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Indonesian Journal of Electronics and Instrumentation Systems

ijeis
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Published by Universitas Gadjah Mada

ISSN : 20883714 EISSN : 24607681 DOI : -

Core Subject : Engineering,

Electrical & Electronics Engineering

IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), a two times annually provides a forum for the full range of scholarly study. IJEIS scope encompasses all aspects of Electronics, Instrumentation and Control. IJEIS is covering all aspects of Electronics and Instrumentation including Electronics and Instrumentation Engineering.

Arjuna Subject : -

Articles 300 Documents

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Sistem Klasifikasi Tingkat Keparahan Retinopati Diabetik Menggunakan Support Vector Machine Taufiq Galang Adi Putranto; Ika Candradewi
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 1 (2018): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

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.

Perancangan Flowmeter Ultrasonik untuk Mengukur Debit Air Pada Pipa Hidayahtullah Abdi Robhani; Abdul Ro'uf
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 1 (2018): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

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%.

Development of A Pressure Sensing Module and Flow Control System For A Prototype Pump Test Bed Md. Rafsan Nahian; Mohammad Sakalin Zaman; Md. Nurul Islam; Md. Rokunuzzaman
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 2 (2018): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Pump test bed is essential to ensure the proper functioning of a pump. However, a conventional pump test bed has some limitations during measuring the flow properties and variating the pump speed. As a result, a digital pump test bed can be a solution for measuring the flow properties more accurately. This article describes the construction process of a pressure sensing module for a digitalized pump test bed and control of flow by varying the speed of a prototype DC pump. A pressure sensing module and flow control system are constructed in this study to develop a prototype pump test bed as well as change the speed of the centrifugal pump. It is found that by using a piezoelectric pressure sensor in delivery pipe, the pressure sensing error is only 6.3% at the designed speed of pump and can be minimized by calibrating the sensor, fixing the leakage problem and increasing the pressure of flow. A wide variety of pump speeds can also be obtained by applying pulse width modulation principle without stopping the power supply.

Sistem Pengukuran Nitrogen, Fosfor, Kalium Dengan Local Binary Pattern Dan Analisis Regresi Muhammad Miftahul Amri; Raden Sumiharto
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 9, No 2 (2019): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Nitrogen, Phosphorus and Potassium (NPK) are macro elements that important for the paddy development. NPK is a parameter that used for calculating fertilizer dosage. Current NPK measurement through laboratory requires a relatively long time, so we design a new system that can speed up the process and provide correct fertilizer dosage recommendations.This paper proposes an android based system using Local Binary Pattern (LBP) and Regression Analysis to measure soil nutrients and provide fertilizer dosage recommendations based on the LPT Bogor's formula. Samples of soil image taken from rice fields in Special Region of Yogyakarta. The measurement is processed by extracting LBP features from the soil image that has through the pre-processing stage. The extraction results were then analyzed using Multiple Linear Regression (MLR). The equation results from MLR is used to calculate NPK.The results show that the proposed system can detect NPK levels in paddy fields in Yogyakarta and provide fertilization dosage with an average detection accuracy of 70.65% (N 94.98%, P 50.84 %, and K 66.14%). The accuracy was obtained from the image taking at an optimal height of 70 cm and optimal angle of 0o to the ground surface. The average processing time is 0.61 seconds.

Hand-Raise Detection Pada Kelas Cendekia Menggunakan Kamera RGB Dan Depth Muhammad Fajar Khairul Auni; Muhammad Idham Ananta Timur; Ika Candradewi
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 1 (2018): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

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%.

Analisis Perbedaan Pola Sinyal EEG Berdasarkan Jenis Kelamin Yang Berbeda Saat Numerical Stroop Task Riswandha Latu Dimas; Catur Atmaji
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 1 (2018): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

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.

