Chatbot for Diagnosis of Pregnancy Disorders using Artificial Intelligence Markup Language (AIML)

Alam Rahmatulloh - Department of Informatics, Faculty of Engineering, Siliwangi University
Anjar Ginanjar - Department of Informatics, Faculty of Engineering, Siliwangi University
Irfan Darmawan - Department of Information System, Faculty of Industrial Engineering, Telkom University
Neng Kurniati - Department of Informatics, Faculty of Engineering, Siliwangi University
Erna Haerani - Department of Informatics, Faculty of Engineering, Siliwangi University


Citation Format:



DOI: http://dx.doi.org/10.30630/joiv.7.1.1595

Abstract


Artificial Intelligence has evolved in sophistication and widespread use. This study aims to create a chatbot application in the health sector regarding the early diagnosis of pregnancy disorders. Based on basic health research, only 44 percent of pregnant women know the danger signs of pregnancy. The chatbot application developed is expected to facilitate and increase knowledge for pregnant women about the danger signs of pregnancy, especially early diagnosis of pregnancy disorders. The chatbot application was developed with artificial intelligence technology based on Artificial Intelligence Markup Language with the question-answer concept using the Pandorabots framework. The test is carried out in two stages: functional and pattern matching. The functional testing uses the black-box testing method, and the pattern-matching test on the chatbot uses the sentence similarity and bigram methods based on user input and keywords similarity in the bot's knowledge base. The functional testing results show that the chatbot application runs well, with the eligibility criteria reaching 81.4% and the results of the keyword similarity test (pattern matching) are zero to one, in the sense that the value of one has the same similarity between user input and pattern. Meanwhile, the zero value has no similarities, so the bot will respond to it as free input. So it can be concluded that the bot can respond to user questions when the pattern and input have the same level of similarity.



Keywords


AIML, Artificial Intelligence, Chatbot, Diagnosis

References


B. Kependudukan and B. Nasional, “Survei Demografi dan Kesehatan Indonesia,” 2013.

S. Susiana, “Angka Kematian Ibu: Faktor Penyebab dan Upaya Penanganannya,” INFO Singkat: Kajian Singkat Terhadap Isu Aktual dan Strategis, vol. XI, no. 24, pp. 13–18, 2015.

K. Ibu, “Kesehatan Ibu & Anak,” no. Gambar 2, 2012.

B. Penelitian, D. A. N. Pengembangan, and K. K. Ri, “Riset kesehatan dasar,” 2010.

R. Singh, M. Paste, N. Shinde, H. Patel, and N. Mishra, “Chatbot using TensorFlow for small Businesses,” in 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), Apr. 2018, pp. 1614–1619. doi: 10.1109/ICICCT.2018.8472998.

A. Følstad and P. B. Brandtzaeg, “Users’ experiences with chatbots: findings from a questionnaire study,” Qual User Exp, vol. 5, no. 1, p. 3, Dec. 2020, doi: 10.1007/s41233-020-00033-2.

D. Lee and S. Yeo, “Developing an AI-based chatbot for practicing responsive teaching in mathematics,” Comput Educ, vol. 191, p. 104646, Dec. 2022, doi: 10.1016/j.compedu.2022.104646.

A. Rahmatulloh and H. Suhendy, “MikrobatX: Deep Learning Approach for Microscopic Identification and Classification of Medicinal Leaf Simplicia Fragments Using Sift Feature Extraction,” SSRN Electronic Journal, 2022, doi: 10.2139/ssrn.4226649.

P. Smutny and P. Schreiberova, “Chatbots for learning: A review of educational chatbots for the Facebook Messenger,” Comput Educ, vol. 151, p. 103862, Jul. 2020, doi: 10.1016/j.compedu.2020.103862.

E. Mogaji, J. Balakrishnan, A. C. Nwoba, and N. P. Nguyen, “Emerging-market consumers’ interactions with banking chatbots,” Telematics and Informatics, vol. 65, p. 101711, Dec. 2021, doi: 10.1016/j.tele.2021.101711.

N. Thi Khanh Chi, "Transforming travel motivation into an intention to pay for nature conservation in national parks: The role of Chatbot e-services," J Nat Conserv, vol. 68, p. 126226, Aug. 2022, doi: 10.1016/j.jnc.2022.126226.

D. Ireland et al., “Introducing Edna: A trainee chatbot designed to support communication about additional (secondary) genomic findings,” Patient Educ Couns, vol. 104, no. 4, pp. 739–749, Apr. 2021, doi: 10.1016/j.pec.2020.11.007.

H. Jiang, Y. Cheng, J. Yang, and S. Gao, “AI-powered chatbot communication with customers: Dialogic interactions, satisfaction, engagement, and customer behavior,” Comput Human Behav, vol. 134, p. 107329, Sep. 2022, doi: 10.1016/j.chb.2022.107329.

