Expert System for Pregnancy Risk Diagnosis Using Decision Tree and Dempster-Shafer Method
Abstract
The high Maternal Mortality Rate (MMR) remains a severe concern in maternal healthcare. One of the reasons is the delay in recognizing early danger signs during pregnancy. To address this issue, there is a proposed solution in the form of developing an expert system aimed at swiftly and efficiently diagnosing pregnancy risks in pregnant women using the Decision Tree and Dempster Shafer methods. The Decision Tree method is employed for symptom classification, while Dempster Shafer provides confidence values for existing facts. This research collects data from the dataset, the Poedji Rochjati Score Card (KSPR), and qualitative data through expert interviews. From the collected data, knowledge acquisition processes are then carried out to extract knowledge using the ID3 Decision Tree and combine all symptoms from the gathered data. The processed data is then represented as a decision tree and assigned confidence values. The development of this expert system utilizes the Laravel framework with PHP language and MySQL database. System validation involves patients as participants and midwives as experts and testers. Testing was conducted on March 13 and 16, 2024, involving 16 patients at the Gatak Community Health Center. The system evaluation results show an accuracy rate of 93.75%. This value indicates that the system can operate effectively. Thus, it can be recommended for use in diagnosing pregnancy risks.
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References
[1] E. F. Wati, E. Sunita Perangin-Angin, and B. Sudrajat, “Pregnancy Disease Diagnostic Expert System With Certainty Factor Method,” International Journal of Information System & Technology Akreditasi, vol. 6, no. 158, pp. 754–760, 2023, doi: https://doi.org/10.30645/.v6i6.292.
[2] E. F. Wati and B. Sudrajat, “Application of Naive Bayes Method For Diagnosis of Pregnancy Disease,” International Journal of Information System & Technology Akreditasi, vol. 6, no. 158, pp. 93–100, 2022, doi: https://doi.org/10.30645/ijistech.v6i1.216.
[3] R. Ilbert and D. Marfuah, “Depressive Symptoms in High-Risk Pregnancies During the COVID-19 Pandemic,” The International Virtual Conference on Nursing (IVCN), Feb. 2022, doi: 10.18502/kls.v7i2.10339.
[4] F. T. Anggraeny, F. Muttaqin, and M. Syahrul Munir, “Modeled early detection of pregnancy risk based on Poedji Rochjati score card using relief and neural network,” Proceeding International Joint Conference on Science and Technology (IJST), 2017, Accessed: Apr. 13, 2024. [Online]. Available: https://ojs.pnb.ac.id/index.php/Proceedings/article/view/920
[5] I. Putu, K. Aryadhi, I. Made Darmayasa, M. Bagus, and D. Aryana, “Characteristics of Risk Factor for Obstetric Emergency Cases Referred to Sanglah General Hospital,” International Journal of Science and Research, 2018, doi: 10.21275/SR201006200628.
[6] G. Aditia, A. Ziqri, A. T. Maulana, and F. D. Adhinata, “Expert System for Identifying Pregnant Using Forward Chaining,” Journal of Informatics Information System Software Engineering and Applications (INISTA), vol. 5, no. 2, pp. 136–143, May 2023, doi: 10.20895/inista.v5i2.494.
[7] S. Puspitaningsih, Suryono, and Farikhin, “Design and Implementation of an Emergency Pregnancy Referral System Using Rule-Based Expert System Forward Chaining Method,” in 2021 6th International Conference on Informatics and Computing, ICIC 2021, 2021. doi: 10.1109/ICIC54025.2021.9632953.
[8] E. F. Wati and A. Puspitasari, “Expert System for Diagnosing Pregnancy Complaints by Forward Chaining,” SinkrOn, vol. 5, no. 1, p. 7, Oct. 2020, doi: 10.33395/sinkron.v5i1.10593.
[9] N. Kapoor and N. Bahl, “Comparative Study Of Forward And Backward Chaining In Artificial Intelligence,” International Journal Of Engineering And Computer Science, Apr. 2016, doi: 10.18535/Ijecs/v5i4.32.
[10] M. R. Anwar, “Analysis of Expert System Implementation in Computer Damage Diagnosis with Forward Chaining Method,” International Transactions on Artificial Intelligence (ITALIC), vol. 1, no. 2, pp. 139–152, 2023.
