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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TEKNIK INFORMATIKA SITEKIN: Jurnal Sains, Teknologi dan Industri Prosiding Semnastek Scientific Journal of Informatics Sistemasi: Jurnal Sistem Informasi Jurnal CoreIT JURNAL MEDIA INFORMATIKA BUDIDARMA IT JOURNAL RESEARCH AND DEVELOPMENT Indonesian Journal of Artificial Intelligence and Data Mining Seminar Nasional Teknologi Informasi Komunikasi dan Industri Journal of Economic, Bussines and Accounting (COSTING) INOVTEK Polbeng - Seri Informatika Jurnal Informatika Universitas Pamulang Jurnal Nasional Komputasi dan Teknologi Informasi JURIKOM (Jurnal Riset Komputer) JOISIE (Journal Of Information Systems And Informatics Engineering) Building of Informatics, Technology and Science bit-Tech Zonasi: Jurnal Sistem Informasi INFORMASI (Jurnal Informatika dan Sistem Informasi) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) Information System Journal (INFOS) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal UNITEK Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Informatika Teknologi dan Sains (Jinteks) Knowbase : International Journal of Knowledge in Database Bulletin of Informatics and Data Science Jurnal Informatika: Jurnal Pengembangan IT Jurnal Komtika (Komputasi dan Informatika)
Elvia Budianita
Universitas Islam Negeri Sultan Syarif Kasim Riau
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Journal : bit-Tech

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Thyroid Disease Classification Using Support Vector Machine and Recursive Feature Elimination Method Citra Wulandari; lis Afrianty; Elvia Budianita; Siska Kurnia Gusti
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3454

