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Optimation Free Space Optic (FSO) Design with Kim Model Using Space Diversity Triyono Subekti; Anggun Fitrian Isnawati; Dodi Zulherman
JURNAL INFOTEL Vol 11 No 3 (2019): August 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i3.444

The development of communication services in remote rural areas is difficult to use cable-based systems such as Digital Subscriber Line (DSL) and FTTx. One solution to solve this problem is to use a wireless system such as radio communication. Free Space Optic (FSO) communication system is a better choice compared to radio communication because of the flexibility of frequency usage. One of the problems of the FSO communication system is the range not too far. The range of the FSO can be increased by using the space diversity method. This study compared FSO systems that not use space diversity and FSO systems that use space diversity in three weather conditions, namely clear, haze, and fog. In taking data results using Kim model propagation with variations in the range between 100 – 2000 meters. The modulation used in this study is external modulation. The result of the analysis of FSO performance after adding space diversity, the range of FSO increases as far as 1200 meters when the condition is clear. During the haze condition, the FSO range increase as far as 800 meters. During the fog condition, the FSO range has increased as far as 300 meters. By adding space diversity, the Q-factor value has increased, and BER (Bit Error Rate) has decreased.

Performance Analysis of Fetal-Phonocardiogram Signal Denoising Using The Discrete Wavelet Transform Ipam Fuadina; Jans Hendry; Dodi Zulherman
JURNAL INFOTEL Vol 11 No 4 (2019): November 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i4.458

The obligation for comprehensive fetal heart rate investigation had driven to improve the passive and non-invasive diagnostic instruments despite the USG or CTG method. Fetal phonocardiography (f-PCG) utilizing the auscultation method met the above criteria, but its interpretation frequently disturbed by the presence of noise. For instance, maternal heart and body organ sounds, fetal movements noise, and ambient noise from the environment where it is recording are the noise that corrupted the f-PCG signal. In this work, the use of discrete wavelet transforms (DWT) to eliminate noise in the f-PCG signal with SNR as the performance parameters observed. It was observing the effect of changes in wavelet type and threshold type on the SNR value. The test was carried out on f-PCG data taken from physio.net. Initial SNR values ranged from -26.7 dB to -4.4 dB; after application of DWT procedure to f-PCG, SNR increased significantly. Based on the test results obtained, wavelet type coif1 with the soft threshold gave the best result with 11.69 dB in SNR value. The coif1 had a superior result than other mother wavelets that use in this work, so the fPCG signal analysis for fetal heart rate investigation suggested to use it.

Software-based simulation to analyze the variation of digital modulation and atmospheric condition on the free space optic (FSO) link performance Fauza Khair; Dodi Zulherman; Rifani Auliana
JURNAL INFOTEL Vol 14 No 3 (2022): August 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v14i3.758

Free Space Optic (FSO) is the solution for telecommunications technology that offers high data rates, wide bandwidth, and low power consumption. However, to maximize the performance of the FSO system, the modulation used should be considered in environmental conditions. This study aims to compare the performance of the FSO communication link based on digital modulation variations used in various weather conditions, including sunny, rainy, and foggy weather. This study uses two attenuation models, namely the Kim and Kruse models, with variations in transmission distance from 500 meters to 10 kilometers. Modulation variations used include QPSK, 8-PSK, 16-PSK, and 16-QAM at 10 Gbps bitrate. The simulation is accomplished using OptiSystem 17.0 software. The study results show that sunny weather (very clear) has the best visibility compared to rain and fog conditions with an attenuation value of 0.46 dB/km on the Kim and Kruse models. QPSK modulation has the best performance with a BER value of less than 1x10-12 up to a transmission distance of 8 km in sunny weather, 3 km in rainy weather (medium rain), and 800 m in foggy (moderate fog) weather. The 8-PSK modulation has a BER value of less than 1x10-12 with a range of 2000 m in sunny weather and 1500 m in rainy weather but does not meet the standards in foggy weather conditions. 16-PSK and 16-QAM modulation have above baseline BER values during rainy and foggy conditions, but 16-QAM modulation still has a BER value of less than 1x10-3 during foggy conditions at a distance of 500 m.

