Comparison of Naive Bayes Method and Certainty Factor for Diagnosis of Preeclampsia
Abstract
Preeclampsia is a disease often suffered by pregnant women caused by several factors such as a history of heredity, blood pressure, urine protein, and diabetes. The data sample used in this study is data on pregnant women in the 2020 time period recorded at health services in the former Cilacap Regency. This study was conducted to compare the final results of the Naive Bayes method and the certainty factor method in providing the results of a diagnosis of preeclampsia seen from the symptoms experienced by these pregnant women. The naïve Bayes approach provides decisions by managing statistical data and probabilities taken from the prediction of the likelihood of a pregnant woman showing symptoms of preeclampsia. Symptoms of preeclampsia, while the certainty factor method determines the certainty value of the diagnosis of preeclampsia in pregnant women based on the calculation of the CF value. The research output compares the two methods, showing that the certainty factor method provides more accurate diagnostic results than the Naive Bayes method. It happens because the CF method requires a minimum value of 0.2 and a maximum of 1 for each rule on the factors/symptoms involved, while the Naive Bayes method only requires values of 0 and 1 for each factor causing preeclampsia in pregnant women.
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References
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[2] H. Bracken et al., "Congo red test for identification of preeclampsia: Results of a prospective diagnostic case-control study in Bangladesh and Mexico," EClinicalMedicine, vol. 31, 2021, doi: 10.1016/j.eclinm.2020.100678.
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[4] M. J. Aguilar-Cordero, A. Lasserrot-Cuadrado, N. Mur-Villar, X. A. León-Ríos, T. Rivero-Blanco, and I. M. Pérez-Castillo, "Vitamin D, preeclampsia and prematurity: A systematic review and meta-analysis of observational and interventional studies," Midwifery, vol. 87, p. 102707, 2020, doi: 10.1016/j.midw.2020.102707.
[5] T. C. C. Macedo et al., "Prevalence of preeclampsia and eclampsia in adolescent pregnancy: A systematic review and meta-analysis of 291,247 adolescents worldwide since 1969," European Journal of Obstetrics Gynecology and Reproductive Biology, vol. 248, no. March, pp. 177–186, 2020, doi: 10.1016/j.ejogrb.2020.03.043.
[6] P. Qiao et al., "Impact of growth discordance in twins on preeclampsia based on chorionicity," American Journal Obstetrics Gynecology, vol. 223, no. 4, pp. 572.e1-572.e8, 2020, doi: 10.1016/j.ajog.2020.03.024.
[7] B. Aini, Fajaria Nur; Widyawati, Melyana Nurul, Santor, “Diagnosa Preeklamsia Pada Ibu Hamil Menggunakan Sistem Informasi Berbasis Web,” Jurnal Keperawatan Silampari, vol. 2, no. 2, pp. 18–27, 2019.
[8] Tri Budiarti, Dhiah Dwi Kusumawati., Nikmah Nuur Rochmah, “Hubungan Berat Bayi Lahir Dengan Kematian Bayi,” Jurnal Kesehatan Al-Irsyad, vol. 12, no. 2, pp. 63–70, 2019, doi: 10.36746/jka.v12i2.42.
[9] Tim Dinas Kesehatan Prop Jateng, “Renstra Dinas Kesehatan Jawa Tengah Tahun 2018-2023,” 2019.
[10] Y. Wang et al., "Exposure to multiple metals and prevalence for preeclampsia in Taiyuan, China," Environmental International, vol. 145, no. August, p. 106098, 2020, doi: 10.1016/j.envint.2020.106098.
[11] A. H. Aji, M. T. Furqon, and A. W. Widodo, “Sistem Pakar Diagnosa Penyakit Ibu Hamil Menggunakan Metode Certainty Factor ( CF ),” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 2, no. 5, pp. 2127–2134, 2018, [Online]. Available: http://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/1556.
[12] D. Kurniasari, F. A.-H. JURNAL, and undefined 2015, “Hubungan Usia, Paritas Dan Diabetes Mellitus Pada Kehamilan Dengan Kejadian Preeklamsia Pada Ibu Hamil Di Wilayah Kerja Puskesmas Rumbia Kabupaten,” Ejurnalmalahayati.Ac.Id, vol. 9, no. 3, pp. 142–150, 2015, [Online]. Available: http://ejurnalmalahayati.ac.id/index.php/holistik/article/view/232.
[13] S. Dai et al., "SeDeM expert system for directly compressed tablet formulation: A review and new perspectives," Powder Technology, vol. 342, pp. 517–527, 2019, doi: 10.1016/j.powtec.2018.10.027.
[14] M. Castelli, L. Manzoni, L. Vanneschi, and A. Popovič, "An expert system for extracting knowledge from customers' reviews: The case of Amazon.com, Inc.," Expert Syst. Appl., vol. 84, pp. 117–126, 2017, doi: 10.1016/j.eswa.2017.05.008.
