BAYESIAN NETWORK UNTUK SISTEM PAKAR : TEKNOLOGI DAN KESEHATAN
Keywords:
Bayesian Network, Sistem Pakar, Prediksi Probabilistik, Kecerdasan Buatan, Aplikasi Teknologi dan KesehatanAbstract
Sistem pakar ialah salah satu penerapan teknologi yang berkembang saat ini. Sitem pakar akan mengadopsi dari pengetahuan dan pemikiran manusia yang divisualisasikan dalam komputer. Teknologi sistem pakar memberikan kemudahan dalam memecahkan suatu masalah yang ada dengan hasil berupa prediksi. Prediksi yang dilakukukan menggunakan metode Bayesian Network. Bayesian Network dapat menampikan hasil visualisasi berupa struktur graf hasil dari distribusi perhitungan probabilitas untuk digunakan pemodelan sistem dan prediksi. Hasil prediksi nantinya diperoleh tingkat akurasi pengujian tertinggi terhadap masalah tersebut. Pada paper ini lebih menekankan pada penerapan metode Bayesian Network untuk sistem pakar dalam bidang kesehatan dan teknologi. Sistem pakar ini sebenarnya dapat diterapkan berbagai bidang sebagai contoh pada bidang teknologi dan diagnosa medis untuk kesehatan. Pengambilan keputusan dan prediksi berdasarkan akurasi tertinggi inilah sangat baik dan penting dengan diterapkannya metode Bayesian Network
References
Adabor, E. S., Acquaah-Mensah, G. K., & Oduro, F. T. (2015). SAGA: A hybrid search algorithm for Bayesian Network structure learning of transcriptional regulatory networks. Journal of Biomedical Informatics, 53, 27–35. https://doi.org/10.1016/j.jbi.2014.08.010
Adiputra, M., Regasari, R., & Putri, M. (2018). Penerapan Bayesian Network Pada Sistem Pakar Ekspresi Wajah dan Bahasa Tubuh Melalui Pengamatan Indra Penglihatan Pada Foto. Journal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(1), 199–208.
Adiwisastra, M. F., & Basjaruddin, N. C. (2017). Intelligent Tutoring System Untuk Mengukur Kemampuan Kognitif Dalam Fisika Dasar Berbasis Metode Bayesian Network. IJCIT (Indonesian Journal on Computer and Information Technology), 2(2), 40–47.
Alizadeh, S. S., Mortazavi, S. B., & Sepehri, M. M. (2014). Building a model using bayesian network for assessment of posterior probabilities of falling from height at workplaces. Health Promotion Perspectives, 4(2), 187. https://doi.org/10.5681/hpp.2014.025
Axelrad, E. T., Sticha, P. J., Brdiczka, O., & Jianqiang Shen. (2013). A Bayesian Network Model for Predicting Insider Threats. 2013 IEEE Security and Privacy Workshops, 82–89. https://doi.org/10.1109/SPW.2013.35
Bayesian, U., For, N., & Users, C. (2004). Cybernetics Using Bayesian Networks for Monitoring. Cybernetics, 40(6), 789–799.
Bouzembrak, Y., Camenzuli, L., Janssen, E., & van der Fels-Klerx, H. J. (2016). Application of Bayesian Networks in the development of herbs and spices sampling monitoring system. Elsivier, November 2016, 1–7. https://doi.org/10.1016/j.foodcont.2017.04.019
Burrell, P. (2000). Application of Bayesian Network Learning Methods to Waste Water Treatment Plants. 2000 Kluwer Academic Publishers, 19–40.
