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Sistem Pendukung Keputusan Pemilihan Siswa Berprestasi Dengan Metode SAW ( Studi Kasus SDN Kedunglumbu)
Andhika Dias F
; Dandi Riski Saputra
; Fajar Bagus Saputra
; Naufaldi Rizqi Eka P
; Rahmat Nur Shidi
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Vol 2
, No 3
(2024)
This study develops a Decision Support System (DSS) for selecting outstanding students at SDN Kedunglumbu using the Simple Additive Weighting (SAW) method. The main goal of this DSS is to help the school determine outstanding students more objectively and efficiently. The SAW method was chosen for its ability to provide weighted sums of relevant criteria, ensuring accurate and fair decisions. The system development follows a waterfall approach, with structured stages from planning to implementat...
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Penerapan Algoritma C4.5 Dalam Klasifikasi Prestasi Atlet: Studi Kasus Pada Daftar Nama Penerima Penghargaan Tahun 2023
Andi Diah Kuswanto
; Hotman Nicolas Badjo
; Septian Kharist
; Muhammad Zayyid Mubarok
; Riski Saputra
; Rivaldi Muhamad Fitroh
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Vol 2
, No 3
(2024)
This study aims to apply the C4.5 algorithm in classifying athlete performance based on the 2023 award recipient list. The C4.5 algorithm was chosen for its ability to construct decision trees that can identify patterns and characteristics distinguishing high-performing athletes. The data used in this study includes various attributes such as gender, age, sport, number of medals, and level of competition participation. The results show that the C4.5 algorithm can classify athletes with high accu...
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Google Scholar
DOI
Penerapan Algoritma C4.5 dalam Klasifikasi Prestasi Atlet: Studi Kasus pada Daftar Nama Penerima Penghargaan Tahun 2023
Andi Diah Kuswanto
; Hotman Nicolas Badjo
; Septian Kharist
; Muhammad Zayyid Mubarok
; Riski Saputra
; Rivaldi Muhamad Fitroh
Modem : Jurnal Informatika dan Sains Teknologi
Vol 2
, No 3
(2024)
This study aims to apply the C4.5 algorithm in classifying athlete performance based on the 2023 award recipient list. The C4.5 algorithm was chosen for its ability to construct decision trees that can identify patterns and characteristics distinguishing high-performing athletes. The data used in this study includes various attributes such as gender, age, sport, number of medals, and level of competition participation. The results show that the C4.5 algorithm can classify athletes with high accu...
Sumber Asli
Google Scholar
DOI