The Certainty Factor Algorithm Applied in Case Based Reasoning Method for Stunting Detection Expert System
Article Sidebar
Read Counter : 543
Download : 287
Main Article Content
Abstract
Stunting is a severe problem that significantly impacts future generations' growth and the quality of Human Resources (HR). In addition to the under-five age factor, stunting is also influenced by several interrelated factors. This research aims to apply the Certainty Factor algorithm in an expert system to detect stunting using the Case-Based Reasoning Method. The application of the CF algorithm by utilizing expert judgment has successfully strengthened the CBR method steps by calculating the similarity level. The results of the User Acceptance Test by 25 respondents showed an approval rate of 85%. If interpreted using the user approval range, these results are 81% - 100%, with a very high level of agreement. Based on calculating risky and safe stunting example cases, the CBR Method shows a similarity rate of 29.26% and 70.73%, respectively. Furthermore, safe stunting cases were analyzed using the CF algorithm with a confidence ratio of 91%.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The proposed policy for journals that offer open access
Authors who publish with this journal agree to the following terms:
- Copyright on any article is retained by the author(s).
- Author grant the journal, right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
- The article and any associated published material is distributed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
References
Friska, E., & Andriani, H. (2022). The Utilization of Android-Based Application as a Stunting Prevention E-Counseling Program Innovation during Covid-19 Pandemic. Journal of Maternal and Child Health, 6(5), 323–332. https://doi.org/10.26911/thejmch.2021.06.05.02
Habibie, D. R. (2019). Analisa Sistem Pakar Diagnosis Awal Penyakit Amebiasis Dengan Metode Case Based Reasoning. Jursima, 7(2), 70. https://doi.org/10.47024/js.v7i2.181
Kementerian Kesehatan Republik Indonesia. (2018). Laporan Nasional Riset Kesehatan Dasar. Kementrian Kesehatan RI, 1–582.
Kementerian Kesehatan RI. (2020). Indikator Program Kesehatan Masyarakat dalam RPJMN dan Rentra Kementerian Kesehatan 2020-2024. Katalog Dalam Terbitan. Kementerian Kesehatan RI, 1–99. https://kesmas.kemkes.go.id/assets/uploads/contents/attachments/ef5bb48f4aaae60ebb724caf1c534a24.pdf
Kementerian PPN/ Bappenas. (2018). Pedoman Pelaksanaan Intervensi Penurunan Stunting Terintegrasi di Kabupaten/Kota. Rencana Aksi Nasional Dalam Rangka Penurunan Stunting: Rembuk Stunting, November, 1–51. https://www.bappenas.go.id
Kurniasari, A. A., Puspitasari, T. D., & Kartika, R. C. (2022). Sistem Informasi Diagnosis Ikterus Neonatorum Menggunakan Metode Fuzzy Tsukamoto. Jurnal Teknologi Informasi Dan Terapan, 9(2), 81–86. https://doi.org/10.25047/jtit.v9i2.274
Purwanto, H. I., & Wibisono, S. (2022). AHP-CBR Untuk Deteksi Dini Stunting Pada Balita Menggunakan Algoritma Similaritas KNN. INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics, 7(1), 64–73. http://ejournal-binainsani.ac.id/index.php/ITBI/article/view/2121
Puspitasari, P. S. D., Etikasari, B., Puspitasari, T. D., Kartika, R. C., Perdanasari, L., & Kurniasari, A. A. (2022). Android-Based Application for Children’s Growth Monitoring as a Complement for Child Development Card. Jurnal Teknokes, 15(1), 44–50. https://doi.org/10.35882/teknokes.v15i1.7
Putri, P. A., & Mustafidah, H. (2011). Sistem Pakar untuk Mendiagnosa Penyakit Hati Menggunakan Metode Forward Chaining (Expert System for Diagnosing Liver Disease Using Forward Chaining). Juita, 4, 2086–9398.