Cai, Z., Sun, S., Si, S., & Yannou, B. (2011). Identifying product failure rate based on a conditional Bayesian network classifier. Expert Systems with Applications, 38(5), 5036–5043. https://doi.org/10.1016/j.eswa.2010.09.146
Carpani, M., & Giupponi, C. (2010). Construction of a bayesian network for the assessment of agri-environmental measures - The case study of the venice lagoon watershed. Italian Journal of Agronomy, 5(3), 265–274. https://doi.org/10.4081/ija.2010.265
Charles E.Kahn Jr, John J. Laur, and G. f. C. (2001). A Bayesian network for diagnosis of primary bone tumors A Bayesian Network for Diagnosis of Primary Bone Tumors. Journal of Digital Imaging, 14(July), 10–12. https://doi.org/10.1007/BF03190296
Cheng, H., & Hadjisophocleous, G. V. (2009). The modeling of fire spread in buildings by Bayesian network. Fire Safety Journal, 44(6), 901–908. https://doi.org/10.1016/j.firesaf.2009.05.005
Coles, M. D., Azzi, D., Haynes, B. P., & Hewitt, A. (2009). A Bayesian network approach to a biologically inspired motion strategy for mobile wireless sensor networks. Ad Hoc Networks, 7(6), 1217–1228. https://doi.org/10.1016/j.adhoc.2008.11.002
De Campos, L. M., Fernández-Luna, J. M., Gámez, J. A., & Puerta, J. M. (2002). Ant colony optimization for learning Bayesian networks. International Journal of Approximate Reasoning, 31(3), 291–311. https://doi.org/10.1016/S0888-613X(02)00091-9
del Sagrado, J., Sánchez, J. A., Rodríguez, F., & Berenguel, M. (2016). Bayesian networks for greenhouse temperature control. Journal of Applied Logic, 17, 25–35. https://doi.org/10.1016/j.jal.2015.09.006
Di Pietro, L., Guglielmetti Mugion, R., Musella, F., Renzi, M. F., & Vicard, P. (2017). Monitoring an airport check-in process by using Bayesian networks. Transportation Research Part A: Policy and Practice, 106(October 2016), 235–247. https://doi.org/10.1016/j.tra.2017.09.020
Dragicevic, S., Celar, S., & Turic, M. (2017). Bayesian network model for task effort estimation in agile software development. Journal of Systems and Software, 127, 109–119. https://doi.org/10.1016/j.jss.2017.01.027
Drury, B., Valverde-Rebaza, J., Moura, M. F., & de Andrade Lopes, A. (2017). A survey of the applications of Bayesian networks in agriculture. Engineering Applications of Artificial Intelligence, 65(January), 29–42. https://doi.org/10.1016/j.engappai.2017.07.003
Fakhravar, D., Khakzad, N., Reniers, G., & Cozzani, V. (2017). Security vulnerability assessment of gas pipelines using Discrete-time Bayesian network. Process Safety and Environmental Protection, 111, 714–725. https://doi.org/10.1016/j.psep.2017.08.036
Febrian, R. A., Regasari, R., & Putri, M. (2018). Sistem Pakar Diagnosis Penyakit Mulut menggunakan Metode Bayessian Network. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(2), 543–553.
Fine, S., & Ziv, A. (2003). Coverage directed test generation for functional verification using bayesian networks. IEEE Computer Society, 286–291.
Frank, J. M., Massman, W. J., & Ewers, B. E. (2016). A Bayesian model to correct underestimated 3-D wind speeds from sonic anemometers increases turbulent components of the surface energy balance. Atmospheric Measurement Techniques, 9(12), 5933–5953. https://doi.org/10.5194/amt-9-5933-2016
Gerstung, M., Baudis, M., Moch, H., & Beerenwinkel, N. (2009). Quantifying cancer progression with conjunctive Bayesian networks. Bioinformatics, 25(21), 2809–2815. https://doi.org/10.1093/bioinformatics/btp505
Gribaudo, M., Iacono, M., & Marrone, S. (2015). Exploiting Bayesian Networks for the analysis of combined Attack Trees. Electronic Notes in Theoretical Computer Science, 310, 91–111. https://doi.org/10.1016/j.entcs.2014.12.014
Groden, M., & Collette, M. (2017). Fusing fleet in-service measurements using Bayesian networks. Marine Structures, 54, 38–49. https://doi.org/10.1016/j.marstruc.2017.03.001
Haddawy, P., Hasan, A. H. M. I., Kasantikul, R., Lawpoolsri, S., Sa-angchai, P., Kaewkungwal, J., & Singhasivanon, P. (2018). Spatiotemporal Bayesian networks for malaria prediction. Artificial Intelligence in Medicine, 84, 127–138. https://doi.org/10.1016/j.artmed.2017.12.002