Abstract

Thyroid disease is a common endocrine disorder that can cause serious metabolic and cardiovascular complications, so accurate early detection is clinically essential. This study proposes a Support Vector Machine (SVM) classifier enhanced with Recursive Feature Elimination (RFE) to select the most informative attributes and Adaptive Synthetic Sampling (ADASYN) to handle class imbalance in a Kaggle thyroid dataset of 3,771 clinical records. The data contain 25 diagnostic attributes with a strongly skewed distribution between healthy and thyroid cases. The model’s robustness was examined using three train–test split ratios. The best configuration, SVM with a Linear kernel and 20 RFE-selected features under an 80:20 split, achieved 98.39% accuracy, with precision, recall, and F1-score all reaching 0.98, indicating consistently strong performance across classes. RFE contributes by removing redundant or weakly relevant variables, helping the classifier construct a more stable and interpretable decision boundary. ADASYN further improves the representation of the minority class, yielding higher recall and F1-score for thyroid cases and reducing the risk of missed diagnoses. Overall, the combined use of feature selection and adaptive oversampling produces a balanced and computationally efficient model for thyroid disease classification. These findings suggest that the proposed approach can support clinical decision-making, reduce diagnostic errors in imbalanced data settings, and strengthen early detection efforts in endocrine health assessment. By offering high sensitivity for thyroid cases while maintaining robust specificity for healthy patients, the model is well suited for integration into clinical decision-support and routine screening workflows.
Application of Backpropagation Neural Network Using Random Oversampling and Robust Scaler for Classification Thyroid Ummy Agustina Putri; Iis Afrianty; Elvia Budianita; Fadhilah Syafria
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Thyroid disease is a fairly common endocrine disorder that requires rapid and accurate diagnosis so that patients can receive appropriate treatment. This study was conducted to improve the system's ability to classify thyroid disease by utilizing data preprocessing techniques with RobustScaler and Random Over Sampling (ROS), as well as the Backpropagation Neural Network (BPNN) algorithm. The research dataset consisted of 3,771 patient data with 25 clinical attributes describing the condition and function of the thyroid. The data preprocessing process involved data selection, data cleaning, and data transformation using RobustScaler so that each feature had a more stable scale and was not affected by extreme values. The class imbalance problem was overcome using ROS so that the amount of data increased to 6,834 samples and the class distribution became more balanced. The Backpropagation Neural Network algorithm was applied in model training by testing various variations in the number of neurons in the hidden layer (38 and 49) and learning rate (0.01 and 0.001). Training was conducted for 5,000 and 10,000 epochs. Evaluation was performed using the 10-Fold Cross Validation method to obtain more consistent results. The results of the study show that the model is capable of achieving very high accuracy, up to 99.85%, on several parameters. The results show that proper data processing and appropriate parameter selection greatly affect model performance. Overall, the use of RobustScaler and ROS has been proven to significantly improve the accuracy of thyroid disease classification.
Co-Authors Abdul Halim Adzhima, Fauzan Afriyanti, Iis Agnesti, Syafira Agung Syaiful Rahman Agustina, Auliyah Aji Pangestu Adek Akbar, Lionita Asa Akhyar, Amany Al Rasyid, Nabila Alfaiza, Raihan Zia Alfarabi.B, Alif Alwis Nazir Alwis Nazir Alwis Nazir Amalia Hanifah Artya Ammar Muhammad Anggi Pranata Aprilia, Tasya Aprima, Muhammad Dzaky Arif Pratama Budiman Ayu Sri Wahyuni Azhima, Mohd Baehaqi Boni Iqbal buhfi arides hanyodi Chely Aulia Misrun Citra Wulandari Damayanti, Elok Desra Rizki Riyandi Dicky Abimanyu Dinyah Fithara Dodi Efendi doli fancius silalahi Eka Pandu Cynthia Eka Pandu Cynthia Eka Pandu Cynthia Eka Suryani Indra Septiawati Elin Haerani Elin Haerani Elin Haerani Elin Haerani Ellin Haerani Fadhilah Syafria Faska, Ridho Mahardika Fatma Hayati Fauzan Adzim Febi Yanto Fikri Utri Amri Fikry Utri Amri Fitri Astuti Fitri Insani Fitri Insani Fitri Insani Fitri Insani Fitri, Anisa Fratiwi Rahayu Gusrifaris Yuda Alhafis Gusti, Siska Kurnia Guswanti, Widya Habibi Al Rasyid Harpizon Habibi, M. Ilham Hara Novina Putri Hariansyah, Jul Ibnu Afdhal Ichsan Permana Putra Ihda Syurfi Ihlal Hanafi Harahap Iis Afrianty Iis Afrianty Ikhsanul Hamdi Ilham Habibi Hasibuan Indah Wulandari Isra Almahsa, Muhammad Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Iskandar Jasril Jasril Jasril Jasril jasril jasril jasril Jeki Dwi Arisandi Khair, Nada Tsawaabul Lestari Handayani Lestari Handayani Lili Rahmawati lis Afrianty Liza Afrianti Lola Oktavia M Fikry M Ikhsan Maulana M ridwan Ma'rifah, Laila Alfi Masaugi, Fathan Fanrita Matondang, Irfan Jamal Mawadda Warohma Mazdavilaya, T Kaisyarendika Megawati Megawati Meiky Surya Cahyana Mhd. Kadarman Mohd. Ridho Zarkasih Rahim Muhammad Affandes Muhammad Fikry Muhammad Fikry Muhammad Fikry Muhammad Fikry Muhammad Hafiz Muhammad Irsyad Muhammad Rizky Ramadhan Mulyati, Sabar Mulyono, Makmur Musa Irfan Mustasaruddin Mustasaruddin Nabyl Alfahrez Ramadhan Amril Nanda Sepriadi Nazir, Alwis Nazruddin Safaat H Neni Sari Putri Juana Novi Yanti Novi Yanti Novriyanto Novriyanto Nur Iza Nuradha Liza Utami Nurafni Syahfitri Nurfadilah, Nova Siska Okfalisa Okfalisa Pasiolo, Lugas Permata, Rizkiya Indah Pizaini Pizaini Putri, Widya Maulida Rahmad Abdillah Rahmad Kurniawan Ramadani, Repi Ramadhan, Aweldri Ramadhani, Astrid Ramadhani, Siti Reni Susanti Reski Mai Candra Reski Mai Candra Rinaldi Syarfianto Robby Azhar Roni Salambue Rusnedy, Hidayati Said Nurfan Hidayad Tillah Saktioto Saktioto Sephia Pratista Silfia Silfia Siti Sri Rahayu Surya Agustian Suwanto Sanjaya Syahputra, Armadani Trisia Intan Berliana Ulti Desi Arni, Ulti Desi Ummy Agustina Putri Wang, Shir Li Widodo Prijodiprodjo Wiranti, Lusi Diah Yeni Fariati Yusra Yusra Yusra Yusra Yusra Yusra Yusra Yusra Yusra, Yusra Zabihullah, Fayat Zulastri, Zulastri Zulkarnain Zulkarnain