Pendeteksi dini dan penjejak kendaraan yang datang dari jarak jauh dengan pendeteksi referensi titik hilang untuk lampu lalu lintas adaptif Yoanda Alim Syahbana; Dodi Zulherman; Yokota Yasunari
JURNAL INFOTEL Vol 15 No 2 (2023): May 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i2.890

Real-time traffic monitoring is essential for the operation of an adaptive traffic lighting system and plays a significant role in decision-making, particularly signaling in roadworks. When only one lane is accessible due to temporary road blockage, early detection of oncoming vehicles is crucial to minimize bottlenecks near the traffic light that could result in congestion and accidents. This research aimed to enhance the detection and tracking of traffic at a distance from the traffic light. We utilized the vanishing point as a reference for detection and calculated the region of interest. We implemented the proposed method on twelve traffic surveillance videos and evaluated the system performance based on how quickly it could detect incoming traffic compared with the R-CNN method. The proposed method detected target vehicles in an average of 17.75 frames, while the R-CNN method required an average of 63.36 frames. Moreover, the proposed method’s precision depends on the number of pixel orientations used to estimate the vanishing point and the definition of the region of interest. Therefore, the proposed method for enhancing the safety and reliability of an adaptive traffic light system is reliable.

Analisis Perbandingan Kinerja Pengkodean Kanal Non-Return-to-Zero (NRZ) dan Return-to-Zero (RZ) pada Rancangan Jaringan Long-haul Dense Wavelength Division Multiplexing (DWDM) Olivian Bagas Pratama; Anggun Fitrian Isnawati; Dodi Zulherman
Buletin Pos dan Telekomunikasi Vol. 17 No. 2 (2019): Desember 2019
Publisher : Centre for Research and Development on Resources, Equipment, and Operations of Posts and I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17933/bpostel.2019.170205

Abstrak Perkembangan jangkauan dan penggunaan internet mendorong pengembangan penyediaan layanan dengan transmisi data yang cepat dan kapasitas yang besar seperti layanan berbasis serat optik. Jaringan long-haul DWDM sebagai teknologi multipleksing sangat mendukung proses transmisi optik jarak jauh. Performa media transmisi long-haul DWDM membutuhkan teknik pengkodean kanal yang dapat diimplementasikan pada sisi pengirim agar diperoleh sistem yang efisien dalam hal bandwidth transmisi. Dalam komunikasi serat optik terdapat beberapa jenis teknik pengkodean kanal yang umum digunakan seperti non-return-to-zero (NRZ) dan return-to-zero (RZ). Penelitian ini bertujuan untuk membandingkan kinerja rancangan sistem dengan variasi teknik pengkodean dengan memberikan variasi daya pancar laser sebesar 0, 2, 4, 6, dan 8 dBm dan variasi jarak sebesar 200, 400, 600, 800, dan 1000 km. Rancangan sistem menggunakan modulasi eksternal dan NRZ atau RZ pada sisi transmitter, serat optik dan penguat EDFA pada media transmisi, dan detektor optik pada sisi receiver. Berdasarkan hasil penelitian, tidak semua kanal sesuai dengan hasil Q-factor dan BER berdasarkan standar ITU-T, namun jenis pengkodean kanal NRZ lebih baik digunakan pada jenis jaringan long-haul DWDM. Abstract The increasing of coverage area and demand for internet services are both drive the development of providing services with high bitrate transmission and gigantic capacity, such as fiber optic communication. Long-haul DWDM network as a multiplexing technology is very supportive in the long-distance optical transmission link requiring channel coding which can be implemented in transmitter. There are various types of channel coding used in optical fiber communication, such as non-return-to-zero and return-to-zero. The aims of this work are to compare the system performance with different channel coding in long-haul link using variations of optical power launch with value 0, 2, 4, 6, and 8 dBm and variations of length of link with value 200, 400, 600, 800, and 1000 km. The design system uses external modulation and NRZ or RZ on the transmitter, optical Fiber with EDFA amplifier on the optical transmission, and optical detector on the receiver. Based on the results, there are several channels with the Q-factor and BER that do not meet the ITU standards. In addition, the NRZ channel coding is better used in the long-haul DWDM link.