Hanafy, M., & ElMaraghy, H. (2014). Co-design of products and systems using a bayesian network. Procedia CIRP, 17, 284–289. https://doi.org/10.1016/j.procir.2014.01.129
Hänninen, M., Valdez Banda, O. A., & Kujala, P. (2014). Bayesian network model of maritime safety management. Expert Systems with Applications, 41(17), 7837–7846. https://doi.org/10.1016/j.eswa.2014.06.029
Haugom, G. P., & Friis-Hansen, P. (2011). Risk modelling of a hydrogen refuelling station using Bayesian network. International Journal of Hydrogen Energy, 36(3), 2389–2397. https://doi.org/10.1016/j.ijhydene.2010.04.131
Hernandez-Leal, P., Gonzalez, J. A., Morales, E. F., & Enrique Sucar, L. (2013). Learning temporal nodes Bayesian networks. International Journal of Approximate Reasoning, 54(8), 956–977. https://doi.org/10.1016/j.ijar.2013.02.011
Hernández, B., Pennington, S. R., & Parnell, A. C. (2015). Bayesian methods for proteomic biomarker development. EuPA Open Proteomics, 9, 54–64. https://doi.org/10.1016/j.euprot.2015.08.001
Huang, K., Zhou, C., Tian, Y.-C., Tu, W., & Peng, Y. (2017). Application of Bayesian network to data-driven cyber-security risk assessment in SCADA networks. 2017 27th International Telecommunication Networks and Applications Conference (ITNAC), november, 1–6. https://doi.org/10.1109/ATNAC.2017.8215355
Ilham, I. (2016). Rekayasa Perangkat Lunak Deteksi Dini Kecenderungan Gangguan Kesehatan Masyarakat Tertinggal Dan Pesisir Dengan Bayesian Network. Jurnal Informatika, 13(2), 127–131. https://doi.org/10.9744/informatika.13.2.39-43
Jäger, W. S., Christie, E. K., Hanea, A. M., den Heijer, C., & Spencer, T. (2017). A Bayesian network approach for coastal risk analysis and decision making. Coastal Engineering, January, 1–14. https://doi.org/10.1016/j.coastaleng.2017.05.004
Jensen, K. L., Toftum, J., & Friis-Hansen, P. (2009). A Bayesian Network approach to the evaluation of building design and its consequences for employee performance and operational costs. Building and Environment, 44(3), 456–462. https://doi.org/10.1016/j.buildenv.2008.04.008
Jin, Y., Su, Y., Zhou, X. H., & Huang, S. (2016). Heterogeneous multimodal biomarkers analysis for Alzheimer’s disease via Bayesian network. Eurasip Journal on Bioinformatics and Systems Biology, 2016(1), 4–11. https://doi.org/10.1186/s13637-016-0046-9
Johnson, S., Marker, L., Mengersen, K., Gordon, C. H., Melzheimer, J., Schmidt-Küntzel, A., Nghikembua, M., Fabiano, E., Henghali, J., & Wachter, B. (2013). Modeling the viability of the free-ranging cheetah population in Namibia: An object-oriented Bayesian network approach. Ecosphere, 4(7), 1–19. https://doi.org/10.1890/ES12-00357.1
Kaeser, T., Klingler, S., Schwing, A. G., & Gross, M. (2017). Dynamic Bayesian Networks for Student Modeling. IEEE Transactions on Learning Technologies, 1382(c), 1–1. https://doi.org/10.1109/TLT.2017.2689017
Katsanos, K., Spiliopoulos, S., Karunanithy, N., Krokidis, M., Sabharwal, T., & Taylor, P. (2014). Bayesian network meta-analysis of nitinol stents, covered stents, drug-eluting stents, and drug-coated balloons in the femoropopliteal artery. Journal of Vascular Surgery, 59(4), 1123–1133.e8. https://doi.org/10.1016/j.jvs.2014.01.041
Kondakci, S. (2010). Network Security Risk Assessment Using Bayesian Belief Networks. 2010 IEEE Second International Conference on Social Computing, 952–960. https://doi.org/10.1109/SocialCom.2010.141
Kreimer, A., & Herman, M. (2016). A Novel Structure Learning Algorithm for Optimal Bayesian Network: Best Parents. Procedia Computer Science, 96, 43–52. https://doi.org/10.1016/j.procs.2016.08.092
Kuang, D., Yang, R., Chen, X., Lao, G., Wu, F., Huang, X., Lv, R., Zhang, L., Song, C., & Ou, S. (2017). Depression recognition according to heart rate variability using Bayesian Networks. Journal of Psychiatric Research, 95, 282–287. https://doi.org/10.1016/j.jpsychires.2017.09.012
Kumar, S., & Tripathi, B. K. (2016). Modelling of Threat Evaluation for Dynamic Targets Using Bayesian Network Approach. Procedia Technology, 24, 1268–1275. https://doi.org/10.1016/j.protcy.2016.05.112
Kurniawan, R., & Wardhani, L. K. (2011). Sistem Pakar Untuk Mendiagnosa Penyakit Mata Dengan Metode Bayesian Network. SNTIKI III 2011, 309–315.
