Prediksi Tingkat Kesehatan Mental Pelajar Menggunakan Algoritma C4.5 Berbasis Knime Analytics Platform: Penelitian

Clarence Sinulingga; Cholil Tamami; Ahmad Gibran Al Ayubbi Maulana; Shafarani Aulia; Muhammad Adrian Eka Pratama; Muhammad Zidane Dinovsyach

doi:10.31004/jerkin.v4i3.4957

Authors

Clarence Sinulingga Universitas Bina Sarana Informatika
Cholil Tamami Universitas Bina Sarana Informatika
Ahmad Gibran Al Ayubbi Maulana Universitas Bina Sarana Informatika
Shafarani Aulia Universitas Bina Sarana Informatika
Muhammad Adrian Eka Pratama Universitas Bina Sarana Informatika
Muhammad Zidane Dinovsyach Universitas Bina Sarana Informatika

DOI:

https://doi.org/10.31004/jerkin.v4i3.4957

Keywords:

Student Mental Health, C4.5, KNIME Analytics Platform, Data Mining, Classification

Abstract

The development of Artificial Intelligence technology in the field of facial image processing has encouraged the emergence of various methods for automatically analyzing human attributes. This study implements the DeepFace and OpenCV libraries to detect faces and predict age and gender based on human facial images. DeepFace provides integration with various pre-trained models such as VGG-Face, OpenFace, and DeepID so that the analysis process can be carried out without retraining. This study uses several stages starting from image upload, face detection, facial attribute analysis, and visualization of the prediction results. From the tests conducted, the system successfully identified faces stably and provided relatively accurate age and gender estimates, especially in images with sufficient lighting and frontal facial poses. The results of this study indicate that DeepFace can be used as a practical solution in the development of facial image-based biometric systems.

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