Triyogatama Wahyu Widodo
Dapartment Of Computer Science And Electronics, Faculty Of Mathematics And Natural Science, Universitas Gadjah Mada, Yogyakarta

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Rancang Bangun Electronic Nose untuk Mendeteksi Tingkat Kebusukan Ikan Air Tawar Chrisal Aji Lintang; Triyogatama Wahyu Widodo; Danang Lelono
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 6, No 2 (2016): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (744.399 KB) | DOI: 10.22146/ijeis.15251

Abstract

When fish die, fish freshness start to reduce gradually until cannot be eaten anymore. Properness of fish meat can be identified by odor that come out from fish itself. An instrument called electronic nose that can detect pattern of fish odor has been designed and implemented in this research.To be able to detect scent of freshwater fish, electronic nose will drain the air from sample chamber to sensor chamber using fan. When taking sample aroma, fan will drain air that contain sample scent from sample chamber to sensor chamber, and air from the outside flowed into sensor chamber when odor off. Scent stimulus captured by sensor array in form of signal response will be extracted with integral method so that the digital fingerprint from samples can be obtained. This pattern then analyzed by PCA (Principal Component Analysis) to determine patterns of freshwater fish odor.Result from this study indicated that electronic nose system can detect scent of freshwater fish with percentage variance of two major components are 98.7% (pomfret), 98.8% (catfish), and 99.5% (tilapia). Sensors that give high response in each samples is TGS 2620, and TGS 2600. TGS 822 give high response when fish is rotting.
Pengembangan Hidung Elektronik untuk Klasifikasi Mutu Minyak Goreng dengan Metode Principal Component Analysis Soca Baskara; Danang Lelono; Triyogatama Wahyu Widodo
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 6, No 2 (2016): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (653.406 KB) | DOI: 10.22146/ijeis.15347

Abstract

The existence of cooking oil which is mixed with dangerous material is very difficult to be detected by human olfactory system yet can be detected by sophisticated equipment. However, the equipment is very expensive and require an expert to operate it.Static system of electronic nose based on unselected gas sensor array has been built for classifying pure cooking oil’s odour and mixed cooking oil’s odour. Sensor array consist of sensor MQ-9, TGS-2600, MQ-2, TGS-2620, and TGS-822 along with a heat exchanger system that can reduce the temperature of sample’s odour. The sample chamber and sensor chamber are made from stainless steel with cylinder shape. The system tested by boiling the sample consist of each pure cooking oil form both palm and coconut oil with its mixture such as used lubricant, candle, and diesel fuel up to 300 0C to realese its odour. After the odour has been detected by electronic nose the next step is to classifying the data with PCA method.The result show that the response of sensor’s output is stable and the output of score plot from each pure cooking oil’s data from both palm and coconut oil can be well-classified from the mixed cooking oil.
Purwarupa Sistem Pembuka Pintu Cerdas Menggunakan Perceptron Berdasarkan Prediksi Kedatangan Pemilik Brisma Meihar Arsandi; Triyogatama Wahyu Widodo; Faizah Faizah
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 7, No 1 (2017): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (741.367 KB) | DOI: 10.22146/ijeis.16840

Abstract

Arrival prediction system on smarthome is system that cam estimating time of home owner arrival on smarthome. Prediction system used to reference on smarthome system to preparing electronic devices so at home owner arrive, the devices are already to use. Prediction system made by divide distance of home owner location to home by driving velocity. Prediction also use neural network perceptron to determine travel condition are in traffic or not and correcting to predicting perform. Perceptron use last travel data as reference correction to prediction system. Based on testing on prediction system, accuracy of prediction system reach 74% to 79%. Accuracy reach these values due errors occurred while determining location so predicted route became not match with real condition. Errors occured by GPS usage not on outdoor area and smartphone GPS only detect 6 GPS satellite. Neural network perceptron differ of traffic condition on travel after fourth epoch, with weight value at 11.09 and bias value at 61. And perceptron can correcting prediction system after twelfth epoch with weight values at -0.2778 and 0.2924 also bias value at -0.05.
Penerapan Sistem Kendali XY-Stage dan Modulasi Laser Pada Tomografi Fotoakustik Menggunakan Arduino Gong Matua; Triyogatama Wahyu Widodo; Mitrayana Mitrayana
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 7, No 2 (2017): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (854.639 KB) | DOI: 10.22146/ijeis.18294