[11] M. Indriani, F. Anggraini, D. Hartama, and M. Ridwan Lubis, “Expert System Diagnosing Damage to Canon Ir5000 Copier With Forward Chaining Method,” Journal of Artificial Intelligence and Engineering Applications, vol. 1, no. 2, 2022, [Online]. Available: https://ioinformatic.org/
[12] A. D. S. Nicolau, J. P. D. S. C. Augusto, and R. Schirru, “Accident diagnosis system based on real-time decision tree expert system,” AIP Conf Proc, vol. 1836, Jun. 2017, doi: 10.1063/1.4981957.
[13] B. Charbuty and A. Abdulazeez, “Classification Based on Decision Tree Algorithm for Machine Learning,” Journal of Applied Science and Technology Trends, vol. 2, no. 01, pp. 20–28, Mar. 2021, doi: 10.38094/jastt20165.
[14] Priyanka and D. Kumar, “Decision Tree Classifier: A Detailed Survey,” International Journal of Information and Decision Sciences, vol. 12, no. 3, pp. 246–269, Apr. 2020.
[15] A. Li and X. Zhang, “Fault Diagnosis Knowledge Base Optimization Based on Decision Tree,” 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), pp. 324–327, 2018, doi: 10.1109/IHMSC.2018.00081.
[16] K. M. Gunnarsdottir, C. E. Gamaldo, R. M. E. Salas, J. B. Ewen, R. P. Allen, and S. V. Sarma, “A Novel Sleep Stage Scoring System: Combining Expert-Based Rules with a Decision Tree Classifier,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Institute of Electrical and Electronics Engineers Inc., Oct. 2018, pp. 3240–3243. doi: 10.1109/EMBC.2018.8513039.
[17] R. N. E. Anggraini, N. F. Ariyani, A. F. Septiyanto, R. Sarno, Z. D. Meilani, and T. Soendoro, “A Decision Tree Knowledge-based System for Reviewing Research Ethics Protocol,” in Proceeding - IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022, 2022, pp. 50–55. doi: 10.1109/COMNETSAT56033.2022.9994414.
[18] A. M. Alfatah, R. Arifudin, and M. A. Muslim, “Implementation of Decision Tree and Dempster Shafer on Expert System for Lung Disease Diagnosis,” Scientific Journal of Informatics, vol. 5, no. 1, p. 57, May 2018, doi: 10.15294/sji.v5i1.13440.
[19] N. Nurdin, E. Susanti, H. A.-K. Aidilof, and D. Priyanto, “Comparison of Naive Bayes and Dempster Shafer Methods in Expert System for Early Diagnosis of COVID-19,” MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 22, no. 1, pp. 215–228, Nov. 2022, doi: 10.30812/matrik.v22i1.2280.
[20] E. K. Panggabean, “Comparative Analysis Of Dempster Shafer Method With Certainty Factor Method For Diagnose Stroke Diseases,” International Journal of Artificial Intelligence Research, vol. 2, no. 1, p. 32, Mar. 2018, doi: 10.29099/ijair.v2i1.53.
[21] N. Astuti Triana, E. Maya Safitri, A. Wulansari, and S. Fitri Ana Wati, “Accuracy of Kidney Disease Expert System Based On Certainty Factor and Dempster Shafer Algorithm,” IJCONSIST JOURNAL, vol. 3, no. 2, pp. 19–24, 2022, [Online]. Available: https://doi.org/10/33005/ijconsist.v3i2.66
[22] K. Adhianto, R. Andrian, and Y. Nuhricha Sari, “Comparative Analysis of Cow Disease Diagnosis Expert System using Bayesian Network and Dempster-Shafer Method,” IJACSA) International Journal of Advanced Computer Science and Applications, vol. 10, no. 4, 2019, doi: 10.14569/IJACSA.2019.0100427.
[23] Septiana, N. Yusliani, and K. J. Miraswan, “Expert System To Diagnose Disease In Toddlers Using Dempster Shafer Method,” Sriwijaya Journal of Informatic and Applications, vol. 2, no. 2, pp. 75–80, Jul. 2021.
