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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JURNAL MEDIA INFORMATIKA BUDIDARMA J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Building of Informatics, Technology and Science Jurnal Teknologi Dan Sistem Informasi Bisnis JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH J-SAKTI (Jurnal Sains Komputer dan Informatika) EXPLORER CHIPSET (Journal on Computer Hardware, Signal Processing, Embedded System and Networking) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Innovative: Journal Of Social Science Research Jurnal Pengabdian Masyarakat Bangsa Jurnal Pengabdian Sosial Jurnal Pengabdian Kepada Masyarakat Radisi Jurnal KALANDRA Journal of Computer Science Artificial Intelligence and Communications Etanic : Journal Of English Language Teaching And Applied Linguistics Jurnal Ilmu Komputer dan Teknik Informatika Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Muhammad Noor Hasan Siregar
Universitas Graha Nusantara, Padangsidimpuan, Sumatera Utara - Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Journal : EXPLORER

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Perancangan Aplikasi Data Mining Untuk Menentukan Pasien Menderita Tifoid Dengan Metode Algoritma C4.5 Yusra Fadhillah; Muhammad Noor Hasan Siregar; Oberlin Siagian
Explorer Vol 1 No 2 (2021): Juli 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.857 KB) | DOI: 10.47065/explorer.v1i2.92

Abstract

Data mining adalah suatu istilah yang digunakan untuk menguraikan penemuan pengetahuan didalam database. Proses data minig ini akan diimplementasikan dengan menggunakan algoritma C.45. Algoritma C.45 dapat digunakan dalam pembentukan pohon keputusan tetapi lebih mengarah pada perhitungan probabilitas dari tiap-tiap record terhadap kategori-kategori tersebut atau untuk mengklarifikasi record dengan mengelompokan ke dalam satu kelas. Setelah sebuah pohon keputusan dibangun maka dapat digunakan untuk mengklarifikasi record yang beulm ada kelasnya. Dimulai dari node root menggunakan tes terhadap atribut dari record yang belum ada kelasnya, kemudian mengikuti cabang sesuai dengan proses pohon keputusan yanitu mengubah bentuk data (table) menjadi pohon (tree) kemudian merubah model pohon tersebut menjadi aturan. Berdasarkan penelitian yang telah dilakukan yang telah dibangun dapat menentukan pasien yang menderita penyakit tipes.
Optimasi Fungsi Aktivasi pada Artificial Neural Network untuk Prediksi Gagal Jantung Secara Akurat Raharjo, Mokhamad Ramdhani; Indra Riyana Rahadjeng; Siregar, Muhammad Noor Hasan; Alkhairi, Putrama
Explorer Vol 5 No 1 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v5i1.1840

Abstract

Heart failure is one of the major health problems that can be fatal if not diagnosed properly and quickly. Therefore, early prediction using artificial intelligence models, especially Artificial Neural Network (ANN), is needed to improve the accuracy in detecting heart failure. This study aims to optimize the activation function in ANN to predict heart failure accurately. Several optimization algorithms tested, namely Adam, RMSprop, SGD, Adagrad, and Adadelta, were used to evaluate model performance in terms of accuracy, precision, recall, and F1-score. The results showed that the Adam optimization algorithm provided the best performance with an accuracy of 86.74%, precision of 75.12%, recall of 66.67%, and F1-score of 70.64%. Meanwhile, other algorithms such as RMSprop, SGD, Adagrad, and Adadelta showed lower performance, with some metrics reaching 0%. This study shows that proper activation function optimization in ANN is very important to improve the model's ability to predict heart failure with a high level of accuracy.
Co-Authors , Eka Putra AA Sudharmawan, AA Ade Ismail Abdul Kodir Agus Perdana Windarto Alfiarini Alkhairi, Putrama Anata, Hery Dia Aswan, Novita Badawi, Masrof Batubara, Heri Dia Anata Chairul rizal Chairul Rizal Deni Apriadi Edi Suharto Eka Putra Fachri, Barany Fadhillah , Yusra Fadhillah, Yusra Ferawati Artauli Hasibuan Ferawati Artauli Hasibuan Furqan Khalidy Handoko, Divi Harahap, Angelia Utari Harputra, Yuswin Hasibuan, Ferawati Artauli Hendry Hendry . HERY DIA ANATA BATUBARA Indra Prasetia, Indra Indra Riyana Rahadjeng Indra Riyana Rahadjeng Khairunnisa Lubis, Fitri Romaito Mardiah Muhammad Eka Muhammad Hasanuddin, Muhammad Muhammad Iqbal Muhammad Iqbal Muhammad Yasin Simargolang Muhammad Zen Munadi Munadi Nuranisah Nurkhasanah Rina Puspita Oberlin Siagian Putra, Randi Rian Raharjo, Mokhamad Ramdhani Rahman, M. Arif Ramadhani, Cerah Fitri Ramadhani, Yulia Rizki Rismayanti Rismayanti Rismayanti Rizal, Chairul Rizki, Cindy Atika Rusmin Saragih, Rusmin Setiawan, Yudika Dwi Siti Hajar Siti Khodijah Suleman, Abdul Rahman Supiyandi Supiyandi Toga Mahaji Yasir, Amru Yuhandri, Muhammad Habib Yusra Fadhillah Yusra Fadhillah