PEMODELAN DAN EVALUASI PREDIKSI RSRP MENGGUNAKAN ARTIFICIAL NEURAL NETWORK UNTUK OPTIMASI KUALITAS LAYANAN JARINGAN KOMUNIKASI NIRKABEL

Mhd Ikhsan Rifki, M. Khalil Gibran, Abdul Halim Hasugian, Muhammad Dani Solihin

Abstract


Penelitian ini bertujuan untuk memprediksi nilai Reference Signal Received Power (RSRP) pada jaringan LTE menggunakan metode regresi berbasis Multilayer Perceptron (MLP). Model dirancang dengan enam variabel input, dua hidden layer, dan satu output untuk menghasilkan estimasi RSRP berdasarkan data pengukuran yang mencakup parameter RSRQ, SNR, RSSI, RSRP terukur dengan identitas longitude dan latidude. Data yang digunakan telah melalui proses pembersihan dan validasi. Evaluasi performa model dilakukan menggunakan metrik Mean Squared Error (MSE) dan Mean Absolute Error (MAE). Hasil pengujian menunjukkan bahwa model mencapai nilai MSE sebesar 6,64 dBm dan MAE sebesar 4.1922 dBm, dengan kesalahan relatif masing-masing 0.73% dan 5.13%. Distribusi kesalahan prediksi dianalisis menggunakan histogram yang berada pada interval 5dBm, yang menunjukkan bahwa dominasi nilai prediksi berada dekat dengan nilai aktual. Hasil ini menunjukkan bahwa model MLP mampu memberikan estimasi RSRP yang cukup akurat dan dapat digunakan untuk mendukung perencanaan serta optimasi kualitas jaringan komunikasi.

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DOI: http://dx.doi.org/10.36723/juri.v17i1.751

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