Analyzing the Level of Anxiety Disorders of Final-Year Students by Applying the Fuzzy Mamdani Method

Authors

  • Virdyra Tasril Universitas Pembangunan Panca Budi
  • Muhammad Iqbal Universitas Pembangunan Panca Budi
  • Febby Madonna Yuma STMIK Royal Kisaran
(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v5i3.226

Keywords:

Application, Classification, k-NN, Stunting

Abstract

Stunting in toddlers is defined as a condition of failure to thrive due to chronic malnutrition in the long term. The problem of stunting in Indonesia is an issue that is still a concern for the Indonesian government. The prevalence of stunting in Indonesia is still relatively high, coupled with the COVID-19 pandemic, which has impacted the economic sector. For this reason, research on stunting is still a critical topic. This study aims to classify toddler stunting using the k-Nearest Neighbor classification algorithm and build a website-based early detection application for toddler stunting cases. The research results using the k-Nearest Neighbor Algorithm trial obtained a relatively high accuracy of 92.45%. Implementing an early detection system for stunting cases has proven to help health workers classify toddlers as stunted or not. This application is also helpful as an archive and facilitates data reporting. The application has eight main menus: the Puskesmas data menu, Posyandu data, toddler data, weighing, weighing results, development menu, and stunting early warning menu, which contains malnourished and stunted toddlers.

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References

Asrori, A. (2015). Terapi Kognitif Perilaku Untuk Mengatasi Gangguan Kecemasan Sosial. Jurnal Ilmiah Psikologi Terapan (JIPT), 3(1), 89–107. Retrieved from http://ejournal.umm.ac.id/index.php/jipt/article/view/2128

Diferiansyah, O., Septa, T., & Lisiswanti, R. (2016). Gangguan Cemas Menyeluruh. Jurnal Medula Unila, 5(2), 63–68. Retrieved from https://juke.kedokteran.unila.ac.id/index.php/medula/article/view/1510

Hendrawan, H., Haris, A., Rasywir, E., & Pratama, Y. (2020). Diagnosis Penyakit Tanaman Karet dengan Metode Fuzzy Mamdani. Paradigma - Jurnal Komputer Dan Informatika, 22(2), 132–138. https://doi.org/10.31294/p.v22i2.8909

Ikhwan, A. (2019). Penerapan Fuzzy Mamdani Untuk Sistem Pendukung Keputusan Pemilihan Laptop. Jurnal Fasilkom, 9(2), 476–483. https://doi.org/10.37859/jf.v9i2.1407

Ismunu, R. S., Purnomo, A. S., & Subardjo, R. Y. S. (2020). Sistem Pakar Untuk Mengetahui Tingkat Kecemasan Mahasiswa Dalam Menyusun Skripsi Menggunakan Metode Multi Factor Evaluation Process Dan Inferensi Fuzzy Tsukamoto. Proceeding SENDIU, 65–72. Semarang: Universitas Stikubank. Retrieved from https://www.unisbank.ac.id/ojs/index.php/sendi_u/article/view/7962/2925

Marbun, M., & Harefa, N. (2020). Implementasi Logika Fuzzy Mamdani Untuk Mengidentifikasi Tingkat Kecanduan Pelajar Terhadap Game Online. JOISIE Journal Of Information System And Informatics Engineering, 4(2), 128–138. Retrieved from https://www.ejournal.pelitaindonesia.ac.id/ojs32/index.php/JOISIE/article/view/848

Matondang, F., Kusumawati, R., & Abidin, Z. (2012). Fuzzy Logic Metode Mamdani Untuk Membantu Diagnosa Dini Autism Spectrum Disorder. MATICS, 4(3), 110–116. https://doi.org/10.18860/mat.v0i0.1571

Muflihunna, K. M. (2022). Penerapan Metode Fuzzy Mamdani dan Metode Fuzzy Sugeno dalam Penentuan. 11(1), 27–37.

Muzarafah, & Marlina. (2022). Penerapan Metode Fuzzy Mamdani Dalam Diagnosa Virus Penyebab Penyakit Pada Kucing. Jurnal Sintaks Logika (JSilog), 2(3), 23–30. Retrieved from https://jurnal.umpar.ac.id/index.php/sylog

Pravina, P., Sugihartono, P., & Hidayat, N. (2020). Implementasi Metode Fuzzy Tsukamoto Untuk Deteksi Dini Tingkat Depresi Mahasiswa Yang Sedang Menempuh Skripsi (Studi Kasus: Fakultas Ilmu Komputer Universitas Brawijaya). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 4(10), 3432–3438. Retrieved from https://jptiik.multi.web.id/index.php/j-ptiik/article/view/7985

Rustam, M. Z. A., & Nurlela, L. (2021). Gangguan Kecemasan dengan Menggunakan Self Reporting Questionaire (SRQ-29) di Kota Surabaya. Jurnal Kesehatan Masyarakat Mulawarman, 3(1), 39–47. https://doi.org/10.30872/jkmm.v3i1.5752

Saleh, U. (2019). Anxiety Disorder (Memahami gangguan kecemasan: jenis-jenis, gejala, perspektif teoritis dan Penanganan). Universitas Hasanuddin.

Santya, L., Miftah, M., Saepudin, S., Mandala, V., & Gustian, D. (2017). Penerapan Metode Fuzzy Mamdani Untuk Pendukung Keputusan Penentuan Jumlah Produksi Lantak Si Jimat. Jurnal Rekayasa Teknologi Nusaputra, 2(2), 27–38. Retrieved from https://jurnal.nusaputra.ac.id/rekayasa/paper/44

Siahaan, J. K. (2020). Analisa Tingkat Trauma Kecelakaan dengan Menerapkan Metode Fuzzy Mamdani. Journal of Pharmaceutical and Health Research, 1(1), 21–26. Retrieved from http://ejurnal.seminar-id.com/index.php/jharma/article/view/94

Tasril, V., & Sari, R. M. (2022). Pemodelan Sistem Fuzzy Diagnosa Anxiety Disorder Terhadap Mahasiswa Selama Masa Pandemi Covid-19 (45th ed.). Klaten: Tahta Media Group.

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Published

2023-06-23

How to Cite

Tasril, V., Iqbal, M., & Yuma, F. M. (2023). Analyzing the Level of Anxiety Disorders of Final-Year Students by Applying the Fuzzy Mamdani Method. Jurnal Riset Informatika, 5(3), 339–344. https://doi.org/10.34288/jri.v5i3.226

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