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All Journal Jurnal Informatika dan Teknik Elektro Terapan Infotech Journal Sistemasi: Jurnal Sistem Informasi Faktor Exacta Jurnal Sains dan Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING INTECOMS: Journal of Information Technology and Computer Science Jurnal Pengabdian Hukum Indonesia (Indonesian Journal of Legal Community Engagement) JPHI Jurnal Kreativitas PKM Jurnal Teknologi Terpadu STRING (Satuan Tulisan Riset dan Inovasi Teknologi) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Pendidikan dan Konseling JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Cyber Security dan Forensik Digital (CSFD) HSG (Health Science Growth) Journal Jurnal Ilmiah Wahana Pendidikan Innovative: Journal Of Social Science Research
Carudin
Universitas Singaperbangsa Karawang
Religion Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
Klasifikasi K-NN dalam Identifikasi Penyakit COVID-19 Menggunakan Ekstraksi Fitur GLCM Nisa Nafisah; Riza Ibnu Adam; Carudin Carudin
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3258

Abstract

Covid-19 is a disease that is endemic in various parts of the world including Indonesia, this disease infects the respiratory tract caused by a new type of corona virus. To find out the presence of this virus in the body, medical examinations such as blood tests, radiological examinations can be carried out X-rays (x-rays) and swabs. Therefore, in this study, identification covid-19 disease based on the rongen image from which the image was extracted using the GLCM feature extraction method, namely contrast, correlation, energy, and homogeneity, after obtaining the value from the extraction and then classified using data mining classification method, namely k-nearest neighbor by doing 3 modeling the input value of k. The results obtained from the classification obtained an accuracy of 80% in model 3 with a value of k = 5 and in models 1 and 2 obtained an accuracy of 90% with a value of k = 1 and k = 3.
Klasifikasi Kadar Kolesterol Menggunakan Ekstraksi Ciri Moment Invariant dan Algoritma K-Nearest Neighbor (KNN) Sekar Arum Nurhusni; Riza Ibnu Adam; Carudin Carudin
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3273

Abstract

Cholesterol is a fat that is mostly formed by the body itself, especially in the liver. Cholesterol is very useful for the body but will be very dangerous if it has excessive levels. The impact of excessive cholesterol is the emergence of deadly diseases such as heart disease, stroke and poor blood circulation. In this study, one of the medical sciences that can be used to detect cholesterol levels is Iridology. This iridology itself can be applied in computer science which is often referred to as Digital Image Processing. In this case, the feature recognition method will be used using Moment Invariant feature extraction and the K-Nearest Neighbor Algorithm. Where the data used is the Dataset from Ubiris V1. With the resulting accuracy of 84,8485%.
Co-Authors Aditya Rizky Sanjaya Apriade Voutama Apriningrum, Nelly Ardhi Fadlika Satria Ariq Zeidan Mubarok Arvin Kynan Pratama Asep Jamaludin Astri Nurdiana Audy Sukma Putera Azhari Ali Ridha Budi Arif Dermawan Dadang Yusup Dadang Yusup Danisya Krisna Deni Nuryadi Eka Andriani Eno Hakimah Kusuma Dewi Fatin Nuha Yamin Hafiz Pratama S Nawawi Ilyas Shiddiq Pratama Iqbal Maulana Jaman, Jajam Haerul Jomanson Matondang Lilis Suryani Marisa Meli Indriyani Muhamad Fajar Yudhistira Herjanto Muhammad Rizki Al-Fajri Nisa Nafisah Nuryadi, Deni Ramdani Ramdani Rendy Galih Saputra Rijal Abdulhakim Riza Ibnu Adam Riza Ibnu Adam Riza Ibnu Adam Sekar Arum Nurhusni Siti Masfiah Syaza Dyah Utami Valerie Febriana Putri Indra Kusumawati