Zamzamy, Dian Arofati Nur (2023) Pengembangan MedHelp: Aplikasi Frontdesk Puskesmas Keputih Menggunakan Pendekatan Deep Learning. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kecerdasan buatan atau Artificial Intelligence merupakan salah satu bentuk teknologi informasi yang berkembang pesat saat ini. Contoh penerapan kecerdasan buatan adalah chatbot yang digunakan sebagai customer service untuk dapat melayani pengunjung selama 24 jam. Layanan informasi Puskesmas Keputih dilayani oleh petugas frontdesk secara manual dan hanya beroperasi sesuai jadwal operasional klinik. Maka dari itu, pada penelitian tugas akhir ini diusulkan pembuatan MedHelp aplikasi chatbot berbasis website untuk memberikan layanan informasi kepada pengunjung Puskesmas Keputih. Chatbot dikembangkan dengan memanfaatkan data pertanyaan dan jawaban terkait layanan Puskesmas Keputih. Data tersebut dilakukan preprocessing dengan metode NLP (Natural Language Processing) untuk selanjutnya dilakukan pelatihan model dengan pendekatan deep learning. Penggunaan algoritma BiLSTM untuk model chatbot berbasis teks memiliki performa yang lebih baik dibandingkan dengan algoritma LSTM dan GRU, dengan nilai akurasi sebesar 97,28% dengan nilai precision 97%, recall 96%, dan f1-score 96%. Implementasi model chatbot pada aplikasi berbasis website dapat memberikan jawaban berupa informasi layanan Puskesmas Keputih yang dibutuhkan oleh pengguna dengan hasil dari uji coba didapatkan akurasi sebesar 91%.
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Artificial intelligence is a form of information technology that is currently developing rapidly. An example of the application of artificial intelligence is a chatbot that is used as a customer service to be able to serve visitors 24 hours a day. Puskesmas Keputih information service is served by frontdesk officers manually and only operates according to the clinic's operational schedule. Therefore, in this final project research, it is proposed to create MedHelp, a website-based chatbot application to provide information to the Puskesmas Keputih visitors . Chatbot was developed by utilizing question and answer data related to Puskesmas Keputih services. The data is preprocessed using the NLP (Natural Language Processing) method and then the data will be trained using the LSTM (Long Short-Term Memory) algorithm to create chatbot model. The use of the BiLSTM algorithm for text-based chatbot models has better performance than the LSTM and GRU algorithms, with an accuracy value 97.28% with a precision value 97%, recall value 96%, and f1-score value 96%. The implementation of the chatbot model on website application can provide the information for users that obtained 91% accuracy.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Chatbot, frontdesk, NLP, LSTM, BiLSTM |
| Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T57.5 Data Processing |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information Technology > 59201-(S1) Undergraduate Thesis |
| Depositing User: | Dian Arofati Nur Zamzamy |
| Date Deposited: | 25 Aug 2023 08:51 |
| Last Modified: | 25 Aug 2023 08:51 |
| URI: | http://repository.its.ac.id/id/eprint/101944 |
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