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All Journal Jurnal Komputer Terapan Proceeding Applied Business and Engineering Conference
Yuli Triyani
Politeknik Caltex Riau
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Journal : Proceeding Applied Business and Engineering Conference

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KLASIFIKASI PENYAKIT DIABETIC RETINOPATHY PADA CITRA FUNDUS BERBASIS DEEP LEARNING vania annisa queentinela; Yuli Triyani
ABEC Indonesia Vol. 9 (2021): 9th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

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Abstract

Diabetic Retinopathy is one of the complications of diabetes and if it is treated too late, the patient will experience permanent blindness. Diabetic Retinopathy cannot be detected directly. This is because the hallmark of Diabetic Retinopathy is on the retina of the eye and can only be detected by an ophthalmoscope which produces an image of the fundus. However, the stage of detecting and classifying the type of Diabetic Retinopathy using an Ophthalmoscope still takes a long time to get results, so a system that can detect Diabetic Retinopathy is needed quickly to detect Diabetic Retinopathy. The Diabetic Retinopathy detection system that will be built is a Deep Learning-based system by detecting the eye fundus image which will go through several stages of process such as preparing data, image training stage and image testing stage. The data set used is from the kaggle.com and strare sites. This system will detect and classify Diabetic Retinopathy based on Deep Learning based on the characteristics of the appearance of mycroaneurysms, hard exudates, soft exudates, and bleeding in the form of dots, lines, and spots on the retina of the eye. The results obtained from the learning process obtained an accuracy of 86.7% and an error of 13.3%. So it can be concluded that the googlenet architecture can classify diabetic retinopathy well.
PERANCANGAN JARINGAN FEMTOCELL PADA JARINGAN LTE MENGGUNAKAN MODEL PROPAGASI COST 231 MULTIWALL Kevin Sean Farrel Manurung; Yuli Triyani
ABEC Indonesia Vol. 9 (2021): 9th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

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Abstract

Caltex Riau Polytechnic Building has 3 floors which are always crowded with students, lecturers and staff every day. The network connection inside the building is not as good as the network connection outside the building because the signal from the BTS is attenuated by the thick walls of the building, causing the signal strength inside the building to be weak. The solution to overcome the problems that occur is to design an indoor Femtocell network on the LTE network in the building. Caltex Riau Polytechnic which can improve signal quality and expand coverage. This design applies the COST 231 Multiwall propagation model which will be simulated using RPS Software. Before designing the femtocell network, calculations are carried out based on Coverage and Capacity to get the required number of FAPs per floor. The simulation results get the average value of RSRP on each floor of the Main Building is -48.55 dBm, -48.81 dBm, -43.18 dBm and the average value of RSRP on each floor of the Multipurpose Building is -45.16 dBm, -51.16 dBm, -42.61 dBm. And the simulation results get the average SINR value on each floor of the Main Building is 20.96 dB, 21.86 dB, 24.46 dB and the average SINR value on each floor of the Multipurpose Building is 16.74 dB, 16.74 dB, 0 dB (because only 1 FAP is placed) The results obtained from the design have met the standard parameters used by the Tri operator.
Co-Authors Andika Djojo Kusuma Kevin Sean Farrel Manurung vania annisa queentinela Wahyu Eka Putra Wahyuni Khabzli Wiwin Styorini