AURELIA, NADYA (2026) IMPLEMENTASI SISTEM BACK-END PADA WEBSITE BABUDDY UNTUK PEMANTAUAN KESEHATAN PENCERNAAN DENGAN ALGORITMA RANDOM FOREST. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
Digestive health is an essential aspect of maintaining the body's overall well-being. However, many individuals tend to overlook changes in their bowel movement patterns, even though information such as bowel movement frequency, stool characteristics, the presence of blood in the stool, as well as water intake and dietary habits can serve as indicators for assessing digestive health. Based on this issue, this study aims to design and implement the back-end system of the BABuddy website as a platform for monitoring and analyzing users' digestive health. This study employed the Waterfall development method, which consists of the requirements analysis, system design, implementation, and testing phases. The back-end system was developed using the Laravel framework with a RESTful API architecture and a MySQL database to manage user data and digestive health records. In addition, the Random Forest algorithm was implemented to classify users' digestive health conditions based on the collected data. The results show that the BABuddy back-end system is capable of efficiently managing digestive health data, providing user authentication services, recording bowel movement activities, water intake, and food consumption, as well as generating digestive health predictions using the Random Forest algorithm. Based on the evaluation using the Confusion Matrix, Accuracy, Precision, Recall, F1- Score, and K-Fold Cross Validation, the Random Forest model demonstrated satisfactory classification performance, indicating its potential to support digestive health monitoring. It is expected that the developed system will encourage users to better understand their digestive health and promote independent health monitoring through the use of digital technology. Keywords: Back-end, Digestive Health, Laravel, BABuddy, Random Forest Algorithm. Kesehatan pencernaan merupakan salah satu aspek penting dalam menjaga keseimbangan tubuh secara menyeluruh. Namun, banyak individu cenderung mengabaikan perubahan pola buang air besar (BAB), padahal informasi mengenai frekuensi BAB, karakteristik feses, keberadaan darah pada feses, serta kebiasaan konsumsi air dan pola makan dapat menjadi indikator dalam menilai kondisi kesehatan pencernaan. Berdasarkan permasalahan tersebut, penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem back-end pada website BABuddy yang berfungsi sebagai media pemantauan dan analisis kesehatan pencernaan pengguna. Metode penelitian yang digunakan adalah metode Waterfall yang meliputi tahapan analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Sistem back�end dikembangkan menggunakan framework Laravel dengan arsitektur RESTful API serta basis data MySQL untuk mengelola data pengguna dan riwayat kesehatan pencernaan. Selain itu, penelitian ini menerapkan algoritma Random Forest untuk melakukan klasifikasi kondisi kesehatan pencernaan berdasarkan data yang dikumpulkan dari pengguna. Hasil penelitian menunjukkan bahwa sistem back-end BABuddy mampu mengelola data kesehatan pencernaan secara efisien, menyediakan layanan autentikasi pengguna, pencatatan aktivitas buang air besar (BAB), konsumsi air, dan asupan makanan, serta menghasilkan prediksi kondisi kesehatan pencernaan menggunakan algoritma Random Forest. Berdasarkan hasil evaluasi menggunakan Confusion Matrix, Accuracy, Precision, Recall, F1-Score, dan K-Fold Cross Validation, model Random Forest menunjukkan performa klasifikasi yang cukup baik sehingga dapat dimanfaatkan sebagai pendukung proses pemantauan kesehatan pencernaan. Dengan adanya sistem ini, diharapkan pengguna dapat lebih memahami kondisi kesehatan pencernaannya serta terdorong untuk melakukan pemantauan secara mandiri melalui pemanfaatan teknologi digital. Kata kunci: Back-end, Kesehatan Pencernaan, Laravel, BABuddy, algoritma Random Forest
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