Kwisthout, J. (2011). Most probable explanations in Bayesian networks: Complexity and tractability. International Journal of Approximate Reasoning, 52(9), 1452–1469. https://doi.org/10.1016/j.ijar.2011.08.003
Landoni, G., Greco, T., Biondi-Zoccai, G., Neto, C. N., Febres, D., Pintaudi, M., Pasin, L., Cabrini, L., Finco, G., & Zangrillo, A. (2013). Anaesthetic drugs and survival: A bayesian network meta-analysis of randomized trials in cardiac surgery. British Journal of Anaesthesia, 111(6), 886–896. https://doi.org/10.1093/bja/aet231
Lee, S. M., & Abbott, P. A. (2003). Bayesian networks for knowledge discovery in large datasets: Basics for nurse researchers. Journal of Biomedical Informatics, 36(4–5), 389–399. https://doi.org/10.1016/j.jbi.2003.09.022
Li, D., Miwa, T., & Morikawa, T. (2016). Modeling time-of-day car use behavior: A Bayesian network approach. Transportation Research Part D: Transport and Environment, 47, 54–66. https://doi.org/10.1016/j.trd.2016.04.011
Li, H., Liu, C., Burge, L., Dae Ko, K., & Southerland, W. (2012). Predicting protein-protein interactions using full Bayesian network. 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, 544–550. https://doi.org/10.1109/BIBMW.2012.6470198
Liu, Y., Cheah, W. P., Kim, B., & Park, H. (2008). Predict Software Failure-prone by Learning Bayesian Network. International Journal of Advanced Science and Technology, 1(1), 35–42.
Liu, Y., Jia, Y., Feng, X., & Wu, J. (2018). Bus Route Design with a Bayesian Network Analysis of Bus Service Revenues. Hindawi Mathematical Problems in Engineering, 2018, 8.
López-Araquistain, J., Jarama, Á. J., Besada, J. A., de Miguel, G., & Casar, J. R. (2019). A new approach to map-assisted Bayesian tracking filtering. Information Fusion, 45(August 2017), 79–95. https://doi.org/10.1016/j.inffus.2018.01.002
López-Cruz, P. L., Larrañaga, P., DeFelipe, J., & Bielza, C. (2014). Bayesian network modeling of the consensus between experts: An application to neuron classification. International Journal of Approximate Reasoning, 55(1 PART 1), 3–22. https://doi.org/10.1016/j.ijar.2013.03.011
Lukman, A. (1950). Algoritma Bayesian Network Untuk Simulasi Prediksi Pemenang Pilkada Menggunakan Msbnx. 100–107.
Mahmudy, W. F., & Widodo, A. W. (2014). Klasifikasi Artikel Berita Menggunakan Naive Bayes Classifier yang Dimodifikasi. Tekno, 21.
Marlita, O. A., Kurniati, A. P., Informatika, F., & Telkom, I. T. (2015). Anomaly Detection Pada Intrusion Detection System ( Ids ) Menggunakan Metode Bayesian Network. Jurnal Penelitian Dan Pengembangan Telekomunikasi, 17(September 2015), 53–61.
