Pengembangan dan Evaluasi Web Dashboard Sistem Prediksi User Throughput-Downlink Berbasis Machine Learning Untuk Jaringan 4G LTE
Abstract
Seiring dengan perkembangan teknologi dan harga perangkat yang relatif terjangkau, pelanggan jaringan seluler cenderung menggunakan smartphone yang mendukung konektivitas berbagai generasi teknologi seluler, mulai dari 2G, 3G, 4G, hingga 5G. Masing-masing generasi memiliki kebutuhan dan kualitas layanan tertentu. Berdasarkan pertimbangan jumlah pelanggan jaringan seluler jaringan 4G yang masih dominan sampai saat ini, sistem dirancang untuk mengolah berbagai parameter jaringan 4G untuk memprediksi throughput yang berasal baik dari dataset yang sudah tersedia maupun hasil dari pengukuran. Sistem dapat menghitung korelasi antara throughput dengan parameter lain yang akan dijadikan nilai masukan sistem. Throughput yang dimaksud pada penelitian ini adalah downlink throughput, yaitu volume trafik pada periode tertentu yang berasal dari internet menuju perangkat pengguna (smartphone). Penelitian ini fokus pada pengembangan dan evaluasi web dashboard Sistem Prediksi User Throughput-Downlink berbasis Machine Learning untuk Jaringan 4G LTE dengan evaluasi berupa uji fungsional dan uji terima berbasis technology acceptance model (TAM). Uji fungsional mencakup pengujian pada halaman utama, fungsionalitas fitur data loading, fungsionalitas feature selection, dan fungsionalitas fitur modelling and evaluation data. Uji terima dilakukan atas tiga konstruk, yaitu persepsi tampilan web dashboard keseluruhan, usefulness, dan ease of use. Uji terima dilakukan kepada 76 responden dengan nilai modus dan nilai rata-rata ≥ 4 dari skala 5.
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