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Journal : Indonesian Journal of Data and Science

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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 A. Alifiya Tenriesa A. Melantik Rompegading A.A. Ketut Agung Cahyawan W Abdul Rahim Achmad Tarmidzi Anas Adiansyah, Romi Adnan , Andi Astinah Agus Eko Sujianto Agus Sugianto Ahmad Khudhory Ainul Mardiana Aji Prasetyo, Aji Aldetia Farendi Aliya Farsya Amelia Defrianti Putri Ana Mardiana Andi Hasriani Andi Nadila Putri Faisah Andi Nasrawaty Hamid Andi Nurahmy M Andi Uceng Andini Fairuz Alifah Anggreani, Desi Anthony Holly Apriani, Fitria Arifin, Muh. Indra Ariyani, Etika Asad, Muh.Arisal Asbah Asfar, Andi Muhamad Iqbal Akbar Asfar, Andi Muhammad Irfan Tauvan Asri Ainun Astinah, Andi BADRUS SOFI Badrut Ali Bakti, Rizki Yusliana Baydowi, Wildi Bella Putri Amelia Burhan Nudin Dadang Juandi Dalle, Asriah Dwi Saputra, Yoggi Edi Edison Emigawaty Eneng Isti Alpiyanti Erna Fadillah, Ardana Fadlillah Fawwaz Sakhi Faturrahman Fiatur Rocmah Firman Nugraha Putra Firzhal Arzhi Jiwantara Fitriah Gita Maharani Hasanuddin Gede Harimbawa Gunaedy Utomo H. Nashiruddin Pilo Hadi, Abd Karim Hamdani Hapzi Ali Hayat, Muhyiddin A M Herwandi Sape Hidaya Hijril Ismail, Hijril Hilwa Anwar Ichsan Syahputra Ihwan Ika Citra Pratiwi Irma Andrianti Irna Ningsi Amalia Rachmna Ismail Jarnawi A. Dahlan Jasin, Hamida A. Julia Julianti Jumriani Juraid Abdul Latief Jusu, La Khaerul Ihsan Lamanda Lintang Lestari Lesmana Prawira Kusumah LILIS DWI FARIDA Limbunan, Excel M. Nasrul Asis M. Samsul Arifin Mahfud M Gamar Mahyuddin Malik, Sayuti Manipi, Ilham Mardiana, Ana Marlina Marselinus Asri Mashudi Mashuri Maulidin Melany Mustika Dewi Miftahul Ulum Mila Karmila Mila Tamrin Mirza Avicenna Asyifyan Misnah Misnah Mohammadong Mubarokhah, Lailatul Muchlis, Khaerunnisa Muhammad Ashraful Annam Muhammad Daffa Imaduddin Muhammad Faisal Muhammad Zein Septiana Muhyiddin A M Hayat Mujidah, Jihan Izzathul Multazam Dwi Parista Muna, Rochmatul Munawarah MUSLIMIN Nasution, Romadon Natriani Syam, Natriani Nofri Aldinata Nur Akmal Nur Hidayat Nurdin Nurabdillah, Baeti Nurannisa, Andi Nurmisba Nurna Ningsih Nurna Ningsih Nursakinah, Jysa Nuruddin Kafy El Ridlo Nurul Hidayah Ilyas Nurul Istiqamah Nurul Safitri Nusrotul Bariyah Olyvia Prameswari Paulus Tangke Perani Rosyani Putri Rachman, Fahrim Irhamna Rachman, Irna Ningsi Amalia Rachmasari Pramita Wardhani RAHAYU, CANDRA Rahmadani, Sukri Rahmadania, Cahya Rahmatia Rahmawati, Ismatu Rais Ramli, Nurhaerani Randitha Missouri Rasni Risma Sari, Risma Rita Setiani Ritha Tuken Rizka Amalia Robert Jao Rotamaro, Sahnan S. Kuba, Muhammad Syafa'at Saba Pasinggi, Yonathan Safira, Meylia Safira, Safra Safitri, Marcelina Via Hanadya Salahudin Salahudin Salam, Abd Saleh, Firman Salman, Nola Fibriyanti Bte Salsabila, Ismi Sam Hermansyah Sambara, Piether Magi Sanjaya, Erie Santi Mandasari Sapri Saputri, Annisa Sayuti Malik Selang, Kamaruddin Sellang, Kamaruddin Selvia Sarungu Setiawan, Rico Shadri Siti Fatimah Abdul Latif Siti Hasanah Siti HasanahSiti Hasanah Siti Norhidayah Sukma Sulaeman Sulardi . SULASTRI Sundari SUPRIATIN Sutoyo Syafira Anggraini Syafruddin Syamsuddin Syamsuri, Andi Makbul Syarifoeddin, Elya Wibawa Tiassari Janjang Suminar Tjiang Y. Suryady, Ardi Triono Uceng, Andi Usman M Utina, Toni Wahyu Sihab Wahyu, Reski Wahyuni, Titin Wardhani, Rachmasari Pramita Wawan Krismanto Wawan Sopiyan Widiyanti Kurnianingsih Y. Abbas, Nurfadillah Yoggi Dwi Saputra Yonathan S Pasinggi Yuli Astuti yulia Yumi Zaifuddin