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IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)
Number of Followers: 3  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2088-3714 - ISSN (Online) 2460-7681
Published by Universitas Gadjah Mada Homepage  [38 journals]
  • Pengembangan Sistem Ground Control Station Berbasis Internet Webserver
           pada Pesawat Tanpa Awak

    • Authors: Fredy Aga Nugroho, Raden Sumiharto, Roghib Muhammad Hujja
      Pages: 1 - 12
      Abstract: In unmanned aerial operations, the ground control station duties as a monitoring and command station so that operators on land can send mission orders, monitor the mission's course and monitor the condition of the UAV during the mission. It is necessary to have a GCS system capable of connecting with UAV that not limited with control transmitter range.This research develops GCS system using internet network and web server based. the system consists of two units, namely flying units and GCS units. The flying unit consists of Raspberry pi, modem, webcam, ADAHRS module and quadrotor with MultiWii controller. on the GCS unit consists of Raspberry pi connected on the internet network with 10Mbps download speed and 1.5Mbps upload.The GCS system can display aircraft conditions, stream video and perform command controls. Configure streaming video for delay time of no more than one second with 240x144 pixel resolution, 256kbps maximum bitrate and 5 fps framerate. This configuration runs at a 1.1 Mbps upload speed with a percentage of 93.83% bitrate compression. Aircraft condition data sent to GCS is optimal if internet bandwidth exceeds the bitrate of streaming video used on the system
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.30126
      Issue No: Vol. 8, No. 1 (2018)
  • Implementasi Algoritma PSO Pada Multi Mobile Robot Dalam Penentuan Posisi
           Target Terdekat

    • Authors: Ikhwannuary Raditya Priyadana, Bakhtiar Alldino Ardi Sumbodo, Triyogatama Wahyu Widodo
      Pages: 13 - 24
      Abstract:  Swarm Intelligence is an artificial intelligence developed by adapting the social behavior of a group of animal. In the migratory birds community, it is known that the behavior of the birds during the flight forms a 'V' formation that plays a role in optimizing the bird's energy saving. The basic principle of a swarm intelligence is the existence of collective, decentralized and self-organizing behavior. This is the basis for the development of behavioral algorithms flocking birds called Particle Swarm Optimization (PSO).In this research used three mobile robot as object to implement PSO algorithm. Three pieces of this robot is homogeneous, which is similar hardware and software. A group of these robots will complete the joint mission of defining the robot with the closest distance to the target TPr (robot handler). There are three TPr targets that have to be executed by the robot handler according to their position with the target point to be completed. The test is done by taking odometry data every 250 milisekon and data frame robot communication.At the end of this research, the result of modeling system result of PSO algorithm implementation on mobile robot group to determine the robot closest to the target. The robot system that meets the principles of PSO, namely the process of data sharing and learning process.
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.25505
      Issue No: Vol. 8, No. 1 (2018)
  • Sistem Pengukuran Modulus Elastisitas Beton Menggunakan Metode Ultrasonic
           Pulse Velocity

    • Authors: Amanda Purwanto, Abdul Ro’uf
      Pages: 25 - 36
      Abstract: Modulus of elasticity of concrete usually measured by Destructive Testing which is not considered as an effective way, because It will destroy the concrete. Ultrasonic Pulse Velocity can be a solution to measure value of modulus of elasticity without destructing it. The concept of the system is to look for velocity of wave, then put the value into modulus elasticity formula.UPV system will transmit ultrasonic wave through concrete. HC-SR04 used for generating 40 kHz wave, increasing voltage of wave on receiver, and calculating time travel. The voltage of wave sent by HC-SR04 is only about 10 volt, so that power and voltage of wave has to be amplified. Piezoelectric is used as a transducer which can converts electrical to mechanical energy.  The results of this research shows that error value on wave velocity measurement have an average value for about 18,2% compared to result of UPV Pundit. Static modulus of elasticity from compressive test is compared to value of dynamic modulus of elasticity that is obtained by UPV system with HC-SR04. Ratio between two values is about 45% - 249%.
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.30978
      Issue No: Vol. 8, No. 1 (2018)
  • Sistem Klasifikasi Tingkat Keparahan Retinopati Diabetik Menggunakan
           Support Vector Machine