Klasifikasi Pergerakan Tangan dan Kaki Berbasis Sinyal EEG Menggunakan Common Spatial Patterns dan Multilayer Perceptron Backpropagation Widadi, Rahmat; Zulherman, Dodi
Jurnal Telematika Vol. 14 No. 2 (2019)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v14i2.292

The artificial bionic appendicular systems, such as hands and feet movement, require the Brain-Computer Interface (BCI) to control the movement. The BCI based movement controlling in a bionic device utilises the EEG signal directly, but the EEG signal classification has to design before it implemented in a BCI device. This study aims to design a classification system for hands and feet movements based on beta channel EEG signals. The system design used the Common Spatial Pattern (CSP) method for feature extraction and stochastic gradient descent in Multilayer Perceptron Backpropagation (MLP-BP) for the hands and feet movement classification. We use the EEG signal from ten subjects to evaluate the design. Also, the variation number of node in MLP-BP to get the system performance based on the confusion matrix. Based on the test results, the improvement of the number of nodes brought the accuracy increasing, especially for variation two, four and eight nodes. The highest mean of system design accuracy reached 94.38% for eight nodes.Teknologi brain computer interface (BCI) dibutuhkan untuk mekanisme pengaturan gerak dari alat bantu bionik sistem appendicular, khususnya tangan dan kaki. Pengendali pergerakan devais bionik berbasis BCI dapat menggunakan sinyal EEG, namun sistem pengelompokan sinyal EEG untuk pergerakan tangan dan kaki dibutuhkan sebagai tahapan awal pengimplementasian tersebut. Penelitian ini bertujuan untuk merancang sebuah sistem klasifikasi pergerakan tangan dan kaki berdasarkan sinyal EEG gelombang beta. Rancangan sistem menggunakan metode Common Spatial Patterns (CSP) pada tahap ekstrasi fitur dan stochastic gradient descent dalam Multilayer Perceptron Backpropagation (MLP-BP) untukmengklasifikasi pergerakan tangan dan kaki. Pengujian sistem menggunakan confusion matrix terhadap sepuluh subjek dan variasi jumlah node MLP-BP. Berdasarkan hasil pengujian, nilai rata-rata akurasi sistem dengan jumlah node dua, empat dan delapan meningkat sebanding dengan peningkatan jumlah node, namun nilai rata-rata akurasi menurun kembali saat jumlah node ditingkatkan menjadi enam belas. Rata-rata akurasi rancangan sistem yang tertinggi mencapai 94,38 % pada sistem dengan delapan node pada hidden layer.

Peran Karakteristik Keluarga Dalam Mendukung Pertumbuhan Dan Perkembangan Anak Prasekolah Qoriansas, Nanda; Andriani, Rizki; Rosita, Erlia; Zulherman, Dodi; Nasution, Nurromsyah
BEST Journal (Biology Education, Sains and Technology) Vol 7, No 2 (2024): September 2024
Publisher : Program Studi Pendidikan Biologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/best.v7i2.9932