[24] M. S. A. Sawa, A. Naba, and H. S. Dahlan, “Bayesian Network Expert System for Early Diagnosis of Heart Diseases,” EECCIS, vol. 7, no. 2, 2014, Accessed: Apr. 13, 2024. [Online]. Available: https://jurnaleeccis.ub.ac.id/index.php/eeccis/article/download/222/196
[25] M. Nugraheni, R. Nuraini, M. Tonggiroh, and S. Nurhayati, “Expert System for Diagnosing Learning Disorders in Children Using the Dempster-Shafer Theory Approach,” sinkron, vol. 8, no. 4, pp. 2513–2525, Oct. 2023, doi: 10.33395/sinkron.v8i4.12960.
[26] W. Ilham, S. E. Putra, D. Aldo, Y. S. R. Nur, and A. Utami, “Expert System for Disease Identification in Palawija Plants with the Dempster Shafer Method,” Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering), vol. 10, no. 2, pp. 258–267, Oct. 2023, doi: 10.33019/jurnalecotipe.v10i2.4418.
[27] I. Parapat Hotel -Medan, E. Astuti, N. E. Saragih, N. Sribina, and R. Ramadhani, “Dempster-Shafer Method for Diagnose Diseases on Vegetable,” The 6 th International Conference on Cyber and IT Service Management (CITSM 2018), 2018, doi: http://dx.doi.org/10.1109/CITSM.2018.8674377.
[28] D. Chrimes, “Using Decision Trees as an Expert System for Clinical Decision Support for COVID-19,” Interact J Med Res, vol. 12, p. e42540, Jan. 2023, doi: 10.2196/42540.
[29] R. M. Marusaha, D. Noviandri, and A. H. Lubis, “The Expert System of Determining the Type of Malaria by using Dempster-Shafer Method,” Bulletin of Information Technology (BIT), vol. 4, no. 2, pp. 377–383, 2023, doi: 10.47065/bit.v3i1.
[30] I. M. K. Karo, M. Y. Fajari, N. U. Fadhilah, and W. Y. Wardani, “Benchmarking Naïve Bayes and ID3 Algorithm for Prediction Student Scholarship,” IOP Conf Ser Mater Sci Eng, vol. 1232, no. 1, p. 012002, Mar. 2022, doi: 10.1088/1757-899x/1232/1/012002.
[31] Y. Li, W. Xu, W. Li, A. Li, and Z. Liu, “Research on hybrid intrusion detection method based on the ADASYN and ID3 algorithms,” Mathematical Biosciences and Engineering, vol. 19, no. 2, pp. 2030–2042, 2021, doi: 10.3934/MBE.2022095.
[32] B. Mahbooba, M. Timilsina, R. Sahal, and M. Serrano, “Explainable Artificial Intelligence (XAI) to Enhance Trust Management in Intrusion Detection Systems Using Decision Tree Model,” Complexity, vol. 2021, 2021, doi: 10.1155/2021/6634811.
[33] Veronika, S. Ramadhani, and I. M. Khamidah, “Expert System for Diagnosis Papaya Plant Disease with Backward Chaining and Dempster Shafer,” TEPIAN, vol. 3, no. 2, pp. 92–100, Jun. 2022, doi: 10.51967/tepian.v3i2.767.
[34] A. Setiawan, S. N. Fauzia, K. Kusmaya, K. S. Haryana, I. Abadi, and E. Yulianto, “Expert System for Diagnosing Disease Symptoms of Rice Pests Using the Dempster Shafer Algorithm and Fuzzy Tsukamoto Algorithm,” Jurnal Sisfokom (Sistem Informasi dan Komputer), vol. 11, no. 3, pp. 407–414, Dec. 2022, doi: 10.32736/sisfokom.v11i3.1425.
[35] S. I. Sezer, G. Elidolu, E. Akyuz, and O. Arslan, “An integrated risk assessment modelling for cargo manifold process on tanker ships under FMECA extended Dempster–Shafer theory and rule-based Bayesian network approach,” Process Safety and Environmental Protection, vol. 174, pp. 340–352, Jun. 2023, doi: 10.1016/j.psep.2023.04.024.
[36] N. E. I. Hamda, A. Hadjali, and M. Lagha, “Multisensor Data Fusion in IoT Environments in Dempster–Shafer Theory Setting: An Improved Evidence Distance-Based Approach,” Sensors, vol. 23, no. 11, Jun. 2023, doi: 10.3390/s23115141.
