Abstract
The general election in Indonesia itself still experiences technical and non-technical problems where the technical problems occur in the recapitulation of votes from sheet C1 which are still incorrectly inputted and done manually. The problem occurred with the difference in the uploaded C1 data and the data in the KPU Situng and the C1 sheet uploaded was blurry, unclear, sheet C1 which was crossed out or folded in the KPU Situng. The purpose of this research is to reduce errors in data input and change the work that is done manually to the system, create a number pattern recognition system using an Artificial Immune System optimization approach, test and analyze the work of the system by taking into account the level of accuracy, preciseness and speed in recognize number patterns. The system created to applies an artificial immune system optimization approach with the Artificial Immune System using the Randomized Real-Valued Negative Selection Algorithm algorithm.
Highlights
non-technical problems where the technical problems occur in the recapitulation of votes
The problem occurred with the difference in the uploaded C1 data
The results of this study obtained the accuracy of the testing process 85.85715728861501 with a testing error
Summary
Kecerdasan buatan (Artificial Intelligence) telah dipelajari bertahun-tahun oleh para filsuf. Pada machine learning terdapat berbagai algoritma, salah satunya adalah Sistem Kekebalan Buatan (Artificial Immune System). Sedangkan Pengenalan pola (pattern recognition) adalah sebuah proses untuk mengambil dan mengklasifikasi data, dimana data tersebut dapat berupa gambar, tulisan, suara, angka dan lain-lain. Pengenalan pola merupakan salah satu bidang dalam pembelajaran mesin (machine learning) yang menitikberatkan pada metode klasifikasi objek ke dalam kelas-kelas tertentu untuk menyelesaikan masalah tertentu. Pada penelitian “Pengenalan Pola Tulisan Tangan Pada Formulir Perolehan Suara Pemilihan Presiden Dan Wakil Presiden Menggunakan Algoritma Principal Component Analysis”, Hasil yang didapatkan dari penelitian ini semakin banyak dan bervariasi citra data training maka semakin baik tingkat akurasi dari identifikasi yang dilakukan. Metode yang digunakan Randomized Real-Valued Negative Selection Algorithm yang menggunakan pendekatan optimisasi Sistem Kekebalan Buatan (Artificial Immune System)
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