Marrone, S. (2015). Using Bayesian networks for highly available cloud-based web applications. Journal of Reliable Intelligent Environments, 1(2–4), 87–100. https://doi.org/10.1007/s40860-015-0009-z
Mascaro, S., Nicholson, A. E., & Korb, K. B. (2011). Anomaly detection in vessel tracks using bayesian networks. CEUR Workshop Proceedings, 818, 99–107. https://doi.org/10.1016/j.ijar.2013.03.012
Mata, J., de Miguel, I., Durán, R. J., Merayo, N., Singh, S. K., Jukan, A., & Chamania, M. (2018). Artificial intelligence (AI) methods in optical networks: A comprehensive survey. Optical Switching and Networking, 28(January), 43–57. https://doi.org/10.1016/j.osn.2017.12.006
Meirelles, S. P., Rebolledo, D. C., Correia, L. F., Baptista, A. M., & Camargo, O. P. (2015). Uncemented Arthroplasty for Hip Pain and Fracture after Metastatic Disease and Multiple Myeloma: Case Series, Exploratory Graphical Analysis and Bayesian Network Modeling. Journal of Orthopedic Oncology, 01(01), 1–7. https://doi.org/10.4172/2472-016X.1000103
Mendes, E. (2007). The Use of a Bayesian Network for Web Effort Estimation. Proceedings of International Conference on Web Engineering - ICWE’07, 2004, 90–104. https://doi.org/10.1109/ICWE.2008.16
Moreira, C., & Wichert, A. (2018). Are quantum-like Bayesian networks more powerful than classical Bayesian networks? Journal of Mathematical Psychology, 82, 73–83. https://doi.org/10.1016/j.jmp.2017.11.003
Muhammad Hasbi, Rully Mujiastuti, M., & Syarip. (n.d.). PENERAPAN METODE BAYESIAN NETWORK DALAM APLIKASI E-LEARNING BERBASIS WEB. Jurnal Sistem Informasi, Teknologi Informasi Dan Komputer, 7(2).
Mukesh Kumari, Dr. Rajan Vohra, A. A. (2014). Prediction of Diabetes Using Bayesian Network. International Journal of Computer Science and Information Technologies, 5(4), 5174–5178.
Myers, C. L., & Troyanskaya, O. G. (2007). Context-sensitive data integration and prediction of biological networks. Bioinformatics, 23(17), 2322–2330. https://doi.org/10.1093/bioinformatics/btm332
Naticchia, B., Fernandez-Gonzalez, A., & Carbonari, A. (2007). Bayesian Network model for the design of roofpond equipped buildings. Energy and Buildings, 39(3), 258–272. https://doi.org/10.1016/j.enbuild.2006.07.002
Network, D. S. E. M. B. (2016). Deteksi Spam Email Menggunakan Bayesian Network. Prosiding Annual Research Seminar, 2(1), 209–211.
Nielsen, S. H., & Nielsen, T. D. (2008). Adapting Bayes network structures to non-stationary domains. International Journal of Approximate Reasoning, 49(2), 379–397. https://doi.org/10.1016/j.ijar.2008.02.007
Nillius, P., Sullivan, J., Carlsson, S., Vouton, V., & Box, P. O. (2006). Multi-Target Tracking – Linking Identities using Bayesian Network Inference. Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference On, 2187–2194. https://doi.org/10.1109/CVPR.2006.198
Ordóñez Galán, C., Matías, J. M., Rivas, T., & Bastante, F. G. (2009). Reforestation planning using Bayesian networks. Environmental Modelling and Software, 24(11), 1285–1292. https://doi.org/10.1016/j.envsoft.2009.05.009
Pan, R., Mejia Sanchez, L., & Inc, C. (2017). Obtaining Reliability Insights during a Product’s Conceptual Design Process through Bayesian Network Modeling. Industrial Engineering & Management, 06(03). https://doi.org/10.4172/2169-0316.1000224
Perkusich, M., Soares, G., Almeida, H., & Perkusich, A. (2015). A procedure to detect problems of processes in software development projects using Bayesian networks. Expert Systems with Applications, 42(1), 437–450. https://doi.org/10.1016/j.eswa.2014.08.015
Poeschl, S., Wirth, F., & Bauernhansl, T. (2016). Situation-based Methodology for Planning the Commissioning of Special Machinery Using Bayesian Networks. Procedia CIRP, 57, 247–252. https://doi.org/10.1016/j.procir.2016.11.043
Prabhakaran, R., Krishnaprasad, R., Nanda, M., & Jayanthi, J. (2016). System Safety Analysis for Critical System Applications Using Bayesian Networks. Procedia Computer Science, 93(September), 782–790. https://doi.org/10.1016/j.procs.2016.07.294
Prathivi, R. (2015). Klasifikasi Data Trafik Internet Menggunakan Metode Bayes Network ( Studi Kasus Jaringan Internet Universitas Semarang ). Jurnal Transformatika, 12(2), 42–45.
