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irma yunita
Jurusan Teknologi Hasil Pertanian Fakultas Teknologi Pertanian Universitas Brawijaya
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Journal : G-Tech : Jurnal Teknologi Terapan

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Mental Health Diagnosis (Chronic Fatigue Syndrome and Depression) using Decision Tree Algorithm Zubairi, Ach.; Homaidi, Ahmad; Yunita, Irma; Prasetyo, Jarot Dwi; Hermanto, Hermanto
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7595

Abstract

Mental health is an important aspect that affects an individual's life, impacting productivity, social relationships and overall quality of life. The World Health Organization (WHO) states that one in four people worldwide will face mental health challenges. With the increasing incidence of conditions such as depression and Chronic Fatigue Syndrome (CFS), effective detection and intervention methods are urgently needed. Data mining, specifically using Decision Tree algorithms, presents a promising approach to address this challenge. This study utilizes a quantitative methodology to classify depression and CFS patients using a public dataset. The data collection from Kaggle included variables such as demographics and clinical evaluations, consisting of 1,000 records and 15 predictive attributes. Data preprocessing addressed noise, specifically missing values, to ensure model accuracy above 80%. A Decision Tree was implemented, displaying the interpretability of the method by partitioning the data based on the selected attributes. Evaluation metrics such as accuracy, precision, recall, and F1 score showed accuracy of 99% and precision and recall of 100%. The results emphasize the potential of the Decision Tree in distinguishing between depression and CFS, enabling early intervention through accurate patient identification. This study advocates the integration of such machine learning models into clinical practice to improve mental health diagnostics and management, by addressing an important aspect of public health.
Co-Authors Abdul Rahman ABDUS SAMAD Ach. Zubairi ACHMAD RIFAI Ade Yuliana, Ade Adibah, Fanny Afandi, Muhammad Dzikry Afifah, Fatma Nur Afini, Dewi Ahmad Homaidi AHMAD LUTFI Akbar, Mohammad Ghiyats Sayyid Alawiyah, Siti Alida, Ravi Anhari Achadi Antonius, Rudy Apriliyani, Femi Azwar Anas Dailami, D. Darul Ilmi Devi, Ulma Dwi Yuniar Ramadhani E. Egriana Handayani Edi Mulyadi Efendi, Ahmad Fadil Dwi Elmira, Via Fahri, Alvin Fajri, Ahmad Maulana Fajriyanto Fajriyanto Fatah, Zaehol Fikrianda, Rifki Fikriyani, Devi Nurul Gunawan, Aan Halilatul Muallafa Harsiti Harsiti, Harsiti Hasani, Nurul Hermanto Hermanto herpratiwi Homaida, Nur Ikmal, Muhammad Jannah, Nadyya Zahratul Junaidi Junaidi Juniansha, Dedi KIKI FIBRIANTO Komalasari, Siti Kusumo, Rangga Lidimilah, Lukman Fakih Lidinillah, Lukman Faqih Lisa Rahmawati Lutfi, Zainul Mahundingan, Rosari Oktaviana Maman Saputra, Maman Marsita, Yuni Muhamad Sofian Hadi Muhammad Fahri, Muhammad Mulyana, Emul Mutia, M. Nabila, Intan Okta Nida Jarmita Nooraeni, Endah Novelia Kiki Permatasari Nur Indahsari, Luluk Nurhasanah, Yeni Nurhuda, Ridha Nurlela Nurlela Nurmi Pande Made Kutanegara Prasetyo, Jarot Dwi Purbawati Naprilia, Tania Putri Rahmi Qori'ah, Arafah Amaliyah Rahayu Wulaning Rahmat Mulyana Dali Ramadhani, Indah Relin, Relin Rini, Nurlita Arinda Risvy, Berliani Ananda Rusdi, Farhannuddin Rusdianah, Iim Safitri, Lulu Saleh, Taufik Saputri, Indah Dwi Sari, Nurlinda Sari, Suci Prihatini Noer mala Sinta, Sinta Masruroh Siregar, Jamaluddin Sobri, Miftahus Subiyantoro, Hari Sudarma Dita Wijayanti Suhairi Suhairi Suhendi, Dadi Sulistianah Sundarta, Muhamad Imam Susilawati, Susilawati Sutihat, Eva Syafrizal, Muhammad Syiarudin, Asep Taufik Hidayat Triwoelandari, Retno Triyadi, Riyan Usman Usman, Andi Usri Verina, Kiki widad, ruqoyyatulwidad Widiya, Ulva yul Hendra Zainarti Zainarti Zubairi, Ach. Zulfah, Maria