Community Culture Improvisation Regarding Waste Management Systems and Per Capita Income Increase

Prasetya, Dwi Arman; Sanusi, Anwar; Chandrarin, Grahi; Roikhah, Elfiatur; Mujahidin, Irfan; Arifuddin, Rahman

doi:10.35741/issn.0258-2724.54.6.8

Cited by 8 publications

(8 citation statements)

References 24 publications

(5 reference statements)

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“…Hasil dari draf tersebut kemudian disimulasi menggunakan software desain untuk menentukan parameter antena mikrostrip margin persegi ganda. Desain coupler hibrida 90 derajat dan simulasi antena penting untuk menentukan pembatasan desain seberapa nyaman atau tidak seperti yang diinginkan dari kemampuan tersebut [19] [20]. Pada gambar 2 Desain jaringan feeding elektromagnetik dari miniatur yang diusulkan, yaitu jaringan feeding 5.5GHz untuk sensor nirkabel SIL.…”

Section: Metodologiunclassified

Antenna 5.8 GHz dengan Output Perbedaan Fasa 90 Derajat Ganda Menggunakan Jaringan Matriks Butler Feeding

Mujahidin

Prasetya

Arifuddin

et al. 2021

protk

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A complex design of electromagnetic feeding network circuit components is needed for a wireless communication network system, and expensive materials, especially for electromagnetic components at a high frequency of 5.8 GHz with dual 90-degree phase difference output using butler matrix Feeding Network for wireless communication network systems. It is novel in form and has a frequency-free, frequency-free, non-complex configuration of microstrip electromagnetic circuits, and uses inexpensive materials at a frequency of 5.8 GHz. This system is a package consisting of a 5.8 GHz microstrip antenna with a rectangular microstrip antenna array and a Butler matrix of four inputs and outputs to achieve a double 90-degree phase difference. The antenna uses a via hole for the transmission line to the network feeding system, has one band and shallow bandwidth with four ports, and has one working frequency, namely 5.58 GHz under the S criterion -10dB, and uses a via hole for the transmission line to the network feeding system, the radiation pattern is forward, the gain level is 6.83dB, and the feeding impedance is 50 Ohm. S11 -26.19 dB for the 90-degree hybrid coupler, S21 31.65 dB, S51 -26.18 dB, and S61 32.52 dB which means these are all working well, and the overall size of this structure is 80mm x 65mm with FR4 of 4.4 dielectric constant having 50 ohms.

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Section: Metodologiunclassified

Antenna 5.8 GHz dengan Output Perbedaan Fasa 90 Derajat Ganda Menggunakan Jaringan Matriks Butler Feeding

Mujahidin

Prasetya

Arifuddin

et al. 2021

protk

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“…In Fig. 2, The input layer has only one node as the frequency, 16 nodes inside the hidden layer to add a non-linearity to model and 6 nodes in the output layer as the representation of the ground plane height, triangle side length, circle diameters, return loss, gain and directivity of the antenna [14] [15]. The algorithm was experimented using a different-numbers of hidden layers and neurons [16] [17].…”

Section: Network Achitecturementioning

confidence: 99%

Performance Tuning of Spade Card Antenna using Mean Average Loss of Backpropagation Neural Network

Mujahidin¹,

Prasetya²,

Nachrowie³

et al. 2020

IJACSA

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The microstrip antennas have different dimensions to get the desired performance, especially for microstrip antennas that have complex components and dimensions with the performance: the range of frequency at 2.4 GHz until 3.6 GHz, Maximum Power of Gain value is 5.83 dB and the minimum value is 3 dB and Maximum Directivity Value is 6.22 and the minimum value is 3.32. in consequence, needs to fill the demand for a new and the corresponding design as solvent to adaptive matching as tuner the frequency on antenna design that needs requires a complex mathematical method and simulation. This paper has the novel design to tune the performance of spade card microstrip antenna that can operate on the single, dual or multiband and able to produce circular or linear polarization using Backpropagation Neural Network in order to obtain an optimum design with a backpropagation algorithm as a solution to simplify the design process. As a result, after 20000 epochs the training loss is around 0.044 and the testing loss is around 0.058. The model has a good performance despite only using a few numbers of training data.

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“…Dunia robotika memasuki berbagai segi di kehidupan manusia mulai dari bidang militer, industri, otomatisasi, entertainment, edukasi maupun juga bidang medis. Humanoid robot adalah salah satu implementasi pada dunia robotika yang dapat menirukan berbagai [4] [5].…”

Section: Pendahuluanunclassified

Pendeteksi Wajah Secara Real Time pada 2 Degree of Freedom (DOF) Kepala Robot Menggunakan Deep Integral Image Cascade

2020

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Abstrak— Teknologi Robot merupakan karya terbaik yang sangat penting bagi kehidupan manusia modern saat ini untuk mempermudah semua pekerjaan manusia. Perkembangan dunia robot saat ini akan difokuskan pada robot yang memiliki fitur mirip manusia. Bahkan diharapkan memiliki kemampuan berinteraksi dan berperilaku seperti manusia yaitu robot humanoid, mekanisme dari gerakan robot humanoid memiliki derajat kebebasan Degree of Freedom (DOF). Layaknya pada manusia robot diberi kemampuan penglihatan untuk mendeteksi adanya objek yang ditangkap secara real time Penelitian kepala robot 2 degree of freedom (DOF) untuk pendeteksi wajah secara real time menggunakan metode Deep Integral Image Cascade untuk deteksi wajahnya. Untuk keakurasian pendeteksi wajah dengan real time pada penelitian ini dengan pengujian akurasi terbesar adalah 95,25% dengan waktu respons pendeteksi tercepat 7 detik dengan waktu terlama 8,55 second rata-rata data citra semuanya tidak terdeteksi dengan benarKata kunci: Raspberry pi, Pendeteksi wajah, Degree of freedom, Haar cascade classifier, Robot kepalaAbstract— Robot technology is the best work that is very important for modern human life today to facilitate all human work. The development of the robot world today will be focused on being a robot that has human-like features. Even expected to have the ability to interact and behave like a humanoid robot, the mechanism of humanoid robot movement has a degree of freedom of Degree of Freedom (DOF). Like in the robot man is given the ability of vision to detect the presence of objects captured in real time robotic head Research 2 degree of freedom (DOF) for face detection in real time using the Deep Integral Image Cascade method to Face Detection. For the real-time accuracy of the face detector in this research with the greatest precision testing is 95.25% with the fastest detection response time of 7 seconds with the oldest time 8.55 second the average image data everything is not detected with Really.Keywords: Raspberry Pi, face detector, Degree of freedom, Haar Cascade classifier, Robot head

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Community Culture Improvisation Regarding Waste Management Systems and Per Capita Income Increase

Cited by 8 publications

References 24 publications

Antenna 5.8 GHz dengan Output Perbedaan Fasa 90 Derajat Ganda Menggunakan Jaringan Matriks Butler Feeding

Antenna 5.8 GHz dengan Output Perbedaan Fasa 90 Derajat Ganda Menggunakan Jaringan Matriks Butler Feeding

Performance Tuning of Spade Card Antenna using Mean Average Loss of Backpropagation Neural Network

Pendeteksi Wajah Secara Real Time pada 2 Degree of Freedom (DOF) Kepala Robot Menggunakan Deep Integral Image Cascade

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