Penerapan Algoritma C4.5 dalam Klasifikasi Status Gizi Balita
Abstract
Posyandu in Dawuan Barat determines the nutritional status of children by looking at the growth chart in KIA and calculating the z-score manually and then matching the results to the category table and threshold, this takes a long time and is at risk of being inaccurate. The formulation of the problem in this study is how to do classification of data mining to determine the nutritional status of toddlers and how the evaluation results from the classification model. This study uses the C4.5 algorithm with the CRISP-DM methodology to classify the nutritional status of toddlers and uses a confusion matrix to determine the accuracy, precision, recall and f1-score values of the classification model and then the model is implemented into an application. The evaluation results of the 3 model scenarios in this study stated that scenario 1 produced the best performance among other models with 90% accuracy and 87% value of precision, recall and f1-score
References
Bappenas. (2018). Pedoman Pelaksanaan Intervensi Penurunan Stunting Terintegrasi Di Kabupaten/ Kota. Kementerian Perencanaan Pembangunan Nasional.
Enterprise, J. (2019). Python untuk Programmer Pemula. Elex Media Komputindo.
Heroku. (n.d.). Heroku. Heroku.Com. Retrieved April 13, 2022, from https://www.heroku.com/
Irsyad, R. (2018). Penggunaan Flask untuk Pemula. 1–4.
Lukhayu Pritalia, G. (2018). Penerapan Algoritma C4.5 untuk Penentuan Ketersediaan Barang E-commerce. Indonesian Journal of Information Systems, 1(1). https://doi.org/10.24002/ijis.v1i1.1727
Marniati. (2021). Manajemen Pemanfaat Posyandu Balita (T. Hidayati, Ed.). Pena Persada.
Marsita, M. (2018). Implementasi algoritma decision tree C4.5 untuk mengidentifikasi gizi balita berdasarkan indeks antropometri: studi kasus posyandu Seruni. UIN Sunan Gunung Djati.
Molina, J., & Soetanto, H. (2021). Optimalisasi Kinerja Hasil Komparasi Algoritma C4.5 dan Naive Bayes Menggunakan Particle Swarm Optimization untuk Deteksi Dini Penentuan Status Gizi pada Balita. Deepublish.
Nugroho, K. S. (2019). Confusion Matrix untuk Evaluasi Model pada Supervised Learning. Medium.Com.
Python. (n.d.). The Python Standard Library. Docs.Python.Org. Retrieved April 13, 2022, from https://docs.python.org/3/library/
Riani, A., Susianto, Y., & Rahman, N. (2019). Implementasi Data Mining Untuk Memprediksi Penyakit Jantung Mengunakan Metode Naive Bayes. Journal of Innovation Information Technology and Application (JINITA), 1(01). https://doi.org/10.35970/jinita.v1i01.64
Ridwan, A., Andono, P., & Supriyanto, C. (2018). Optimasi Klasifikasi Status Gizi Balita Berdasarkan Indeks Antropometri Menggunakan Algoritma Naive Bayes Classification Adaboost. Jurnal Teknologi Informasi. http://research.pps.dinus.ac.id/index.php/Cyberku/article/download/76/72
Saleh, H., Informatika, J. T., & Komputer, F. I. (2020). Analisa Faktor Penyebab Stunting Menggunakan Algoritma C4 . 5. Scientico: Computer Science and Informatics Journal, 3(1).
Schröer, C., Kruse, F., & Gómez, J. M. (2021). A systematic literature review on applying CRISP-DM process model. Procedia Computer Science, 181. https://doi.org/10.1016/j.procs.2021.01.199
Suprijono, S. A., Setianingsih, C., & Saputra, R. E. (n.d.). Deteksi Tinggi Rendah Gelombang Air Laut Dengan Multisensor Menggunakan Algoritma Fuzzy Sukamoto High And Low Sea Waves Detection With Multisensor Using Fuzzy Sukamoto Algoritm.
Syaputro, & Widya, R. (2022). Pemanfaatan Bot Api Telegram Pada Sistem Manajemen (Studi Kasus UKM Informatika dan Komputer). Digilab STMIK AKAKOM.
Tim Nasional Percepatan Penanggulangan Kemiskinan. (2017). 100 Kabupaten/Kota Prioritas untuk Intervensi Anak Kerdil (Stunting).
Wahyudi, R., Orisa, M., & Vendyansyah, N. (2021). Penerapan Algoritma K-Nearest Neighbors Pada Klasifikasi Penentuan Gizi Balita (Studi Kasus Di Posyandu Desa Bluto). Jati (Jurnal Mahasiswa Teknik Informatika), 5(2). https://doi.org/10.36040/jati.v5i2.3738
Wahyudin, W. (2020). Klasifikasi Stunting Balita Menggunakan Naive Bayes Dengan Seleksi Fitur Forward Selection. Jurnal Bisnis Digitasl Dan Sistem Informasi, 1. https://ejr.stikesmuhkudus.ac.id/index.php/jikoma/article/viewFile/1220/760
Wanto & Anjar, D. (2020). Data Mining : Algoritma dan Implementasi - Books. In Yayasan kita menulis.
