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All Journal Insand Comtech : Information Science and Computer Technology Journal SmartComp
Adi Nur Rohkhim
Universitas Narotama Surabaya
Computer Science & IT Electrical & Electronics Engineering

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ALGORITHM K-NN IN CLASSIFICING POTENTIAL AREAS OF MEN SINGLES BADMINTON PLAYERS IN INDONESIA Adi nur Rohkhim
Insand Comtech : Information Science and Computer Technology Journal Vol 5, No 2 (2020): Insand Comtech
Publisher : Universitas Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.429 KB) | DOI: 10.53712/jic.v5i2.734

Abstract

Badminton is one sport that is contested at the Summer Olympics. Noted Indonesian badminton player has won 7 gold medals in the event. Until now Indonesia has not been able to add any gold medal from other sports that were competed in the Olympics. No wonder badminton has become a very important sport in Indonesia. Even though badminton is not from Indonesia, but Indonesia has given birth to many badminton legends since the 1960s until now. In the digital age sport science has now been developed in various countries to support athlete and official performance, but if this is not supported by the regeneration of young players, the achievement relay will be interrupted. How important it is to prepare young players with the potential to carry on the tradition of achievement in the badminton branch. Indonesia is one of the countries with a relatively slow regeneration of young players compared to other competing countries such as China, South Korea and Japan. The implementation of the K-Nearst Neighbor algorithm to classify areas with the potential of male singles badminton athletes in Indonesia is one solution so that the parent of Indonesian badminton organizations get a potential single male player. By using 1000 national male singles ranking data in Indonesia and classifying them into 3 regions, Potential areas, enough potential, and no potential.
Klasifikasi penyakit kalkulus ( karang gigi ) menggunakan pengolahan citra digital dengan metode jaringan saraf tiruan backpropagation Adi Nur Rohkhim; Cahyo Darujati
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 9, No 2 (2020): Smart Comp :Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v9i2.1944

Abstract

Jenis penyakit gigi dan mulut cukup banyak jumlahnya. Mulai dari yang jenisnya ringan hingga yang berat. Salah satu contoh  jenis penyakit gigi yang ringan adalah karang gigi. Mungkin kebanyakan orang sering mengabaikan penyakit yang satu ini. Karena alasan tidak menganggu kinerja gigi. Padahal ada beberapa dampak yang di timbulkan ketika karang gigi dibiarkan menumpuk, seperti : bau mulut, peradangan pada gusi, sampai penyumbatan pembuluh darah. Menurut inisiasi dan tingkat akumulasi bentuk karang gigi . Karang gigi di klasifikasikan menjadi 3 bagian yaitu sligt, moderate, dan heavy. Penelitian ini bertujuan untuk mempermudah tenaga medis gigi dalam mengklasifikasi penyakit kalkulus menggunakan bidang keilmuan pengolahan citra digital dan jaringan saraf tiruan backpropagation. Masukan Jaringan saraf tiruan berupa luas area karang gigi, ciri hue, ciri saturation, dan ciri  value. Menggunakan 2 hidden layer dengan masing masing masukan neuron berjumlah 100 neuron. Di peroleh hasil tingkat akurasi sebesar 100 % untuk data latih, dan 90 % untuk data uji . Penelitian ini menggunakan 50 data citra kalkulus, dengan perbadingan data latih dan data uji sebesar 60:40.
Co-Authors Cahyo Darujati