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Lembaga Penelitian Pengabdian Masyarakat Universitas Nusa Mandiri
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PREDIKSI HASIL PEMILU LEGISLATIF DENGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR
Keywords:
Algoritma K-Nearest Neighbor, Data Mining, Prediksi Hasil Pemilu
Abstract
Pemilihan Umum di Indonesia telah mengalami beberapa perubahan dari periode Pemilu ke periode Pemilu yang lain. Selama pemilu Orde Baru, kita mengenal sistem pemilu proporsional dengan daftar tertutup. Keterpilihan calon legislatif bukan ditentukan pemilih, melainkan menjadi kewenangan elite partai politik sesuai dengan susunan daftar caleg beserta nomor urut. Dalam sistem demikian, kedudukan parpol menjadi sangat kuat terhadap kadernya di parlemen. Namun di satu sisi, basis sosial dan relasi politik para wakil rakyat dengan konstituen menjadi lemah. Inilah yang menyebabkan kedudukan caleg terpilih mereka menjadi ”jauh” dalam hubungannya dengan konstituen. Semangat memilih langsung wakil rakyat baru mulai diakomodasi pada Pemilu 2004 melalui UU No. 12 Tahun 2003, dengan menggunakan sistem proporsional dengan daftar calon terbuka. Pemilih tidak hanya memilih tanda gambar parpol, tetapi juga diberi kesempatan memilih caleg.Penelitian yang berhubungan dengan pemilu sudah pernah dilakukan oleh peneliti yaitu dengan menggunakan metode decision tree dan classification tree dan estimator bayesian. Pada penelitian ini peneliti akan menggunakan metode K-Nearest Neighbor. algoritma K-Nearest Neighbor telah menunjukkan hasil yang menjanjikan dalam prediksi untuk data time-series dibandingkan dengan pendekatan tradisional sehingga hasil prediksi pemilu legislatif DKI Jakarta lebih akurat.
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Santoso, T. (2004). Pelanggaran pemilu 2004 dan penanganannya. Jurnal demokrasi dan Ham , 9-29.
Sardini, N. H. , 2011, Restorasi penyelenggaraan pemilu di Indonesia. Yogyakarta: Fajar Media Press.
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Vercellis, C. , 2009, Business Intelligence : Data Mining and Optimization for Decision Making. John Wiley & Sons, Ltd.
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Published
2015-09-15
How to Cite
Badrul, M. (2015). PREDIKSI HASIL PEMILU LEGISLATIF DENGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR. Jurnal Pilar Nusa Mandiri, 11(2), 152-160. Retrieved from https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/424
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