[37] R. G. Tanjung, “Expert System for Diagnosing Cataract Using Forward Chaining Method,” Journal of Computer Scine and Information Technology, pp. 13–17, Jan. 2023, doi: 10.35134/jcsitech.v9i1.56.
[38] E. Fitri Rahayu, “Comparative Analysis Expert System Of Certainty Factor Method With Dempster Shafer Method By Using Open Decision Maker Tool For Toddler At Vaccine House,” UG JURNAL, vol. 14, 2020.
[39] M. Iwan Shofyan et al., “Expert System Design for Web-Based Lecturer Scheduling,” J Phys Conf Ser, vol. 1175, no. 1, Jun. 2019, doi: 10.1088/1742-6596/1175/1/012119.
[40] S. Elmie Dansy et al., “Expert System for Diagnosis Coronavirus Disease,” International Journal of Artificial Intelligence, vol. 1, pp. 39–44, 2023, doi: 10.36079/lamintang.ijai-1001.537.
[41] Y. B. Arya, “Flash Damage Expert System Using the Dempster Shafer Method,” MECOMARE (International Journal of Mechanical Computational and Manufacturing Research), vol. 12, no. 1, pp. 10–15, 2023, doi: 10.35335/computational.v12i1.92.
[42] S. Y. Choi and S. H. Kim, “Knowledge acquisition and representation for high-performance building design: A review for defining requirements for developing a design expert system,” Sustainability (Switzerland), vol. 13, no. 9, May 2021, doi: 10.3390/su13094640.
[43] J. Fajaryanti and C. Author Abstrak, “Expert System Development To Identify Employee Personality Types Using Dempster Shafer Theory,” Jurnal Riset Informatika, vol. 4, no. 3, pp. 227–232, 2022, doi: https://doi.org/10.34288/jri.v4i3.389.
[44] S. R. D. Putranti, “Relationships between Mean, Median and Mode,” Aloha International Journal of Multidisciplinary Advancement (AIJMU), vol. 3, no. 4, p. 87, Apr. 2021, doi: 10.33846/aijmu30403.
[45] H. Henderi, F. Al Khudhorie, G. Maulani, S. Millah, and V. T. Devana, “A Proposed Model Expert System for Disease Diagnosis in Children to Make Decisions in First Aid,” INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi, vol. 6, no. 2, pp. 139–149, Aug. 2022, doi: 10.29407/intensif.v6i2.16912.
[46] M. Abdul Aziz Sujudi and dan Deny Hidayatullah, “Expert System Certainty Factor Method in Website-Based Pest Diagnosis of Eggplant Plants,” Jurnal Mantik, vol. 3, no. 36, pp. 428–438, 2020, [Online]. Available: https://iocscience.org/ejournal/index.php/mantik/index
[2] E. F. Wati and B. Sudrajat, “Application of Naive Bayes Method For Diagnosis of Pregnancy Disease,” International Journal of Information System & Technology Akreditasi, vol. 6, no. 158, pp. 93–100, 2022, doi: https://doi.org/10.30645/ijistech.v6i1.216.
[3] R. Ilbert and D. Marfuah, “Depressive Symptoms in High-Risk Pregnancies During the COVID-19 Pandemic,” The International Virtual Conference on Nursing (IVCN), Feb. 2022, doi: 10.18502/kls.v7i2.10339.
[4] F. T. Anggraeny, F. Muttaqin, and M. Syahrul Munir, “Modeled early detection of pregnancy risk based on Poedji Rochjati score card using relief and neural network,” Proceeding International Joint Conference on Science and Technology (IJST), 2017, Accessed: Apr. 13, 2024. [Online]. Available: https://ojs.pnb.ac.id/index.php/Proceedings/article/view/920
[5] I. Putu, K. Aryadhi, I. Made Darmayasa, M. Bagus, and D. Aryana, “Characteristics of Risk Factor for Obstetric Emergency Cases Referred to Sanglah General Hospital,” International Journal of Science and Research, 2018, doi: 10.21275/SR201006200628.
[6] G. Aditia, A. Ziqri, A. T. Maulana, and F. D. Adhinata, “Expert System for Identifying Pregnant Using Forward Chaining,” Journal of Informatics Information System Software Engineering and Applications (INISTA), vol. 5, no. 2, pp. 136–143, May 2023, doi: 10.20895/inista.v5i2.494.
