DOI: https://doi.org/10.14710/jtsiskom.6.3.2018.110-114

Deteksi Tingkat Risiko Kehamilan dengan Metode Fuzzy Mamdani dan Simple Additive Weighting

Detection of Pregnancy Risk Level with Fuzzy Mamdani and Simple Additive Weighting Methods

Department of Informatics, Universitas Dian Nuswantoro, Indonesia

Received: 26 Mar 2018; Published: 31 Jul 2018.
Open Access Copyright (c) 2018 Jurnal Teknologi dan Sistem Komputer
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
The risk of pregnancy is a contributing factor in increasing mother maternal mortality (MMR). This study aimed to produce a pregnancy risk detection system based on patient examination results. This research combines fuzzy Mamdani and Simple Additive Weighting (SAW) methods using 11 criteria to determine the risk of pregnant women, that is low, high, and very high. The criteria that determine the risk of pregnancy are expressed as fuzzy statements. In system testing to 100 pregnant women patients, obtained an accuracy of 88% using recognition rate method.

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Inferensi Aturan Nilai Risiko Berdasarkan Kriteria Ibu Hamil
Subject Detection of Pregnancy Risk Level with Fuzzy Mamdani and Simple Additive Weighting Methods
Type Research Materials
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Keywords: pregnancy risk early detection; high risk pregnancy factor; Fuzzy Mamdani system; simple additive weighting; recognition rate accuracy
Funding: Department of Informatics, Universitas Dian Nuswantoro

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Language : ID
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  1. G. D. Widarta, M. Ardian, C. Laksana, A. Sulistyono, and W. Purnomo, "Deteksi Dini Risiko Ibu Hamil dengan Kartu Skor Poedji Rochjati dan Pencegahan Faktor Empat Terlambat," Majalah Obstetri & Ginekologi, vol. 23, no. 1, pp. 28–32, 2015
  2. V. P. Subiyanto, Cara Sehat & Aman Menghadapi Kehamilan di Atas Usia 35 Tahun, 1st ed. Klaten: Cable Book, 2012
  3. W. Aryawati, "Pengembangan Model Pencegahan Resiko Tinggi Kehamilan Dan Persalinan Yang Terencana Dan Antisipatif (REGITA)," Jurnal Kebijakan Kesehatan Indonesia, vol. 5, no. 2, pp. 86–93, 2016
  4. R. Ristrini and O. Oktarina, "Upaya Peningkatan Deteksi Dini Risiko Tinggi Kehamilan Melalui Kelengkapan Pengisian Buku KIA oleh Bidan di Kabupaten Bangkalan Jawa Timur 2013," Buletin Penelitian Sistem Kesehatan, vol. 17, no. 3, pp. 215–225, Juli 2014
  5. W. Syahidah, I. F. Astuti, and A. H. Kridalaksana, "Sistem Pakar Skrining Kehamilan Resiko Tinggi Menggunakan Metode Certainty Factor (Studi Kasus: Puskesmas Handil Bakti Palaran)," Skripsi, Universitas Mulawarman, 2015
  6. Y. Permatasari, U. Salamah, and R. Saptono, "Klasifikasi Risiko Bahaya Kehamilan dengan Metode Fuzzy C-Means," ITSMART: Jurnal Teknologi dan Informasi, vol. 2, no. 1, pp. 8–15, 2013
  7. R. L. Gema, D. Kartika, and M. Pratiwi, "Artificial Intelligence Menentukan Kualitas Kehamilan pada Wanita Pekerja," Majalah Ilmiah, vol. 24, no. 2, pp. 318–324, 2017
  8. A. M. Nugraheni, "Sistem Pakar Deteksi Dini Tingkat Risiko pada Ibu Hamil terhadap Preeklampsia dengan Logika Fuzzy," Skripsi, Universitas Airlangga, 2016
  9. M. Kastina and M. Silalahi, "Logika Fuzzy Metode Mamdani Dalam Sistem Keputusan Fuzzy Produksi Menggunakan Matlab," Jurnal Ilmu Komputer, vol. 1, no. 2, pp. 171–181, 2016
  10. E. Y. Anggraeni and W. Agustina, "Sistem Pendukung Keputusan Dalam Diagnosa Penyakit Anemia Dengan Menggunakan Metode Saw (Simple Additive Weighting)," Semnasteknomedia Online, vol. 4, no. 1, pp. 6–7, 2016
  11. S. Yudha Prayogi, "Penerapan Metode Simple Additive Weighting dalam Pemilihan Tablet PC Untuk Pemula," CESS (Journal of Computer Engineering, System and Science), vol. 1, no. 1, pp. 35–40, 2016
  12. C. Surya, "Sistem Pendukung Keputusan Rekomendasi Penerima Beasiswa Menggunakan Fuzzy Multi Attribute Decision Making (FMADM) dan Simple Additive Weighting (SAW)," Jurnal Rekayasa Elektrika., vol. 11, no. 4, pp. 149-156, 2015
  13. E. Panggabean, "Sistem Pendukung Keputusan Penentuan Lokasi Perumahan Ideal Menggunakan Metode Fuzzy Simple Additive Weighting," Jurnal Times, vol. 4, no. 1, pp. 12–17, 2015
  14. M. K. T. Sutojo, Kecerdasan Buatan. Semarang: Penerbit Andi, 2010

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