[15] D. Santra, S. K. Basu, J. K. Mandal, and S. Goswami, "Rough set based lattice structure for knowledge representation in medical expert systems: Low back pain management case study," Expert System Application, vol. 145, p. 113084, 2020, doi: 10.1016/j.eswa.2019.113084.
[16] Y. Prasetio and H. Haryanto, “Visualisasi Berbasis Naive Bayes untuk Pemetaan Penyebaran Penyakit Infeksi Saluran Pernafasan Akut,” Sisfotenika, vol. 7, no. 1, 2017, doi: 10.30700/jst.v7i1.135.
[17] Y. Nurfarianti, “Sistem Pakar Untuk Diagnosis Dismenore Menggunakan Metode Naïve Bayes,” Program Studi Informatika Universitas Tanjungpura, vol. 4, no. 1, pp. 1–6, 2016.
[18] M. H. Rifqo and A. Wijaya, “Implementasi Algoritma Naive Bayes Dalam Penentuan Pemberian Kredit,” Pseudocode, vol. 4, no. 2, pp. 120–128, 2017, doi: 10.33369/pseudocode.4.2.120-128.
[19] K. E. Setyaputri, A. Fadlil, and S. Sunardi, “Analisis Metode Certainty Factor pada Sistem Pakar Diagnosa Penyakit THT,” Jurnal Teknik Elektro, vol. 10, no. 1, pp. 30–35, 2018, doi: 10.15294/jte.v10i1.14031.
[20] L. P. Wanti, I. N. Azroha, and M. N. Faiz, “Implementasi User Centered Design Pada Sistem Pakar Diagnosis Gangguan Perkembangan Motorik Kasar Pada Anak Usia Dini,” Media Aplikom, vol. 11, no. 1, pp. 1–10, 2019.
[21] L. P. Wanti and S. Romadlon, “Implementasi Forward Chaining Method Pada Sistem Pakar Untuk Deteksi Dini Penyakit Ikan,” Infotekmesin, vol. 11, no. 02, pp. 74–79, 2020, doi: 10.35970/infotekmesin.v11i2.248.
[22] R. Rusdiansyah, S. Setiawan, and M. Badrul, “Diabetes Mellitus Diagnosis Expert System With Web-Based Forward Chaining,” SinkrOn, vol. 3, no. 2, p. 61, Mar. 2019, doi: 10.33395/sinkron.v3i2.10055.
[23] A. H. Oluwole, A. A. Adekunle, A. O. Olasunkanmi, and A. O. Adeodu, "A shoveling-related pain intensity prediction expert system for workers' manual movement of material," International Journal of Technology, vol. 7, no. 4, pp. 603–615, 2016, doi: 10.14716/ijtech.v7i4.2208.
[24] S. A. Sabab, M. A. R. Munshi, A. I. Pritom, and S. Shihabuzzaman, "Cardiovascular disease prognosis using effective classification and feature selection technique," 1st International Conference on Medical Engineering, Health Informatics Technology MediTec 2016, no. November, pp. 1–6, 2017, doi: 10.1109/MEDITEC.2016.7835374.
[25] K. NainSukhia, A. Ashraf Khan, and M. Bano, "Introducing Economic Order Quantity Model for Inventory Control in Web based Point of Sale Applications and Comparative Analysis of Techniques for Demand Forecasting in Inventory Management," International Journal Computer Applications, vol. 107, no. 19, pp. 1–8, 2014, doi: 10.5120/18856-7385.
[26] F. Ali, K. S. Kwak, and Y. G. Kim, "Opinion mining based on fuzzy domain ontology and Support Vector Machine: A proposal to automate online review classification," Applied Soft Computing Journal, vol. 47, pp. 235–250, 2016, doi: 10.1016/j.asoc.2016.06.003.
[27] A. P. Wibawa et al., "Naïve Bayes Classifier for Journal Quartile Classification," International Journal of Recent Contributions from Engineering, Science & IT, vol. 7, no. 2, p. 91, 2019, doi: 10.3991/ijes.v7i2.10659.
[28] A. A. S. Nugraha, N. Hidayat, and L. Fanani, “Sistem Pakar Diagnosis Penyakit Kucing Menggunakan Metode Naive Bayes – Certainty Factor Berbasis Android,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Universitas Brawijaya, vol. 2, no. 2, pp. 650–658, 2018.
[29] S. Shastri et al., "Development of a Data Mining Based Model for Classification of Child Immunization Data," International Journal of Computational Engineering Research, vol. 8, no. 6, pp. 41–49, 2018, [Online]. Available: www.ijceronline.com.