F. Jiang et al., “Artificial intelligence in healthcare: past, present and future,” Stroke Vasc Neurol, vol. 2, no. 4, pp. 230–243, Dec. 2017, doi: 10.1136/svn-2017-000101.

S. Siddique and J. C. L. Chow, “Machine Learning in Healthcare Communication,” Encyclopedia, vol. 1, no. 1, pp. 220–239, Feb. 2021, doi: 10.3390/encyclopedia1010021.

P. Butow and E. Hoque, “Using artificial intelligence to analyse and teach communication in healthcare,” The Breast, vol. 50, pp. 49–55, Apr. 2020, doi: 10.1016/j.breast.2020.01.008.

S. Colabianchi, M. Bernabei, and F. Costantino, “Chatbot for training and assisting operators in inspecting containers in seaports,” Transportation Research Procedia, vol. 64, pp. 6–13, 2022, doi: 10.1016/j.trpro.2022.09.002.

C. V. Misischia, F. Poecze, and C. Strauss, “Chatbots in customer service: Their relevance and impact on service quality,” Procedia Comput Sci, vol. 201, pp. 421–428, 2022, doi: 10.1016/j.procs.2022.03.055.

E. W. T. Ngai, M. C. M. Lee, M. Luo, P. S. L. Chan, and T. Liang, “An intelligent knowledge-based chatbot for customer service,” Electron Commer Res Appl, vol. 50, p. 101098, Nov. 2021, doi: 10.1016/j.elerap.2021.101098.

D. S. Hormansyah and Y. P. Utama, “Aplikasi Chatbot Berbasis Web Pada Sistem Informasi Layanan Publik Kesehatan Di Malang Dengan Menggunakan Metode Tf-Idf,” Jurnal Informatika Polinema, vol. 4, no. 3, p. 224, 2018, doi: 10.33795/jip.v4i3.211.

J. Weizenbaum, “ELIZA — a computer program for the study of natural language communication between man and machine,” Commun ACM, vol. 26, no. 1, pp. 23–28, Jan. 1983, doi: 10.1145/357980.357991.

B. AbuShawar and E. Atwell, “ALICE Chatbot: Trials and Outputs,” Computación y Sistemas, vol. 19, no. 4, Dec. 2015, doi: 10.13053/cys-19-4-2326.

Md. S. Satu, Md. H. Parvez, and Shamim-Al-Mamun, “Review of integrated applications with AIML based chatbot,” in 2015 International Conference on Computer and Information Engineering (ICCIE), Nov. 2015, pp. 87–90. doi: 10.1109/CCIE.2015.7399324.

A. Dewi and B. Setiaji, “Pemanfaatan Sentence-Similarity Measurement Untuk Proses Pencarian Pola Pada Chatbot Berbasis Pattern-Matching,” Seminar Nasional Teknologi Informasi dan Multimedia 2014, pp. 39–44, 2014.

R. Sutoyo, A. Chowanda, A. Kurniati, and R. Wongso, “Designing an Emotionally Realistic Chatbot Framework to Enhance Its Believability with AIML and Information States,” Procedia Comput Sci, vol. 157, pp. 621–628, 2019, doi: 10.1016/j.procs.2019.08.226.

Y. Sharma and S. Gupta, “Deep Learning Approaches for Question Answering System,” Procedia Comput Sci, vol. 132, pp. 785–794, 2018, doi: 10.1016/j.procs.2018.05.090.

F. Azwary, F. Indriani, and D. T. Nugrahadi, “Question Answering System Berbasis Artificial Intelligence Markup Language,” Kumpulan Jurnal Ilmu Komputer, vol. 04, no. 01, pp. 48–60, 2016.

E. Bahartyan, N. Bahtiar, and I. Waspada, “Integrasi Chatbot Berbasis Aiml Pada Website E-Commerce Sebagai Virtual Assistant Dalam Pencarian Dan Pemesanan Produk (Studi Kasus Toko Buku Online Edu4Indo.Com),” Jurnal Masyarakat Informatika, vol. 5, no. 10, 2015, doi: 10.14710/jmasif.5.10.34-43.

B. Rusmarasy, B. Priyambadha, and F. Pradana, “Pengembangan Chat Bot pada CoMa untuk Memberikan Motivasi Kepada Pengguna Menggunakan AIML,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 3, no. 5, pp. 4484–4490, 2019.

J. Informatika, F. I. Komputer, and U. A. Yogyakarta, “IMPLEMENTASI ALGORITMA SENTENCE SIMILARITY Dicky Andhika Rizaldhi , 2 Galih Adhi Kuncoro Rosyad , 3 Anggit Dwi Hartanto,” vol. 4, no. 1, pp. 10–14, 2020.




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