Kelas Cendekia Versi Mobile yang Terintegrasi dengan Sistem Rekomendasi Nur Ridho Abdurrahmansyah; Muhammad Idham Ananta Timur
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 2 (2018): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Urgency usefulness of online learning system based on social constructivism which is the mobile virtual classroom learning philosophy is of concern, because the system is built on the pattern of reciprocity between users in order to produce the most quality materials see the absence of a system that provides online learning for it. Content of lecture materials that have been divided into certain categories are processed into virtual versions and delivered lightly. The recommendation system is designed to respond users who have rated it by providing good quality course material. Software is created with Unity Engine and incorporated the recommended system protocol with data stored in a scholarly research database. The recommendation system implemented is the items based collaborative filtering with the specification of training data used are 401 rating data, 51 records and 17 users. With sparsity data training amounted to 53.74%, tested the prediction accuracy resulted RMSE 0.91523 and the accuracy of 81.69%. The mobile version of virtual class that has been planted with recommendation system is tried and tested on several brands of android smartphone. Results obtained on the questionnaire resulted in a rating of 4,762 on performance and 4,572 against the intellectual class software interface. Whereas the level of user enthusiasm for the virtual class reaches 4,0588 on a scale of 1 to 5.

Brain Tumor Classification Using Gray Level Co-occurrence Matrix and Convolutional Neural Network Wijang Widhiarso; Yohannes Yohannes; Cendy Prakarsah
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 2 (2018): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Image are objects that have many information. Gray Level Co-occurrence Matrix is one of many ways to extract information from image objects. Wherein, the extracted informations can be processed again using different methods, Gray Level Co-occurrence Matrix is use for clarifying brain tumor using Convolutional Neural Network. The scope in this research is to process the extracted information from Gray Level Co-occurrence Matrix to Convolutional Neural Network where it will processed as Deep Learning to measure the accuracy using four data combination from TI1, in the form of brain tumor data Meningioma, Glioma and Pituitary Tumor. Based on the implementation of this research, the classification result of Convolutional Neural Network shows that the contrast feature from Gray Level Co-occurrence Matrix can increase the accuracy level up to twenty percent than the other features. This extraction feature is also accelerate the classification process using Convolutional Neural Network.

Hybrid Support Vector Machine to Preterm Birth Prediction Noviyanti Santoso; Sri Pingit Wulandari
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 2 (2018): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Preterm birth is one of the major contributors to perinatal and neonatal mortality. This issue became important in health research area especially human reproduction both in developed and developing country. In 2015 Indonesia rank fifth as the country with the highest number of premature babies in the world. The ability to reduce the number of preterm birth is to reduce risk factors associated with it. This research will be made the prediction model of preterm birth using hybrid multivariate adaptive regression splines (MARS) and Support Vector Machine (SVM). MARS used to select the attributes which suspected to affect premature babies. The result of this research is prediction model based on hybrid MARS-SVM obtains better performance than the other models

Otomasi Kamera Perangkap Menggunakan Deteksi Gerak dan Komputer Papan Tunggal Habib Dwi Cahya; Agus Harjoko
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 9, No 1 (2019): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

USB camera is currently used in daily life for various purposes. On its development, the use of USB camera can be used to create camara traps and can be used to observe the development of animal with integrated systems. In this research, motion detection was used to observe animals online using Single Board Computer (SBC) Camera trap in this research using Single Board camera in form of raspberry pi 3 B. Python proggramming language is used with OpenCV library. The method used to detect motion is the Mixture of Gaussian (MOG). The result image gained by motion detection will be uploaded to the dropbox API.The test performed on 11 videos, the system can process images with 320x240 resolution. The test results show the best blut value of k = 13, the best threshold value is 100 pixel with an accuracy of 80,3%, and the maximum distance system can detect animal objects as far as 6m. The response time gained for the sytem to process frame per second have average of 0,098 seconds, while for uploading image to dropbox han an average of 1,618 seconds. The test result show the system still has room for development and improvement.

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