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All Journal Jurnal Nalar Pendidikan CommIT (Communication & Information Technology) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Scientific Journal of Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Knowledge Engineering and Data Science JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) Jurnal Mantik Progresif: Jurnal Ilmiah Komputer Infotekmesin Jurnal Informatika dan Rekayasa Elektronik JATI (Jurnal Mahasiswa Teknik Informatika) Madani : Indonesian Journal of Civil Society Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan Tadris : Jurnal Penelitian dan Pemikiran Pendidikan Islam Journal of Dinda : Data Science, Information Technology, and Data Analytics Prosiding Seminar Nasional Pengabdian Kepada Masyarakat IJCOSIN : Indonesian Journal of Community Service and Innovation Proceeding of International Conference Health, Science And Technology (ICOHETECH) eProceedings of Engineering Madani : Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika: Jurnal Pengembangan IT Jurnal MediaTIK Journal of Mechatronics and Artificial Intelligence Transaction on Informatics and Data Science
Ummi Athiyah
Institut Teknologi Telkom Purwokerto
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Journal : Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan

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Diagnosa Resiko Penyakit Jantung Menggunakan Logika Fuzzy Metode Tsukamoto Ummi Athiyah; Felia Citra Dwiyani Putri Rosyadi; Reno Agil Saputra; Hafidz Daffa Hekmatyar; Tufail Akhmad Satrio; Adam Ikbal Perdana
Jurnal Infokes Vol 11 No 1 (2021): Jurnal Ilmiah Rekam Medis dan Informatika Kesehatan
Publisher : Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The heart is one of the most vital organs in the body and its a very important role for humans. Therefore, it is very important to pay attention to the risk of heart disease from an early age. This disease can be detected early with routine examinations. Based on WHO data (2011), heart disease is the number one cause of death in the world and at least 17.5 million or the equivalent of 30% of deaths worldwide are caused by heart disease. From these problems, the researchers created an expert system using the Fuzzy Tsukamoto method to diagnose the risk of heart disease. The benefit of this research is that it can help make it easier for the general public to check the level of risk for heart disease. The input from the system is blood sugar, cholesterol, blood pressure, and body mass index (BMI), while the output is a risk rating for heart disease with 3 categories, namely small, medium, and large. The stages of the fuzzy method Tsukamoto include fuzzification, formation of IF-THEN rules, inference engine, and finally defuzzification. From the application of the fuzzy Tsukamoto produces an expert system that can diagnose heart disease with three risk categories and based on 30 test data, an accuracy value of 83 percent is generated based on a comparison of the system results with expert results.
Implementasi Algoritma Fuzzy Tsukamoto Untuk Diagnosis Penyakit Anemia (Studi Data: Rekam Medis Pasien Ibu RSIA Bunda Arif Purwokerto) Rheni Aprilia Ningrum; Agus Priyanto; Ummi Athiyah
Jurnal Infokes Vol 11 No 2 (2021): Jurnal Ilmiah Rekam Medis dan Informatika Kesehatan
Publisher : Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/infokes.v11i2.1303

Abstract

Anemia is caused by a low hemoglobin condition in the human body. Low hemoglobin conditions can cause various symptoms, including fatigue, weakness, dizziness and others. The impact on anemia can reduce concentration, physical endurance and get sick easily. So it is necessary to detect early to diagnose anemia based on the symptoms experienced with maximum accuracy. Users only need to enter the value of symptoms experienced, namely the value of hb, bleeding and weakness, the system will calculate the symptom values using the Tsukamoto fuzzy algorithm. In calculations using the Tsukamoto fuzzy algorithm using the Python programming language, there are 4 stages, namely fuzzification, rule formation, inference engine and defuzzification. At the fuzzification stage, the input symptom value becomes a fuzzy value (0-1), then at the rule formation stage there are 18 rules of 3 symptoms and 3 diagnosis results. After obtaining a rule, it is followed by an inference engine that looks for the α-predicate value in each rule using the min function. After getting the α-predicate value, defuzzification is carried out to get the crisp value or the output value. With the multiple confusion matrix method, the accuracy of the resulting data from the Tsukamoto fuzzy algorithm and prediction data is 85%. This can be used by the community to easily detect anemia early through the website.
Co-Authors Adam Ikbal Perdana Adela Putri Handayani Aditya Dwi Putro Aditya Dwi Putro Wicaksono Adytia Abi Restianto Agus Priyanto Agustyawan, Arif Ahmad Muslih Syafi'i Al Fachri, Moh. Aminullah Alam Patria Utama Alameka, Faza Alifta Salma Shafira Alika, Shintia Dwi Amalia, Hasna Shafa Andreas Rony Wijaya Arif Wirawan Muhammad Arif Wirawan Muhammad Arnelka Hananta Atika Ratna Dewi Azhari, Ahmad Dwi Setiawan, Brandon Elisabeth Angeline Wilhelmina Bakowatun Erlina Marfianti, Erlina Faisal Dharma Adhinata Faiz Rizky Fahlevi Felia Citra Dwiyani Putri Rosyadi Firda Millennianita Firda Millennianita Habiburrahman, Muhammad Quthb Hafidz Daffa Hekmatyar Hasan Nizar Hikmah Quddustiani Hulqi, Filfimo Yulfiz Ahsanul Irmayatul Hikmah Ismail , Moh Izzati Muhimmah Jannah , Uzlifatul Juvandio Aufaresa Kholidiyah Masykuroh Luthfi Rakan Nabila Made Riza Kartika Maya Nurachmawati Adiningtias Moh. Aminullah Al Fachri Muhammad Alvi Awliya Muhammad Nur Faiz Muhammad Nur Faiz Muhammad Quthb Habiburrahman Muhammad Yusril Aldean Naden, Yoga Nikmatul Khayati Novanda Alim Setya Nugraha Novantri Prasetya Putra Novian Adi Prasetyo Oktavia Jazilatus Sa’adah Pangestu, Happy Gery Puguh Ika Listyorini Rafian Ramadhani Rara Nur Salsabila Rayhan Hidayat Regina Putri Wanda Zahirah Reno Agil Saputra Rheni Aprilia Ningrum Ridha Berlianny Sulistiaputri Sa’adah, Oktavia Jazilatus Saputro, Satria Nur Sausan Sinaga, Rifaldo Yohannes Siti Khomsah, Siti Sudianto Suryani, Ajeng Ayu Taufik Maulidi Theo Felix Harianto Purba Tri Ginanjar Laksana Trihastuti Yuniati Tufail Akhmad Satrio Ulya, Fadilla Zundina Vico Meylana Eka Putra Warto Yehezekiel Ramasyah Putra Haloho Yohani Setiya Rafika Nur Yunita Wisda Tumarta Arif