[7] S. Puspitaningsih, Suryono, and Farikhin, “Design and Implementation of an Emergency Pregnancy Referral System Using Rule-Based Expert System Forward Chaining Method,” in 2021 6th International Conference on Informatics and Computing, ICIC 2021, 2021. doi: 10.1109/ICIC54025.2021.9632953.
[8] E. F. Wati and A. Puspitasari, “Expert System for Diagnosing Pregnancy Complaints by Forward Chaining,” SinkrOn, vol. 5, no. 1, p. 7, Oct. 2020, doi: 10.33395/sinkron.v5i1.10593.
[9] N. Kapoor and N. Bahl, “Comparative Study Of Forward And Backward Chaining In Artificial Intelligence,” International Journal Of Engineering And Computer Science, Apr. 2016, doi: 10.18535/Ijecs/v5i4.32.
[10] M. R. Anwar, “Analysis of Expert System Implementation in Computer Damage Diagnosis with Forward Chaining Method,” International Transactions on Artificial Intelligence (ITALIC), vol. 1, no. 2, pp. 139–152, 2023.
[11] M. Indriani, F. Anggraini, D. Hartama, and M. Ridwan Lubis, “Expert System Diagnosing Damage to Canon Ir5000 Copier With Forward Chaining Method,” Journal of Artificial Intelligence and Engineering Applications, vol. 1, no. 2, 2022, [Online]. Available: https://ioinformatic.org/
[12] A. D. S. Nicolau, J. P. D. S. C. Augusto, and R. Schirru, “Accident diagnosis system based on real-time decision tree expert system,” AIP Conf Proc, vol. 1836, Jun. 2017, doi: 10.1063/1.4981957.
[13] B. Charbuty and A. Abdulazeez, “Classification Based on Decision Tree Algorithm for Machine Learning,” Journal of Applied Science and Technology Trends, vol. 2, no. 01, pp. 20–28, Mar. 2021, doi: 10.38094/jastt20165.
[14] Priyanka and D. Kumar, “Decision Tree Classifier: A Detailed Survey,” International Journal of Information and Decision Sciences, vol. 12, no. 3, pp. 246–269, Apr. 2020.
[15] A. Li and X. Zhang, “Fault Diagnosis Knowledge Base Optimization Based on Decision Tree,” 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), pp. 324–327, 2018, doi: 10.1109/IHMSC.2018.00081.
[16] K. M. Gunnarsdottir, C. E. Gamaldo, R. M. E. Salas, J. B. Ewen, R. P. Allen, and S. V. Sarma, “A Novel Sleep Stage Scoring System: Combining Expert-Based Rules with a Decision Tree Classifier,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Institute of Electrical and Electronics Engineers Inc., Oct. 2018, pp. 3240–3243. doi: 10.1109/EMBC.2018.8513039.
[17] R. N. E. Anggraini, N. F. Ariyani, A. F. Septiyanto, R. Sarno, Z. D. Meilani, and T. Soendoro, “A Decision Tree Knowledge-based System for Reviewing Research Ethics Protocol,” in Proceeding - IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022, 2022, pp. 50–55. doi: 10.1109/COMNETSAT56033.2022.9994414.
[18] A. M. Alfatah, R. Arifudin, and M. A. Muslim, “Implementation of Decision Tree and Dempster Shafer on Expert System for Lung Disease Diagnosis,” Scientific Journal of Informatics, vol. 5, no. 1, p. 57, May 2018, doi: 10.15294/sji.v5i1.13440.
[19] N. Nurdin, E. Susanti, H. A.-K. Aidilof, and D. Priyanto, “Comparison of Naive Bayes and Dempster Shafer Methods in Expert System for Early Diagnosis of COVID-19,” MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 22, no. 1, pp. 215–228, Nov. 2022, doi: 10.30812/matrik.v22i1.2280.
[20] E. K. Panggabean, “Comparative Analysis Of Dempster Shafer Method With Certainty Factor Method For Diagnose Stroke Diseases,” International Journal of Artificial Intelligence Research, vol. 2, no. 1, p. 32, Mar. 2018, doi: 10.29099/ijair.v2i1.53.