Rao, M., & Kamila, N. K. (2017). Bayesian network based energy efficient ship motion monitoring. Karbala International Journal of Modern Science. https://doi.org/10.1016/j.kijoms.2017.11.001
Rehg, J. M., Murphy, K. P., & Fieguth, P. W. (1999). Vision-Based Speaker Detection Using Bayesian Networks. Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference, 00(c), 2.
Retno, D., & Saputro, S. (2009). Memprediksi Curah Hujan ( Data Spatio-Temporal ) Dengan Metode Bayesian Networks. Prosiding Seminar Nasional Penelitian, Pendidikan Dan Penerapan MIPA, 1, 37–42.
Rochmad, M. (2009). Identifikasi Kerusakan Pankreas Melalui Iridology Menggunakan Metode Bayes Untuk Pengenalan Diabetes Mellitus. Seminar Nasional Informatika 2009, 2009(semnasIF), 33–42.
Rupareliya, J., Vithlani, S., & Gohel, C. (2016). Securing VANET by Preventing Attacker Node Using Watchdog and Bayesian Network Theory. Procedia Computer Science, 79, 649–656. https://doi.org/10.1016/j.procs.2016.03.082
Sari, B. N., Permana, H., Trihandoko, K., Jamaludin, A., & Umaidah, Y. (2017). Prediksi Produktivitas Tanaman Padi di Kabupaten Karawang Menggunakan Bayesian Networks. Jurnal INFOTEL, 9.
Setiawan, W., Kom, M., & Riza, L. S. (n.d.). PENGGUNAAN METODE BAYESIAN NETWORK DALAM SISTEM PAKAR Indyana Meigarani Ketentuan Umum Kata Kunci. Jurnal Program Komputer, 1–5.
Shi, D., Zurada, J., & Guan, J. (2016). A Bayesian network approach to classifying bad debt in hospitals. Proceedings of the Annual Hawaii International Conference on System Sciences, 2016–March, 3298–3307. https://doi.org/10.1109/HICSS.2016.412
Sierra, L. A., Yepes, V., García-Segura, T., & Pellicer, E. (2018). Bayesian network method for decision-making about the social sustainability of infrastructure projects. Journal of Cleaner Production, 176, 521–534. https://doi.org/10.1016/j.jclepro.2017.12.140
Su, X., Bai, P., Du, F., & Feng, Y. (2011). Application of Bayesian Networks in Situation Assessment. Intelligent Computing and Information Science: International Conference, ICICIS 2011, Chongqing, China, January 8-9, 2011. Proceedings, Part I, 643–648. https://doi.org/10.1007/978-3-642-18129-0_97
Suchánek, P., Marecki, F., & Bucki, R. (2014). Self-learning bayesian networks in diagnosis. Procedia Computer Science, 35(C), 1426–1435. https://doi.org/10.1016/j.procs.2014.08.200
Taylor, D., Biedermann, A., Hicks, T., & Champod, C. (2018). A template for constructing Bayesian networks in forensic biology cases when considering activity level propositions. Forensic Science International: Genetics, 33(November 2017), 136–146. https://doi.org/10.1016/j.fsigen.2017.12.006
Thu, H. N. T., & Ngoc, D. V. T. (2014). Improve Bayesian Network to Generating Vietnamese Sentence Reduction. International Conference on Future Information Engineering, 10, 190–195. https://doi.org/10.1016/j.ieri.2014.09.076
Tinaliah. (2015). Aplikasi sistem pakar untuk diagnosa penyakit hewan ternak sapi dengan bayesian network. Jurnal Ilmiah SISFOTENIKA, 5(1), 13–24.
