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All Journal Journal of Information Systems and Informatics Journal of Information Technology Ampera
Suriani, Uci
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Computer Science & IT

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Comparing the Prediction of Numeric Patterns on Form C1 Using the K-Nearest Neighbors (K-NN) Method and a Combination of K-Nearest Neighbors (K-NN) with Connected Component Labeling (CCL) Suriani, Uci; Kurniawan, Tri Basuki
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.592

Abstract

Indonesia's elections serve as a cornerstone of its democratic system, with the active participation of its citizens being of paramount importance. To bolster transparency and civic engagement during these elections, the SITUNG system (Election Result Information System) is employed for the tabulation of election results. However, the current tabulation process remains manual, potentially leading to data entry errors and a reduced accuracy of election outcomes. This research endeavor seeks to enhance the efficiency and accuracy of election result tabulation by employing the K-Nearest Neighbors (K-NN) method for recognizing numeric patterns on Form C1, both independently and in combination with Connected Component Labeling (CCL). The K-NN method demonstrates a commendable 60.0% accuracy in recognizing numeric patterns from the original Form C1 data. However, when combined with CCL, the accuracy drops to 51.2%. This research makes a significant contribution by simplifying the tabulation process and improving the accuracy of election results in Indonesia through the application of the K-NN method. The technology is anticipated to fortify democracy by promoting a more transparent and participatory electoral process for the citizens.
Pemodelan Prediktif Keterlambatan Bicara pada Balita Terkait dengan Penggunaan Smartphone Menggunakan Data Mining Suriani, Uci; Ninditama, Ilsa Palingga; Syaputra, Wahyudi
Journal of Information Technology Ampera Vol. 5 No. 1 (2024): Journal of Information Technology Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalita.v5i1.590

Abstract

Penelitian ini bertujuan untuk memprediksi tingkat keterlambatan bicara pada balita yang sudah terindekasi smartphone dengan menggunakan metode klasifikasi dan algoritma Decision Tree C4.5. Atribut yang digunakan dalam penelitian ini mencakup umur (usia), durasi, dan jenis aplikasi yang digunakan. Pengelolaan data untuk prediksi tingkat keterlambatan bicara pada balita menggunakan tahapan Knowledge Discovery in Database (KDD) dengan alat bantu tools RapidMiner. Proses penghitungan data dengan algoritma Decicion Tree menunjukkan bahwa tingkat keterlambatan bicara (Speech Delayed) yang terlambat lebih rendah dibandingkan dengan tingkat balita yang tidak mengalami keterlambatan bicara (Normal). Hasil akurasi prediksi sebesar 89.59%. Evaluasi dengan metrik AUC juga menunjukkan nilai 89.59%, mengindikasikan bahwa model ini memiliki kemampuan klasifikasi yang hampir sempurna. Temuan ini memverifikasi bahwa model mampu memprediksi tingkat keterlambatan Bicara pada balita dengan tingkat akurasi yang tinggi.
Co-Authors Kurniawan, Tri Basuki Ninditama, Ilsa Palingga Syaputra, Wahyudi