[21] N. Astuti Triana, E. Maya Safitri, A. Wulansari, and S. Fitri Ana Wati, “Accuracy of Kidney Disease Expert System Based On Certainty Factor and Dempster Shafer Algorithm,” IJCONSIST JOURNAL, vol. 3, no. 2, pp. 19–24, 2022, [Online]. Available: https://doi.org/10/33005/ijconsist.v3i2.66
[22] K. Adhianto, R. Andrian, and Y. Nuhricha Sari, “Comparative Analysis of Cow Disease Diagnosis Expert System using Bayesian Network and Dempster-Shafer Method,” IJACSA) International Journal of Advanced Computer Science and Applications, vol. 10, no. 4, 2019, doi: 10.14569/IJACSA.2019.0100427.
[23] Septiana, N. Yusliani, and K. J. Miraswan, “Expert System To Diagnose Disease In Toddlers Using Dempster Shafer Method,” Sriwijaya Journal of Informatic and Applications, vol. 2, no. 2, pp. 75–80, Jul. 2021.
[24] M. S. A. Sawa, A. Naba, and H. S. Dahlan, “Bayesian Network Expert System for Early Diagnosis of Heart Diseases,” EECCIS, vol. 7, no. 2, 2014, Accessed: Apr. 13, 2024. [Online]. Available: https://jurnaleeccis.ub.ac.id/index.php/eeccis/article/download/222/196
[25] M. Nugraheni, R. Nuraini, M. Tonggiroh, and S. Nurhayati, “Expert System for Diagnosing Learning Disorders in Children Using the Dempster-Shafer Theory Approach,” sinkron, vol. 8, no. 4, pp. 2513–2525, Oct. 2023, doi: 10.33395/sinkron.v8i4.12960.
[26] W. Ilham, S. E. Putra, D. Aldo, Y. S. R. Nur, and A. Utami, “Expert System for Disease Identification in Palawija Plants with the Dempster Shafer Method,” Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering), vol. 10, no. 2, pp. 258–267, Oct. 2023, doi: 10.33019/jurnalecotipe.v10i2.4418.
[27] I. Parapat Hotel -Medan, E. Astuti, N. E. Saragih, N. Sribina, and R. Ramadhani, “Dempster-Shafer Method for Diagnose Diseases on Vegetable,” The 6 th International Conference on Cyber and IT Service Management (CITSM 2018), 2018, doi: http://dx.doi.org/10.1109/CITSM.2018.8674377.
[28] D. Chrimes, “Using Decision Trees as an Expert System for Clinical Decision Support for COVID-19,” Interact J Med Res, vol. 12, p. e42540, Jan. 2023, doi: 10.2196/42540.
[29] R. M. Marusaha, D. Noviandri, and A. H. Lubis, “The Expert System of Determining the Type of Malaria by using Dempster-Shafer Method,” Bulletin of Information Technology (BIT), vol. 4, no. 2, pp. 377–383, 2023, doi: 10.47065/bit.v3i1.
[30] I. M. K. Karo, M. Y. Fajari, N. U. Fadhilah, and W. Y. Wardani, “Benchmarking Naïve Bayes and ID3 Algorithm for Prediction Student Scholarship,” IOP Conf Ser Mater Sci Eng, vol. 1232, no. 1, p. 012002, Mar. 2022, doi: 10.1088/1757-899x/1232/1/012002.
[31] Y. Li, W. Xu, W. Li, A. Li, and Z. Liu, “Research on hybrid intrusion detection method based on the ADASYN and ID3 algorithms,” Mathematical Biosciences and Engineering, vol. 19, no. 2, pp. 2030–2042, 2021, doi: 10.3934/MBE.2022095.
[32] B. Mahbooba, M. Timilsina, R. Sahal, and M. Serrano, “Explainable Artificial Intelligence (XAI) to Enhance Trust Management in Intrusion Detection Systems Using Decision Tree Model,” Complexity, vol. 2021, 2021, doi: 10.1155/2021/6634811.
[33] Veronika, S. Ramadhani, and I. M. Khamidah, “Expert System for Diagnosis Papaya Plant Disease with Backward Chaining and Dempster Shafer,” TEPIAN, vol. 3, no. 2, pp. 92–100, Jun. 2022, doi: 10.51967/tepian.v3i2.767.