Torabi, R., Moradi, P., & Khantaimoori, A. R. (2012). Predict Student Scores Using Bayesian Networks. Procedia - Social and Behavioral Sciences, 46, 4476–4480. https://doi.org/10.1016/j.sbspro.2012.06.280
Wan, P., Zongliang, & Yue , Zhan Xie , Qiang Gao , Mengyao Yu , Zhiwei Yang, J. H. (2013). Mechanisms of Radiation Resistance in Deinococcus radiodurans R1 Revealed by the Reconstruction of Gene Regulatory Network Using Bayesian Network Approach. Journal of Proteomics & Bioinformatics, 01(S6), 6–10. https://doi.org/10.4172/jpb.S6-007
Wang, J., Tang, Y., Nguyen, M., & Altintas, I. (2014). A Scalable Data Science Workflow Approach for Big Data Bayesian Network Learning. 2014 IEEE/ACM International Symposium on Big Data Computing, 16–25. https://doi.org/10.1109/BDC.2014.10
Wang, Z., & Chan, L. (2011). Using Bayesian Network Learning Algorithm to Discover Causal Relations in Multivariate Time Series. 2011 IEEE 11th International Conference on Data Mining, 814–823. https://doi.org/10.1109/ICDM.2011.153
Weil, K. K., Cronan, C. S., Meyer, S. R., Lilieholm, R. J., Danielson, T. J., Tsomides, L., & Owen, D. (2018). Predicting stream vulnerability to urbanization stress with Bayesian network models. Landscape and Urban Planning, 170(November), 138–149. https://doi.org/10.1016/j.landurbplan.2017.11.001
Wicaksono, Y. A., Santoso, H. A., & Earthquake, D. (2016). Implementasi Metode Bayesian Network Untuk Decision Support System Pada. Seminar Nasional Teknologi Informasu Dan Multimedia 2016, 6–7.
Wijesiri, B., Deilami, K., McGree, J., & Goonetilleke, A. (2018). Use of surrogate indicators for the evaluation of potential health risks due to poor urban water quality: A Bayesian Network approach. Environmental Pollution, 233, 655–661. https://doi.org/10.1016/j.envpol.2017.10.076
Wu, J., & Yang, M. (2013). Modeling Commuters’ Travel Behavior by Bayesian Networks. Procedia - Social and Behavioral Sciences, 96(Cictp), 512–521. https://doi.org/10.1016/j.sbspro.2013.08.060
Xu, X., Zhu, L., Sun, D., Tran, A. B., Weber, I., Fu, M., & Bass, L. (2016). Error Diagnosis of Cloud Application Operation Using Bayesian Networks and Online Optimisation. Proceedings - 2015 11th European Dependable Computing Conference, EDCC 2015, 37–48. https://doi.org/10.1109/EDCC.2015.15
Yu, D., Huang, X., Wang, H., Cui, Y., Hu, Q., & Zhou, R. (2010). Short-Term Solar Flare Level Prediction Using a Bayesian Network Approach. The Astrophysical Journal, 710(1), 869–877. https://doi.org/10.1088/0004-637X/710/1/869
Zarkasi, I. B., H, R. M., Fitria, D. N., Studi, P., Informatika, T., & Sains, F. (2011). Metode Bayesian Networks untuk Menyelesaikan Occlusion pada Object Tracking. Journal Al - Azhar Indonesia Seri Sains Dan Teknologi, 1(2), 89–94.
Zhang, G., & Thai, V. V. (2018). Addressing the epistemic uncertainty in maritime accidents modelling using Bayesian network with interval probabilities. Safety Science, 102(October 2017), 211–225. https://doi.org/10.1016/j.ssci.2017.10.016
Zhang, L., Wu, X., Skibniewski, M. J., Zhong, J., & Lu, Y. (2014). Bayesian-network-based safety risk analysis in construction projects. Reliability Engineering and System Safety, 131, 29–39. https://doi.org/10.1016/j.ress.2014.06.006
3.png)
1.png)
1.png)