Faktor keluarga mempengaruhi pertumbuhan dan perkembangan anak prasekolah, terutama di masa-masa awal kehidupan yang krusial bagi perkembangan jangka panjang mereka. Penelitian ini bertujuan untuk menganalisis hubungan antara karakteristik keluarga dengan pertumbuhan fisik (berat badan dan tinggi badan) serta perkembangan kognitif, motorik, dan sosial anak prasekolah. Metode penelitian ini menggunakan pendekatan kuantitatif dengan desain cross-sectional. Data dikumpulkan dari 42 keluarga yang memiliki anak prasekolah yang bersekolah di PAUD Keumala Bhayangkara Tapaktuan, Aceh Selatan. Analisis data dilakukan menggunakan uji bivariat dan komputerisasi menggunakan SPSS 25. Hasil penelitian menunjukkan tidak ada hubungan signifikan antara karakteristik keluarga dengan pertumbuhan anak, dengan p-value yang tidak signifikan untuk usia ibu, pendidikan, pekerjaan, dan pendapatan (p 0,05). Namun, terdapat hubungan yang signifikan antara pendidikan dan pendapatan ibu dengan perkembangan anak, di mana p-value untuk pendidikan adalah 0,032, pekerjaan 0,038, dan pendapatan 0,000. Penelitian ini menunjukkan bahwa meskipun faktor keluarga seperti usia, pendidikan, dan pekerjaan ibu tidak mempengaruhi pertumbuhan fisik anak secara langsung, pendidikan dan pendapatan ibu memiliki peran penting dalam perkembangan kognitif, motorik, dan sosial anak. Hal ini mengindikasikan bahwa dukungan ekonomi dan pendidikan yang memadai dapat meningkatkan kemampuan ibu dalam menyediakan lingkungan yang mendukung perkembangan anak yang optimal

Peran Karakteristik Keluarga Dalam Mendukung Pertumbuhan Dan Perkembangan Anak Prasekolah Qoriansas, Nanda; Andriani, Rizki; Rosita, Erlia; Zulherman, Dodi; Nasution, Nurromsyah
BEST Journal (Biology Education, Sains and Technology) Vol 7, No 2 (2024): September 2024
Publisher : Program Studi Pendidikan Biologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/best.v7i2.9932

Faktor keluarga mempengaruhi pertumbuhan dan perkembangan anak prasekolah, terutama di masa-masa awal kehidupan yang krusial bagi perkembangan jangka panjang mereka. Penelitian ini bertujuan untuk menganalisis hubungan antara karakteristik keluarga dengan pertumbuhan fisik (berat badan dan tinggi badan) serta perkembangan kognitif, motorik, dan sosial anak prasekolah. Metode penelitian ini menggunakan pendekatan kuantitatif dengan desain cross-sectional. Data dikumpulkan dari 42 keluarga yang memiliki anak prasekolah yang bersekolah di PAUD Keumala Bhayangkara Tapaktuan, Aceh Selatan. Analisis data dilakukan menggunakan uji bivariat dan komputerisasi menggunakan SPSS 25. Hasil penelitian menunjukkan tidak ada hubungan signifikan antara karakteristik keluarga dengan pertumbuhan anak, dengan p-value yang tidak signifikan untuk usia ibu, pendidikan, pekerjaan, dan pendapatan (p 0,05). Namun, terdapat hubungan yang signifikan antara pendidikan dan pendapatan ibu dengan perkembangan anak, di mana p-value untuk pendidikan adalah 0,032, pekerjaan 0,038, dan pendapatan 0,000. Penelitian ini menunjukkan bahwa meskipun faktor keluarga seperti usia, pendidikan, dan pekerjaan ibu tidak mempengaruhi pertumbuhan fisik anak secara langsung, pendidikan dan pendapatan ibu memiliki peran penting dalam perkembangan kognitif, motorik, dan sosial anak. Hal ini mengindikasikan bahwa dukungan ekonomi dan pendidikan yang memadai dapat meningkatkan kemampuan ibu dalam menyediakan lingkungan yang mendukung perkembangan anak yang optimal

Combining Finite State Machine and Fuzzy Logic Control for Accuracy Enhancing Performance of a Tomato-Handling Robot Gripper Mardiati, Rina; Firdaus, Hardiansyah; Setiawan, Aan Eko; Zulherman, Dodi
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23579