[30] A. Saleh and F. Nasari, “Penerapan Equal-Width Interval Discretization Dalam Metode Naive Bayes Untuk Meningkatkan Akurasi Prediksi Pemilihan Jurusan Siswa,” Masyarakat Telematika Dan Informasi: Jurnal Penelitian Teknologi Informasi dan Komunikasi, vol. 9, no. 1, p. 1, 2018, doi: 10.17933/mti.v9i1.113.
[31] A. Saleh, “Implementasi Metode Klasifikasi Naïve Bayes Dalam Memprediksi Besarnya Penggunaan Listrik Rumah Tangga,” Creative Information Technology Journal, vol. 2, no. 3, pp. 207–217, 2015.
[32] M. F. A. Saputra, T. Widiyaningtyas, and A. P. Wibawa, "Illiteracy classification using K means-naïve bayes algorithm," International Journal on Informatics Visualization, vol. 2, no. 3, pp. 153–158, 2018, doi: 10.30630/joiv.2.3.129.
[33] S. Ernawati, E. R. Yulia, Frieyadie, and Samudi, "Implementation of The Naïve Bayes Algorithm with Feature Selection using Genetic Algorithm for Sentiment Review Analysis of Fashion Online Companies," in 2018 6th International Conference on Cyber and IT Service Management (CITSM), Aug. 2018, pp. 1–5, doi: 10.1109/CITSM.2018.8674286.
[34] M. Arifin, S. Slamin, and W. E. Y. Retnani, “Penerapan Metode Certainty Factor Untuk Sistem Pakar Diagnosis Hama Dan Penyakit Pada Tanaman Tembakau,” Berkala Sainstek, vol. 5, no. 1, p. 21, 2017, doi: 10.19184/bst.v5i1.5370.
[35] J. Wang et al., "Refined micro-scale geological disaster susceptibility evaluation based on UAV tilt photography data and weighted certainty factor method in Qingchuan County," Ecotoxicology and Environmental Safety, vol. 189, no. November, p. 110005, 2020, doi: 10.1016/j.ecoenv.2019.110005.
[36] J. Li and Y. Zhang, "GIS-supported certainty factor (CF) models for assessment of geothermal potential: A case study of Tengchong County, Southwest China," Energy, vol. 140, pp. 552–565, 2017, doi: 10.1016/j.energy.2017.09.012.
[37] A. Azareh et al., "Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models," Science Total Environment, vol. 655, pp. 684–696, 2019, doi: 10.1016/j.scitotenv.2018.11.235.
[38] A. A. Zain and E. Z. Astutik, “Analisis Metode Certainty Factor Dalam Sistem Pakar Untuk Mendeteksi Penyakit Sapi Pedaging”, Universtas Dian Nuswantoro, Semarang, 2015.
[39] P. F. Aprilliani and H. Mustafidah, “Implementasi Certainty Factor Pada Diagnosa Penyakit Infeksi Tropis,” Jurnal Riset, Sains dan Teknologi, vol. 1, no. 1, pp. 22–24, 2017, [Online]. Available: http://jurnalnasional.ump.ac.id/index.php/JRST/article/download/1081/1245.
[40] A. Riadi, “Penerapan Metode Certainty Factor Untuk Sistem Pakar Diagnosa Penyakit Diabetes Melitus Pada Rsud Bumi Panua Kabupaten Pohuwato,” ILKOM Jurnal Ilmiah., vol. 9, no. 3, pp. 309–316, 2017, doi: 10.33096/ilkom.v9i3.162.309-316.
[41] J. Yuan, S. Zhang, S. Wang, F. Wang, and L. Zhao, "Process abnormity identification by fuzzy logic rules and expert estimated thresholds derived certainty factor," Chemometrics and Intelligent Laboratory System, vol. 209, no. August 2020, p. 104232, 2021, doi: 10.1016/j.chemolab.2020.104232.
[42] V. Balakrishnan and W. Kaur, "ScienceDirect ScienceDirect String-based Multinomial Naïve Bayes for Emotion Detection String-based Multinomial Naïve Bayes for Emotion Detection among Facebook Diabetes Community among Facebook Diabetes Community," Procedia Computer Science, vol. 159, pp. 30–37, 2019, doi: 10.1016/j.procs.2019.09.157.
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Published
2022-08-24
How to Cite
WANTI, Linda Perdana et al.
Comparison of Naive Bayes Method and Certainty Factor for Diagnosis of Preeclampsia.
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi, [S.l.], v. 13, n. 2, p. 105-116, aug. 2022.
ISSN 2541-5832.
Available at: <https://ojs.unud.ac.id/index.php/lontar/article/view/82863>. Date accessed: 22 nov. 2024.
doi: https://doi.org/10.24843/LKJITI.2022.v13.i02.p04.
Section
Articles
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