    • Authors: Taufiq Galang Adi Putranto, Ika Candradewi
      Pages: 37 - 48
      Abstract: Diabetic retinopathy is a vision disorder disease that can cause damage to the retina of the eye that will have a direct impact on the disruption of vision of the patient. The diabetic retinopathy phase is classified into four types (normal, mild NPDR, moderate NPDR (Non-Proliferative Diabetic Retinopathy), and severe NPDR). Retinal of eye data of diabetic retinopathy patients treated from the MESSIDOR database. By applying image processing, the retinal image of the eye in extraction using the area features extraction from the detection of exudate, blood vessels, microaneurysms, and texture feature extraction Gray Level Co-occurrence Matrix. The extracted results classified using the Support Vector Machine method with the Radial Basis Function (RBF) kernel. Classification evaluated with these parameters: Accuracy, specificity, and sensitivity.The results of classification show the best value using 6 statistical features ie, contrast, homogeneity, correlation, energy, entropy and inverse difference moment in the direction of 45 degrees with the RBF kernel. The result of classification research system on 240 data training and 60 data testing yields an average accuracy is 95.93%, the value of specificity is 97.29%, and a sensitivity rating is  91.07%. From the research result, using RBF kernel get the best accuracy result than using kernel polynomial or kernel linear.
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.31206
      Issue No: Vol. 8, No. 1 (2018)
  • Klasifikasi Kakao Berbasis e-nose dengan Metode Neuro Fuzzy

    • Authors: Ikhsan Nur Rahman, Danang Lelono, Kuwat Triyana
      Pages: 49 - 60
      Abstract: During this time to clasify quality of cacao based on color and aroma involving human taster. But this cacao tester still has weaknesses such as subjective. Besides that, the standard chemical analytical methods requires a high cost and need expertise to analyzing it. Basically aroma of cacao is determined by volatile compounds such aldehid and alcohol. Electronic nose based on unselected gas sensor array has the ability to analyze samples with complex compositions that can be known characteristics and qualitative analysis of the samples. Stimulus aroma is transformed by electronic nose into fingerprint data then it is used by feature extraction process using the differential method. The results of feature extraction is used to process the neuro fuzzy training to obtain optimal parameters. The parameters have been optimized is then tested on cacao. Based on test results, neuro fuzzy can clasify samples with 95,21% accuracy rate so that the clasification of cacao quality with electronic nose using neuro fuzzy has been successfully carried out.
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.25512
      Issue No: Vol. 8, No. 1 (2018)
  • Klasifikasi Teh Hijau dan Teh Hitam Tambi-Pagilaran dengan Metode
           Principal Component Analysis (PCA) Menggunakan E-Nose

    • Authors: Inca Inca, Triyogatama Wahyu Widodo, Danang Lelono
      Pages: 61 - 72
      Abstract: This research aims to classification of samples of green tea and black tea originated from different planting sites,  Tambi and Pagilaran. Samples of green tea and black tea; quality I (BOP), quality II (BP), quality III (Bohea) were each collected from Tambi and Pagilaran to analyze the charasteristic of both sample from both sites. Measurements of tea samples were performed using a dynamic e-nose device based on a MOS gas sensor, with a maximum set point temperature of 40ºC, flushing 300 seconds, collecting 120 seconds, and purging 80 seconds for 10 cycles repeatedly. The resulting sensor response is then processed using the difference method for baseline manipulation. Characteristic of extraction process on the sensor response results is carried out in three methods; relative, fractional change, and integral. Matrix data of the feature extraction results was reduced using the PCA method by mapping the aroma patterns of each sample using 2-PCA components. The PCA reduction results in integral feature extraction showed the largest percentage of cumulative variance in classifying green tea sample data by 97% and black tea by 100%. The large percentage value of cumulative variance indicates PCA can differentiate samples of green tea and black tea from Tambi and Pagilaran well.
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.28718
      Issue No: Vol. 8, No. 1 (2018)
  • Collaborative Filtering Recommender System pada Virtual 3D Kelas Cendekia