Robotic grippers are becoming increasingly vital in modern agriculture, especially in tasks like harvesting delicate crops such as tomatoes, where precision and care are crucial. These advanced tools are designed to handle tomatoes without causing damage, significantly improving efficiency and reducing labor costs. Research on gripper robots for fruit picking continues to be developed using various methods in an effort to achieve accurate picking results. This study proposes a hybrid method that combines Finite State Machine (FSM) for behavior control with Fuzzy Logic Control (FLC) to optimize the positioning of the gripper. The system utilizes a PixyCam2 CMUcam5 for tomato detection, an Arduino microcontroller for image processing, and a servo mechanism to precisely align the gripper with the target. The experimental results confirm that each component functions as expected, with the gripper successfully performing actions such as idling, gripping, and placing in accordance with the FSM model. Furthermore, the FLC model was tested against simulations, resulting in error rates of 1.004% for the elbow angle and 0.826% for the base angle. The entire system was validated by comparing the performance of the system using FLC and non-FLC in ten tests, each with tomatoes placed in different positions. The results indicate that the proposed gripper, utilizing the FSM-FLC model, achieved a 100% success rate in grasping the target, significantly outperforming the FSM-non-FLC gripper, which achieved only a 20% success rate. These findings have important implications for the agricultural industry. The successful integration of the FSM and FLC models in robotic grippers paves the way for fully automated harvesting systems, potentially reducing costs and enhancing productivity.

Klasifikasi Sinyal Phonocardiogram Menggunakan Short Time Fourier Transform dan Convolutional Neural Network Amal, Muhammad Alwi Adnan; Zulherman, Dodi; Widadi, Rahmat
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 2: April 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20235424

Berdasarkan laporan American Heart Association, penyakit kardiovaskular menjadi penyebab kematian global tertinggi. Phonocardiogram (PCG) dan electrocardiogram (ECG) biasanya digunakan untuk mendeteksi penyakit jantung. Penggunaan sinyal PCG memberikan hasil prediksi yang lebih baik pada deteksi penyakit jantung bila dibandingkan dengan ECG. Tetapi, penggunaan PCG secara elektronik membutuhkan analisis sinyal yang kompleks untuk mengklasifikasikan kondisi jantung. Penelitian ini bertujuan merancang suatu sistem klasifikasi sinyal PCG berdasarkan metode ekstraksi fitur menggunakan Short Time Fourier Transform (STFT) dan metode klasifikasi menggunakan Convolutional Neural Network (CNN). Pengujian rancangan sistem menggunakan dataset sekunder dengan 2.575 rekaman PCG normal dan 665 rekaman PCG abnormal dalam format wav. Pengujian kinerja menggunakan variasi Hamming, Hann dan Blackman-Harris Window pada bagian ektraksi fitur dan variasi jumlah layer konvolusi pada bagian klasifikasi. Berdasarkan hasil pengujian, penggunaan hamming window pada proses ekstraksi fitur dan 4 layer konvolusi pada proses klasifikasi memberikan hasil terbaik dengan tingkat akurasi 88,11%. Penelitian ini membuktikan bahwa penggunaan hamming window pada bagian ekstraksi fitur dan 4 layer konvolusi pada bagian klasifikasi sebagai bentuk model terbaik sistem klasifikasi PCG berdasarkan STFT dan CNN. AbstractAccording to a report by the American Heart Association, cardiovascular disease is the leading global cause of death. Phonocardiogram (PCG) and electrocardiogram (ECG) are commonly used to detect heart disease. The use of PCG signals provides better predictive results in the detection of heart disease when compared to ECG. However, the use of PCG electronically requires complex signal analysis to classify heart conditions. This study aims to design a PCG signal classification system based on the extraction method using the Short Time Fourier Transform (STFT) and the classification method using the Convolutional Neural Network (CNN). The system design test used a secondary dataset with 2,575 normal PCG records and 665 abnormal PCG records in wav format. Performance testing uses variations of Hamming, Hann and Blackman-Harris Window in the feature extraction section and variations in the number of convolution layers in the classification section. Based on the test results, the use of a hamming window in the feature extraction process and 4 convolution layers in the classification process gives the best results with an accuracy rate of 88.11%. This study proves that the use of a hamming window in the feature extraction section and 4 convolution layers in the classification section is the best form of the PCG classification system based on STFT and CNN.

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