Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Umpak : Jurnal Arsitektur dan Lingkungan Binaan Scientific Journal of Informatics
Mariyana, Ekanata Desi Sagita
Unknown Affiliation
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Environmental Science

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Mental Health Chatbot Application on Artificial Intelligence (AI) for Student Stress Detection Using Mobile-Based Naïve Bayes Algorithm Mariyana, Ekanata Desi Sagita; Novita, Mega; Nur Latifah Dwi Mutiara Sari
Scientific Journal of Informatics Vol. 12 No. 2: May 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i2.24307

Abstract

Purpose: This study aims to design and evaluate a chatbot-based artificial intelligence system to identify stress levels in students using the Naïve Bayes classification method. With increasing mental health concerns among students, early stress detection is considered crucial for timely intervention Methods: This study proposes an AI-based chatbot system to detect student stress levels using a comparative approach between Naïve Bayes and Support Vector Machine (SVM) algorithms. A Kaggle dataset with 15 psychological and academic indicators was preprocessed and balanced using SMOTE. Naïve Bayes showed higher accuracy (90%) than SVM (89%). The trained model was deployed via Flask with Ngrok tunneling and integrated into a Flutter mobile app connected to the Gemini AI API for real-time stress screening. This research offers a practical and scalable solution for early mental health detection in students through intelligent chatbot interaction. Result: The findings show that the Naïve Bayes model achieves a classification accuracy of 90%, slightly surpassing the SVM model, which records an accuracy of 89%. Evaluation through ROC and AUC metrics supports the reliability of Naïve Bayes in detecting stress levels. The integrated chatbot offers a responsive and engaging platform for preliminary mental health assessments. Novelty: This research presents a unique contribution by combining AI-driven stress detection with a real-time chatbot interface, offering an accessible and scalable approach to student mental health support. The integration of machine learning models with conversational AI provides an innovative solution for early intervention. Future developments may involve deep learning and more diverse psychological inputs to further improve accuracy and effectiveness.
Analisis Penerapan Coolroofs Pada Bangunan Balai Rw Sebagai Langkah Mitigasi Pemanasan Global Di Kota Semarang Roni, Muhamad; Mariyana, Ekanata Desi Sagita
UMPAK : Jurnal Arsitektur dan Lingkungan Binaan Vol 2, No 1 (2019): Maret
Publisher : Program Studi Arsitektur, Fakultas Teknik dan Informatika, Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/umpak.v2i1.20215

Abstract

Global warming menjadi permasalahan utama yang menyebabkan meningkatnya suhu di permukaan bumi, memicu terjadinya kekeringan, dan memicu terjadinya kebakaran hutan. Namun, global warming kini juga berdampak terhadap bangunan seperti memanasnya permukaan bangunan dan mengakibatkan panas hingga kedalam ruang bangunan, yang dimana bangunan merupakan ruang kehidupan manusia masa  kini.  Dilakukannya  penelitian  ini  yaitu  untuk  mengetahui  dampak  dari  penerapan  prinsip coolroofs pada sebuah bangunan dengan menggunakan cat reflektif surya sebagai langkah awal mitigasi pemanasan global, khususnya bangunan dengan atap material asbes yang dimana karakteristik material tersebut memiliki daya serap panas yang cukup tinggi. Penelitian ini bertujuan mengetahui efektivitas penggunaan cat reflektif surya pada sebuah bangunaan khususnya dengan atap material asbes. Untuk mengetahui hasil dari penggunaan cat reflektif surya, peneliti melakukan pengukuran pada dua bagian bangunan yaitu suhu ruang utama dan temperatur permukaan atap. Pada penelitian ini terdapat data komparasi suhu yang membuktikan cat reflektif surya dapat mereduksi panas.
Co-Authors Mega Novita Nur Latifah Dwi Mutiara Sari Roni, Muhamad