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All Journal Media Kesehatan Masyarakat Indonesia NUTRIRE DIAITA Public Health of Indonesia Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Ilmiah Bidan Jurnal Manajemen Kesehatan Yayasan RS.Dr. Soetomo JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Manajemen Informatika Jurnal Kesehatan Indonesia Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) Health Information : Jurnal Penelitian PREPOTIF : Jurnal Kesehatan Masyarakat Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda (JIPIKI) Journal of Nursing and Public Health (JNPH) J-REMI : Jurnal Rekam Medik dan Informasi Kesehatan Health Publica : Jurnal Kesehatan Masyarakat Jurnal Ilmu Kesehatan Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science International Journal of Health and Information System (IJHIS) Detector: Jurnal Inovasi Riset Ilmu Kesehatan Promotor: Jurnal Mahasiswa Kesehatan Masyarakat Holistik Jurnal Kesehatan
Hosizah Hosizah
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Dentistry Economics, Econometrics & Finance Education Health Professions Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Journal : Indonesian Journal of Artificial Intelligence and Data Mining

 1 
Natural Language Processing for Enhancing Anamnesis Documentation in Typhoid Fever Cases Putri, Tacyah Kholifah; Nurmalasari, Mieke; Hosizah, Hosizah; Krismawati, Dewi; Panutun, Satria Bagus
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 1 (2025): March 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i1.33325

Abstract

The implementation of Natural Language Processing (NLP) is crucial for enhancing the quality of medical records. This study aimed to develop an NLP model to improve the accuracy of documenting disease anamnesis for typhoid fever. The problem addressed by this research is the difficulty in analyzing and classifying patient complaints recorded in electronic medical records, which can affect the accuracy of diagnosis and treatment. The urgency of this study lies in ensuring that documented medical information is used accurately to support diagnosis and patient management. A quantitative approach was used, focusing on electronic medical records of patients who underwent anti-salmonella IgM tests in 2023, involving 424 individuals. The study assessed the performance of three models: Support Vector Machines (SVM), Naive Bayes Bernoulli, and Logistic Regression. The SVM model achieved the highest accuracy at 81.4%, compared to 76.7% for Naive Bayes Bernoulli and 79.1% for Logistic Regression. Additionally, four topic models were identified, highlighting common complaint words and their impacts. The most frequently occurring symptoms in the anamnesis of typhoid fever were "defecation," "nausea," "vomiting," "fever," "diarrhea," "heartburn," "weakness," "loss of appetite," "abdominal pain," "cough," and "cold." This study demonstrates that the SVM model provides superior accuracy in analyzing medical records compared to other models.
Co-Authors Alumni STIKES Husada Borneo Azza, Azizatul Basuki Hari Darmawan, Lusiana desi aryani Dewi, Sukmala Endang Titi Amrihati, Endang Titi Herey, Peter HILHAMI, HILHAMI Irmawan, - Julianti, Anissa JUS’AT, IDRUS Krismawati, Dewi Kuntoro Kuntoro Larasati , Dhiar Niken Latumapina, Stella Florence Imanuela Lepong, Maria Lestari, Jayanti Lisda Novilia Mauren Michaela, Sarah Muchlis, Husni Abdul Munggaran, Rahayu Putri Nurhasanah, Raden Nurmalasari, Mieke Oktavianti, Putri Panutun, Satria Bagus Puspita, Kori Putri, Tacyah Kholifah Qomarania, Witri Uama Qomarania, Witri Zuama Rafidah, Arlien Rona Rahmawati, Danisa Ocha Rahmayani, Kamila Zainab Ratna Indrawati, Ratna Rina Anindita Rina Yuliana Rischa Zahra Bellanisa Rosida, Putri Lailatul Rusman Efendi Salsabilla, Jihan Saskia Saqil Ahmad Saragih, Pestaria Selviani, Selviani Silalahi, Rani Gartika Holivia STIKES Husada Borneo Sulistianingsih Sulistianingsih Sunarti Temesvari, Nauri Anggita Tria Saras Pertiwi Umi Khoirun Nisak Widjaja, Lily Yusnaeni Yusnaeni, Yusnaeni Zuama Qomarania, Witri