    • Authors: Angga Setia Wardana, Muhammad Idham Ananta Timur
      Pages: 73 - 82
      Abstract:  Intelligent Clasrooms is a concept of modern learning process where users can perform collaborative learning wherever and whenever. With learning in Intelligent Classroom, users can get different learning experience where learning process is expected to run more effectively and efficiently. One application of the Intelligent Classrooms concept is learning by utilizing the virtual world. The information collected in the Intelligent Classroom will increase so that a system is needed. The recommendation system of collaborative filtering is the most appropriate system with the intellectual class. With the sparsity of training rate of 80%, it is implemented a collaborative filtering recommendation system with error rate which if calculated with RMSE is 1.060709 or it can be said that the accuracy level is 78.79%.
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.28729
      Issue No: Vol. 8, No. 1 (2018)
  • Perancangan Flowmeter Ultrasonik untuk Mengukur Debit Air Pada Pipa

    • Authors: Hidayahtullah Abdi Robhani, Abdul Ro'uf
      Pages: 83 - 94
      Abstract:  Measurement of water discharge using ultrasonic wave properties ensures the stability of measured water profile because of its non-intrusive nature. In this study, a water discharge measuring device has been developed by utilizing ultrasonic wave properties to determine its speed. The device is designed using two pairs of ultrasonic transmitters and receivers at upstream and downstream positions toward the direction of the water flow. 40 kHz ultrasonic waves are generated with AD9850 DDS sinusoidal pulse generating module. The sensor data processor uses an Arduino Due microcontroller module by calculating the measured ultrasonic wave travel time difference.             Measurements were made on a 57 mm diameter pipe with flow rates varied using 25%, 50%, 75%, and 100% tap openings. The measurement resulte shows the lowest water debit calculation value of 4.42×10-4 m3/s at 25% faucet opening and highest discharge of 2.15×10-3 m3/s at 100% faucet opening with the values of coefficient of correlation and coefficient of determination on 25%, 50%, 75% and 100% faucet openings respectively 0.9715, 0.9669, 0.9604 and 0.9647 and 94.37%, 93.49%, 92 , 24%, and 93.07%.
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.31774
      Issue No: Vol. 8, No. 1 (2018)
  • Hand-Raise Detection Pada Kelas Cendekia Menggunakan Kamera RGB Dan Depth

    • Authors: Muhammad Fajar Khairul Auni, Muhammad Idham Ananta Timur, Ika Candradewi
      Pages: 95 - 106
      Abstract: The requisite of intelligent classroom’s to perform the quickest speaker lift determination of speakers in the classroom using the concept of ubiquitous computing where the technology exists but does not feel around. The classroom concept requires several capabilities such as knowing the ideal distance from the camera, performing real-time hand-lifted movements from the speaker using the AdaBoost method, and determining the fastest hand lift from the speaker in real-time. The camera's ideal distance to speakers is about 250 cm. the system has a detection accuracy of 97.485497% and accuracy using coordinates joint point of 98%. The system is also capable of determining the fastest time using AdaBoost with 93.5% accuracy and the accuracy of the fastest hands lifting using coordinates joint point of 95%.
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.34162
      Issue No: Vol. 8, No. 1 (2018)
  • Analisis Perbedaan Pola Sinyal EEG Berdasarkan Jenis Kelamin Yang Berbeda
           Saat Numerical Stroop Task

    • Authors: Riswandha Latu Dimas, Catur Atmaji
      Pages: 107 - 118
      Abstract: Cognitive process show how brain work from stimulus reception until stimuls reaction. With electroencephalogram (EEG) device, cognate process can be observerd in brain signal or EEG signal form. In cognitive process different kind of stimulus could affect generated brain signal. Also, given interference in cognitive prcess could affect brain signal. In this research, conducted observation whether gender difference has effect in cognitive process. Numerical stroop task with three kinds of conditions (congruence, incongruence, and neutral) are used as reference in signal observation process which is generated when the cognitive process in difference genders are done. The resulting EEG signal then conducted three kinds of analysis that is ERP analysis, reaction time, and energy analysis. The result of ERP analysis show both subject class have difference in response time that indicated with P3 peak time. On average, respons time in female (kongruent = 623,34 ms; inkongruent = 645,18 ms ; neutral = 614,91 ms)subject class is faster than male (kongruent = 709,67 ms; inkongruent = 745,00 ms; neutral =715,37 ms) subject class. Energy analysis show when numerical stroop task takes place, left side of the brain (51,36%) and cetral side of the brain (50,65%) more dominant than others parts of the brain.
      PubDate: 2018-04-30
      DOI: 10.22146/ijeis.34383
      Issue No: Vol. 8, No. 1 (2018)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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