Qurrothul Uyun, I., I Gede, W., Gumilang, M. A., & Setyo Wibowo, N. (2022). Early Detection Of Development To Children Aged 0 – 24 Months With Developmental Pre-screening Questionnaire Model Using Certainty Factor Method. JTIM : Jurnal Teknologi Informasi Dan Multimedia, 4(2), 122–132. https://doi.org/10.35746/jtim.v4i2.231
Rahima, M. (2020). Aplikasi Android Deteksi Dini Rawan Stunting Pada Balita Menggunakan Metode Certainty Factor. Repositori Universitas Muhammadiyah Malang. https://eprints.umm.ac.id/64501/
Rahutomo, R., Elwirehardja, G. N., Dominic, N., Caesario, B., & Pardamean, B. (2022). Database Management System Design Improvement for Child Stunting Data Collection in Multiple Observation Areas. 2022 International Conference on Information Management and Technology (ICIMTech), 149–154. https://doi.org/10.1109/ICIMTech55957.2022.9915209
Redaksi Mediakom. (2020). Saat Berharga untuk Tumbuh Kembang Si Kecil. Mediakom Kementerian Kesehatan RI. https://mediakom.kemkes.go.id/2020/03/saat-berharga-untuk-tumbuh-kembang-si-kecil/
Ritonga, K. (2019). Sistem Pakar Mendiagnosa Penyakit Kanker Kulit Melanoma Menggunakan Metode Case Based Reasoning. Jurnal Informasi Dan Teknologi Ilmiah (INTI), 7(3), 5.
Rohadi, E., Triswidrananta, O. D., & Ayu, J. (2020). Sistem Pakar Pendeteksi Kerusakan Kamera DSLR Dengan Metode Case Based Reasoning. Journal Informatika Dan Teknologi Informasi, 1–6.
Rostika Flora. (2021). Stunting Dalam Kajian Molekuler. In Unsri Press. UPT. Penerbit dan Percetakan Universitas Sriwijaya. http://repository.unsri.ac.id/46448/1/Buku_Stunting.pdf
Sapriatin, B., & Sianturi, F. A. (2021). Penerapan Teorema Bayes Mendeteksi Stunting pada Balita. Jurnal Media Informatika [Jumin], 3(1), 24–37. https://ejournal.sisfokomtek.org/index.php/jumin/article/view/203/175
Sudikno, Irawan, I. R., Setyawati, B., Sari, Y. D., Wiryawan, Y., Puspitasari, D. S., Widodo, Y., Ahmadi, F., Rachmawati, R., Amaliah, N., Arfines, P. P., Rosha, B. C., Pambudi, J., Aditianti, Julianti, E. D., & Safitri, A. (2019). Laporan Akhir Penelitian Status Gizi Balita Tahun 2019. Kemenkes RI, 1–150. https://cegahstunting.id/unduhan/publikasi-data/
WHO. (2019). World health statistics 2019: monitoring health for the SDGs, sustainable development goals. https://doi.org/.1037//0033-2909.I26.1.78
Wibowo, D. S., Yanitasari, Y., & Dedih, D. (2018). Sistem Pakar Diagnosis Potensi Penyebaran Penyakit pada Tanaman Cabai Menggunakan Fuzzy Mamdani. Jurnal Teknologi Dan Sistem Komputer, 6(2), 71–75. https://doi.org/10.14710/jtsiskom.6.2.2018.71-75
Wiro Sasmito, G. (2017). Sistem Pakar Diagnosis Hama dan Penyakit Tanaman Hortikultura dengan Teknik Inferensi Forward dan Backward Chaining. Jurnal Teknologi Dan Sistem Komputer, 5(April), 59–74. https://doi.org/10.14710/jtsiskom.5.2.2017.69-74
Wiryawan, I. G., Hendyca Putra, D. S., Pristiwaningsih, E. R., Mulyadi, E., Destarianto, P., & Agustianto, K. (2022). Studi Evaluasi Sistem Informasi Geografi Kasus Stunting Menggunakan COBIT 5 Framework. Jurnal Sistem Informasi Bisnis, 12(1), 10–16. https://doi.org/10.21456/vol12iss1pp10-16
Wiryawan, I. G., Oktava, H., Mulyadi, E., Destarianto, P., & Agustianto, K. (2021). Analysis of Upper Arm Circumference Using Statistical Approach as a Risk Factor of Stunting Cases. Proceedings of the First International Conference on Social Science, Humanity, and Public Health (ICOSHIP 2020), 514, 69–73. https://doi.org/10.2991/assehr.k.210101.016
World Health Organizations. (2019). World Health Statistics data visualizations dashboard. https://apps.who.int/gho/data/node.sdg.2-2-viz-1?lang=en#content
Zuhriyah, N., & Priyandoko, G. (2020). Sistem Pakar Mendeteksi Gangguan Gizi Pada Anak Balita Menggunakan Metode Certainty Factor Berbasis Web. Publishing-Widyagama.Ac.Id, Ciastech, 551–560.