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All Journal Jurnal Vokasi Journal Serambi Engineering (JSE)
Amir D
Politeknik Negeri Lhokseumawe
Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences

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Journal : Journal Serambi Engineering (JSE)

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Analisa Perhitungan Pathloss Propagasi Gelombang Radio Outdoor Menggunakan Model Hata dan Model Cost 231 Pada Jaringan 3G Telkomsel Lhokseumawe Amir D; Naziruddin; Jamaluddin; Ariefin; Halim Saini
Jurnal Serambi Engineering Vol. 9 No. 2 (2024): April 2024
Publisher : Faculty of Engineering, Universitas Serambi Mekkah

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Abstract

The problem that arises in wireless communications is how to predict the transmission channel attenuation between Tx transmitters and Rx receivers that have different channel characteristics. This research explains the results of comparing the Hata empirical model with the Cost 231 model. The empirical model is a prediction model for radio wave attenuation used by engineers in the field without the use of experimental equipment. The aim of this research is to determine the accuracy of the calculation results in the two models. Three locations were used as research samples, namely Darussalam Road, Samudera Baru Road and Gudang Baru Road. The third locations have different distances and BTS. The standard deviation shows the amount of deviation from the average distribution of the predicted data group. Based on the prediction results at the three locations, the Cost 231 model produces larger predicted pathloss calculations compared to the Hata model, the average value of the pathloss prediction of the Cost 231 model is 260.47 dB and the Hata model is 196.46 dB, the difference between the two calculation results is 64.01. The empirical Cost 231 model gives a standard deviation of the mean distribution of 13.59, while the Hata model gives a standard deviation of 0.56 of the mean distribution of the calculated values.
Perbandingan Akurasi Algoritma Principal Component Analysis Dengan Algoritma Convolutional Neural Network Dalam Pengenalan Wajah indrawati; ismi amelia; Guntur Syahputra3; alfa nerfsiha; Amir D
Jurnal Serambi Engineering Vol. 9 No. 2 (2024): April 2024
Publisher : Faculty of Engineering, Universitas Serambi Mekkah

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Abstract

Facial recognition technology is used in various fields such as criminal identification, security purposes, finding missing people, diagnosing diseases, forensic investigations, identifying people on social media platforms, opening mobile phones, access control of meeting rooms, bank vaults. This paper presents a performance comparison between PCA and CNN algorithms. The aim of this research is to test the classification and compare the accuracy of PCA and CNN algorithms in face recognition. The method is to test the classification of Euclidean distance weights and compare performance tests which include; precision, recall and accuracy. The results showed that the accuracy of the PCA algorithm predicted TP by 100%, while the CNN algorithm predicted TP by 82%, while FN predicted 0. The recall performance on the PCA algorithm predicted TP by 100%, while on the CNN algorithm the recall performance predicted TP by 82%. Accuracy in the PCA algorithm is known that the TP prediction result is 100%, where TN, FN and FP are 0, while the accuracy performance in the CNN algorithm, TP is 82%, FN is 18%, TN and FP are 0.
Co-Authors alfa nerfsiha Ariefin Ariefin Ariefin Gunawan Gunawan Guntur Syahputra3 Halim Saini Indrawati ismi amelia Jamaluddin Naziruddin Naziruddin Naziruddin Rahmawati Rahmawati