Algoritma C4.5. 2(1).

Rizki, M., Devrika, D., Umam, I. H., & Lubis, F. S. (2020). Aplikasi Data Mining dalam Penentuan Layout Swalayan dengan Menggunakan Metode MBA. Jurnal Teknik Industri: Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri, 5(2), 130. https://doi.org/10.24014/jti.v5i2.8958

Sahi, A. (2020). APLIKASI TEST POTENSI AKADEMIK SELEKSI SARINGAN MASUK LP3I BERBASIS WEB ONLINE MENGGUNAKAN FRAMEWORK CODEIGNITER. TEMATIK, 7(1), 120–129. https://doi.org/10.38204/tematik.v7i1.386

Sunarti, S., & Handayanna, F. (2022). Penerapan Algoritma C4.5 Untuk Memprediksi Keluhan Pelanggan Pada Apartemen Jakarta. Techno.Com, 21(4), 868–877. https://doi.org/10.33633/tc.v21i4.6844

Tumbel, R., Kiyai, B., & Mambo, R. (2021). DAMPAK KEBIJAKAN PROGRAM BANTUAN LANGSUNG TUNAI DENGAN KONDISI EKONOMI MASYARAKAT DI KELURAHAN TALIKURAN KECAMATAN KAWANGKOAN UTARA KABUPATEN MINAHASA. 110.

Utami, F. H. (2022). Aplikasi Pelayanan Antrian Pasien Menggunakan Metode FCFS Menggunakan PHP dan MySQL.

Utomo, D. P., & Mesran, M. (2020). Analisis Komparasi Metode Klasifikasi Data Mining dan Reduksi Atribut Pada Data Set Penyakit Jantung. JURNAL MEDIA INFORMATIKA BUDIDARMA, 4(2), 437. https://doi.org/10.30865/mib.v4i2.2080