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Hamdani
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Journal : Indonesian Journal of Data and Science

 1 
Grid Search Hyperparameter Analysis in Optimizing The Decision Tree Method for Diabetes Prediction Anggreani, Desi; Hamdani; Nurmisba; Lukman
Indonesian Journal of Data and Science Vol. 5 No. 3 (2024): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v5i3.190

Abstract

Diabetes is a global health issue that continues to rise, especially in Indonesia, caused by unhealthy lifestyles, poor diets, and genetic factors. Early detection of diabetes risk is crucial to prevent serious complications, and machine learning offers innovative predictive solutions. This research focuses on the development of a diabetes risk prediction model using the Decision Tree algorithm with hyperparameter optimization through the Grid Search technique. The research methodology includes the collection of patient medical data with key attributes such as glucose levels, blood pressure, skin health, insulin, body mass index (BMI), diabetes pedigree, age, and health history. The hyperparameter tuning process is carried out by varying key parameters such as the maximum tree depth (max_depth), the minimum number of samples required to split a node (min_samples_split), and the minimum number of samples required at a leaf node (min_samples_leaf). Grid Search is used to systematically explore hyperparameter combinations in order to find the optimal configuration that can improve the model's performance. The research process includes data preprocessing, splitting the dataset into training and testing sets, model training, and evaluation using accuracy metrics, confusion matrix, and ROC AUC curve. The initial results show a model accuracy of 76%, which was then improved to 81% after hyperparameter optimization using Grid Search. The visualization of the decision tree reveals that glucose levels and BMI have the most significant contributions in predicting diabetes risk. This research demonstrates the potential of machine learning in supporting the early detection of diabetes, with the Decision Tree algorithm showing promising predictive capabilities. Nevertheless, further research with larger datasets and the integration of other algorithms is highly recommended to improve the accuracy and generalization of the model. The main contribution of this research is the development of a machine learning-based approach that can assist medical personnel in screening for diabetes risk more efficiently and accurately.
Co-Authors -, M Saleh Abdul Holik, Abdul Ade Mirza Adi Sastra Pengalaman Tarigan Adisastra Pengalaman Tarigan Afriana Agung Hartoyo Agustin Agusviyanda Agusviyanda Ahmad Alim Bachri Ahmad Yani T Aida Alahuddin Ali Nurhadi Alin Riani Alvina Anggraini Alwi Amanti, Anggi Tias Ambar Lukitaningsih Anam, M Khairul Andarini Rani Prabowati Andi Azhar, Andi Azhar Andi Tenri Kawareng Andri Setiadi Anggreani, Desi Anria, Reni Aqiilah, Dian Ariani, Linda Asparizal As’ady, Mustofa Atma Hayat Audina, Nia Aulia Sandhi Kurniawan Ayu Oktaviani, Ayu Azwar Yunus Beni Satria Charli, Chintya Ones Darul Ilmi Dede Suratman Dhea Zatira Dimyati, Arjun Dwi Patlan Dona Fitriawan Dyah Nuri Mardania Edy Yusmin Elsa Audia Utami Eni Suharti Erlinda, Susi Fauzah Nur Aksa Febrianto, Hendra Galuh Firman Hakiki Fuadi Gadis Afriani Gadis Ayu Rizky Darmala Galang Reza Firdaus Budiutomo Ganefi Gerrit M. Pentury Gunadi Guslaili, Rafika Gustiar Martua Siregar Hadi Asnal, Hadi Hakim Muttaqim Hakim, Mohamad Zulman Hakim, Syahirman Hartoyo , Agung Hasbi Helen Retno Wulandari Heni Listiana Hikmatul Fadhilah Sianipar Hilmi Hilmi Husni Pasarela Hustna Dara Sarra Ida Ayu Putu Sri Widnyani Ihsanuddin Ilham Nuzul Firman Illahi, Kurnia Fitri Imam Hidayat Intan Rahmawati IRWANSYAH Ismail Isnan Murdiansyah Iswadi Jamaris, Muhammad Joko Susetyanto Jordy, Steven Julpandi Jungjungan, Muhammad Arisandi Kholdi, Faldini Kudadiri, Parlindungan Lukman M. Rasyidin M. Rimawan Maghfirah, Nurul Mahmud Maimun Markus Suryoutomo Mazidah, Isti'anatul Melinda Wijaya Melsa Putri Mochamad Ridwan Moh. Fathur Rohman mohamad rifat Mohammad Ali Al Humaidy Mohammad Solekhan Mokhlis Muchamad Arif Al Ardha Muchimah Muhammad Arief Solihin Muhammad Bambang Firdaus Muhammad Dirhamsyah Muhammad Habil Muhammad Hatta Muhammad Rasyid Ridha MUHAMMAD RIZAL Muhammad Rusdiansyah Muhammad Shohibuddin Muhibuddin Mukhtar Mulyani, Nani N.A, Randi Nafa Salsabila Ni Made Dwi Puspitawati Nonik Kusuma Ningrum Nor Hikmah Norlena Novika Rosari Nugraha, Billy Nur Efendy, Agik Nur Sulistyo Budi Ambarini Nurcahya Nurfadilah Siregar Nuri Wahda Salsabila Usmany Nurmasyitah Nurmisba Ovriyaidn Pangesti, Rizka Dhilla Dwi Pasaribu, Revi Lestari Permatasari, Reskia Dwi Pratama, Rizky Puji Muniarty Puput Qomaruddin Rahma Fitri Rahmaddeni Rahmaddeni Ramadhan, Yogi Rifansyah Rika Savitri Rikko kurnia fitra Rikko kurnia fitra Rini Andriani Rizka Donny Agung Saputra Robiatul Andawiyah Rohwati, Siti Romi Asmara Rustam Efendi Saiful Bahgia Saleh, M Sandy Prabowo Sapto Wibowo Saputra, Syifa Sari Yulis Terfiadi Saryana Septiza Siti Lathifah, Suci Slamet Sofyan Jafar Soleha Sonia Nadia Muslimah Sopan Hidayat Sri Murni Sri Sudono Saliro Sugiatno . Suharno, Muhammad Iqbal Susandri, Susandri SUSANTI Susetyanto, Joko SUSI ERLINDA Sustari Alamsyah Syabarrudin, Agus Syadella Nur Aqilla Syaiful Amin T.Sy Eiva Fadha Tahir, Muhlis Tajul Munir Teuku Yudi Afrizal Thorik Satria Ilmi Tiara Tomo Djudin Triyani Arita Fitri Udiannoor Ulfah Fajarini Uliyah, Siti Wahyu WAHYUDI Wahyudin Wedra Aprison Winata, Nugraha Pandu Yanti, Asri Vivi Yola Dyfa Meisari Yonnedi, Efa Yudith Evametha Vitranilla Zulfadli