DETEKSI DINI PENYAKIT BALITA MENGGUNAKAN ALGORITMA SORENSEN BERBOBOT
DOI:
https://doi.org/10.33884/jif.v9i02.3744Keywords:
Sistem Pakar, Balita, Case-Based Reasoning, AHP SorensenAbstract
There are still many parents who do not have sufficient understanding in terms of toddler disease. One way to provide education is the availability of a system that can be used for consultation based on the symptoms of illness experienced by toddlers and the actions needed to overcome them. The system that will be built is an expert system that can relatively provide suggestions for solutions to children's health problems using the Case Based Reasoning (CBR) method. namely an expert system that uses case-based reasoning methods, namely looking for similarities of a disease compared to a disease that has existed before. In this study, the CBR method was combined with a weighting process using the pairwise comparison method which was within the scope of the AHP (Analytic Hierarchy Process) method. In comparing consultations with old diseases that already exist in the system, and looking for similarities from the comparison results, the Sorensen similarity algorithm is used. This study resulted in weights with 3 symptom categories, namely mild symptoms with a weight of 0.09, moderate symptoms with a weight of 0.24 and severe symptoms with a weight of 0.67 and will recommend several diseases with a similarity above 0.5 and diseases with a similarity below 0.5 will be entered into the revise table to find a solution.
References
[2] S. Kusumadewi, Artificial Intelligence (Teknik dan Aplikasinya). Yogyakarta: Graha Ilmu, 2003.
[3] J. L. Kolodner, “An introduction to case-based reasoning,” Artif. Intell. Rev., vol. 6, no. 1, hal. 3–34, 1992, doi: 10.1007/BF00155578.
[4] R. Adawiyah, “Case Based Reasoning Untuk Diagnosis Penyakit Demam Berdarah,” Intensif, vol. 1, no. 1, hal. 63, 2017, doi: 10.29407/intensif.v1i1.544.
[5] Tursina, “Case-Based Reasoning Untuk Diagnosa Penyakit Respirologi Anak Menggunakan Similaritas Simple Mathcing Coefficient,” vol. 4, no. 1, hal. 17–22, 2012.
[6] M. Y. C. Mage, D. R. Sina, T. Widiastuti, J. I. Komputer, U. N. Cendana, dan B. City, “CASE BASED REASONING UNTUK MENDIAGNOSA PENYAKIT ANAK,” vol. 5, no. 2, hal. 42–47, 2017.
[7] M. N. Sutoyo, “DIAGNOSA KEADAAN GIZI ANAK MENGGUNAKAN METODE CASE BASED REASONING Children Nutrition Diagnosis Using the Case Based Reasoning Method,” vol. 2, no. 2, hal. 25–33, 2019.
[8] F. Tahel, “PENERAPAN EXPERT SYSTEM PADA ANAK BALITA UNTUK MENDETEKSI OBESITAS MENGGUNAKAN METODE,” vol. 2, no. 2, hal. 20–28, 2018.
[9] T. R. Maulidia, T. Rismawan, dan S. Bahri, “Implementasi Case Based Reasoning Sistem Diagnosa Penyakit Anak Berbasis Web,” vol. 05, no. 03, 2017.
[10] R. Josefa, R. Sovia, E. Praja, dan W. Mandala, “Sistem Pakar Diagnosa Penyakit Pneumonia Pada Anak Menggunakan Metode Case Based Reasoning,” hal. 868–872, 2019.
[11] D. Rachmat, “Implementasi Metode Sorensen Coefficient Dalam Menentukan Daerah Berpotensi Rawan Penyakit Demam Berdarah (Studi Kasus : Kota Pontianak),” JUSTIN (Jurnal Sist. dan Teknol. Informasi), vol. 2(3), hal. 172–177, 2014.
[12] V. A. Arundy, I. Fitri, dan E. Mardiani, “Implementasi Metode Penalaran CBR dalam Mengidentifikasi Gejala Awal Penyakit Jantung menggunakan Algoritma Sorensen Coeffient,” J. JTIK (Jurnal Teknol. Inf. dan Komunikasi), vol. 5, no. 3, hal. 306, 2021, doi: 10.35870/jtik.v5i3.220.
[13] K. T. N. Iman dan S. Wibisono, “Pembobotan Menggunakan Pairwise Comparison Pada Case Based Reasoning Rekomendasi Hotel,” J. Manaj. Inform. Sist. Inf., vol. 4, no. 1, hal. 9–18, 2021.
[14] A. Amanaturohim dan S. Wibisono, “Penentuan Parameter Terbobot Menggunakan Pairwise Comparison Untuk CBR Deteksi Dini,” J. Sains Komput. Inform., vol. 5, hal. 280–294, 2021.
[15] A. Aamodt dan E. Plaza, “Case-based reasoning: Foundational issues, method ological variations, and system approaches,” Artif. Intell. Commun., vol. 7, no. 1, hal. 39–59, 1996, [Daring]. Tersedia pada: https://ibug.doc.ic.ac.uk/media/uploads/documents/courses/CBR-AamodtPlaza.pdf.
[16] S.-H. Cha, “Comprehensive survey on distance/similarity measures between probability density functions,” City, vol. 1, no. 2, hal. 1, 2007.
[17] S. S. Choi, S. H. Cha, dan C. C. Tappert, “A survey of binary similarity and distance measures,” WMSCI 2009 - 13th World Multi-Conference Syst. Cybern. Informatics, Jointly with 15th Int. Conf. Inf. Syst. Anal. Synth. ISAS 2009 - Proc., vol. 3, no. 1, hal. 80–85, 2009.
[18] Cahyana, M. A. K., & Simanjuntak, P. (2020). Aplikasi Sistem Pakar untuk Mendiagnosis Penyakit Kusta dengan Metode Forward Chaining. Computer and Science Industrial Engineering (COMASIE), 3(1), 31-37.
Downloads
Published
Versions
- 2021-11-27 (2)
- 2021-09-02 (1)