[34] A. Setiawan, S. N. Fauzia, K. Kusmaya, K. S. Haryana, I. Abadi, and E. Yulianto, “Expert System for Diagnosing Disease Symptoms of Rice Pests Using the Dempster Shafer Algorithm and Fuzzy Tsukamoto Algorithm,” Jurnal Sisfokom (Sistem Informasi dan Komputer), vol. 11, no. 3, pp. 407–414, Dec. 2022, doi: 10.32736/sisfokom.v11i3.1425.
[35] S. I. Sezer, G. Elidolu, E. Akyuz, and O. Arslan, “An integrated risk assessment modelling for cargo manifold process on tanker ships under FMECA extended Dempster–Shafer theory and rule-based Bayesian network approach,” Process Safety and Environmental Protection, vol. 174, pp. 340–352, Jun. 2023, doi: 10.1016/j.psep.2023.04.024.
[36] N. E. I. Hamda, A. Hadjali, and M. Lagha, “Multisensor Data Fusion in IoT Environments in Dempster–Shafer Theory Setting: An Improved Evidence Distance-Based Approach,” Sensors, vol. 23, no. 11, Jun. 2023, doi: 10.3390/s23115141.
[37] R. G. Tanjung, “Expert System for Diagnosing Cataract Using Forward Chaining Method,” Journal of Computer Scine and Information Technology, pp. 13–17, Jan. 2023, doi: 10.35134/jcsitech.v9i1.56.
[38] E. Fitri Rahayu, “Comparative Analysis Expert System Of Certainty Factor Method With Dempster Shafer Method By Using Open Decision Maker Tool For Toddler At Vaccine House,” UG JURNAL, vol. 14, 2020.
[39] M. Iwan Shofyan et al., “Expert System Design for Web-Based Lecturer Scheduling,” J Phys Conf Ser, vol. 1175, no. 1, Jun. 2019, doi: 10.1088/1742-6596/1175/1/012119.
[40] S. Elmie Dansy et al., “Expert System for Diagnosis Coronavirus Disease,” International Journal of Artificial Intelligence, vol. 1, pp. 39–44, 2023, doi: 10.36079/lamintang.ijai-1001.537.
[41] Y. B. Arya, “Flash Damage Expert System Using the Dempster Shafer Method,” MECOMARE (International Journal of Mechanical Computational and Manufacturing Research), vol. 12, no. 1, pp. 10–15, 2023, doi: 10.35335/computational.v12i1.92.
[42] S. Y. Choi and S. H. Kim, “Knowledge acquisition and representation for high-performance building design: A review for defining requirements for developing a design expert system,” Sustainability (Switzerland), vol. 13, no. 9, May 2021, doi: 10.3390/su13094640.
[43] J. Fajaryanti and C. Author Abstrak, “Expert System Development To Identify Employee Personality Types Using Dempster Shafer Theory,” Jurnal Riset Informatika, vol. 4, no. 3, pp. 227–232, 2022, doi: https://doi.org/10.34288/jri.v4i3.389.
[44] S. R. D. Putranti, “Relationships between Mean, Median and Mode,” Aloha International Journal of Multidisciplinary Advancement (AIJMU), vol. 3, no. 4, p. 87, Apr. 2021, doi: 10.33846/aijmu30403.
[45] H. Henderi, F. Al Khudhorie, G. Maulani, S. Millah, and V. T. Devana, “A Proposed Model Expert System for Disease Diagnosis in Children to Make Decisions in First Aid,” INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi, vol. 6, no. 2, pp. 139–149, Aug. 2022, doi: 10.29407/intensif.v6i2.16912.
[46] M. Abdul Aziz Sujudi and dan Deny Hidayatullah, “Expert System Certainty Factor Method in Website-Based Pest Diagnosis of Eggplant Plants,” Jurnal Mantik, vol. 3, no. 36, pp. 428–438, 2020, [Online]. Available: https://iocscience.org/ejournal/index.php/mantik/index
Published
2024-09-16
How to Cite
[1]
Wiharto, S. M. Azizah, and B. Hendrasuryawan, “Expert System for Pregnancy Risk Diagnosis Using Decision Tree and Dempster-Shafer Method ”, j.electron.electromedical.eng.med.inform, vol. 6, no. 4, pp. 382-396, Sep. 2024.
Section
Research Paper
Copyright (c) 2024 Wiharto, Setia Mukti Azizah, Brilyan Hendrasuryawan
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