Abstract

 Photoacoustic tomography is a system of utilization of the photoacoustic effect is used to obtain image-processing with high resolution and contrast. The purpose of studies is to design a mechanics xy-stage and implement control systems in laser modulation. The system design consists of designing hardware and software. Hardware design includes the design of optical devices and the design of electronic devices using the Arduino microcontroller. Software design using Arduino IDE, Audacity and Matlab. Recording test results showed that the photoacoustic signal peaks on the recording with the samples was higher than the recording unsampled. Based on the test mileage xy-stage mechanical movement using a type of bipolar stepper motor Nema 17, earned mileage (4.046 ± 0.005) mm for the motor movement for one revolution and it takes 25 steps to obtain the distance as far (0.50 ± 0.05) mm used on scanning process. Image-processing has been able to show the results of the image corresponding to the scanning area, the process is carried out on the object-imaging soft tissues such as the pancreas with cell tumor tissue.
Deteksi Daging Sapi Menggunakan Electronic Nose Berbasis Bidirectional Associative Memory Eviyan Fajar Anggara; Triyogatama Wahyu Widodo; Danang Lelono
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 7, No 2 (2017): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (614.416 KB) | DOI: 10.22146/ijeis.25489

Abstract

E-nose is an instrument used to detect odor. E-nose developed with Bidirectional Associative memory (BAM) algorithm has advantages in processing incomplete input data and noise. The purpose of the study was to implement the BAM algorithm to detect pure beef among samples of beef, pork, and mixed meat from aroma with  e-nose.Data processing of the sample reading results begins by performing the baseline manipulation process, then do difference and integral feature extraction for the data. The characteristic extraction data will be converted into bipolar matrix patterns (1 and -1) so that the threshold data is needed to be able to determine the feature extraction data to be bipolar. Data that have become bipolar matrices will be used as test and reference data in the program with cross validation testing to obtain the percentage of truth of meat detection using BAM based e-nose.Detection of meat with BAM using integral feature extraction with bipolar the first way yields a 14,8% success percentage and the second way bipolar yields a 15,7% success rate. The extraction of characteristic difference with bipolar the first way yields a success percentage of 17,3% and the second way bipolar yields a success rate of 16,4%.
Implementasi Algoritma PSO Pada Multi Mobile Robot Dalam Penentuan Posisi Target Terdekat Ikhwannuary Raditya Priyadana; Bakhtiar Alldino Ardi Sumbodo; Triyogatama Wahyu Widodo
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 1 (2018): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (615.531 KB) | DOI: 10.22146/ijeis.25505

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.
Klasifikasi Teh Hijau dan Teh Hitam Tambi-Pagilaran dengan Metode Principal Component Analysis (PCA) Menggunakan E-Nose Inca Inca; Triyogatama Wahyu Widodo; Danang Lelono
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 1 (2018): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (378.474 KB) | DOI: 10.22146/ijeis.28718

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.
Sistem Konfigurasi Otomatis Pada Pengendalian Nirkabel Dengan Pendekatan Context-Aware Pada Rumah Pintar Dewinta Nila Hapsari; Triyogatama Wahyu Widodo
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 11, No 2 (2021): Oktober
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.57051

Abstract

A house consists of several rooms with electronic devices inside of it. Each device has a remote control or a button to control it. With technologies have been increasing rapidly, we can control home appliances easily with our Android smartphone. However, thiscan make user uncomfortable to control,  if all the devices appear simultaneously in one screen. Therefore,this project aims to develop an automatic configuration remote control system which adapts to the situation of the room to be controlled. Using Bluetooth technology in smartphone for transfering data. Usually to connect to a Bluetooth device,usermanually chooses one of the Bluetooth devicenames from the list that appears from the scan results. Therefore, the focus of this project is to develop a wireless control system that is capable of performing automatic configurationsthat suit the situation of the room. This system usesa localization method that utilizes the signal strength that Bluetooth receives or RSSI Bluetooth.The testing result of the system are able to perform automatic configuration where the system is automatically connected to the nearest room without the need for prior settings and adjust the control menu according to the situation of the room.
The Application of Music Therapy For Children with Autism Based On Facial Recognition Using Eigenface Method Hesti Khuzaimah Nurul Yusufiyah; Ilona Usuman; Agfianto Eko Putra; Triyogatama Wahyu Widodo
Journal of Natural Sciences and Mathematics Research Vol 3, No 1 (2017): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (801.747 KB) | DOI: 10.21580/jnsmr.2017.3.1.1695

Abstract

This research is motivated by the condition of children with autism who require continuous monitoring without a parent accompany, and certain therapies who is capable to reduce repetitive behaviors and increase the concentration. Music therapy is one of the treatment which able to perform it. The implementation of this research is located in a special schools with autism, the perform is proper at certain times and requires tools for music therapy. Therefore, the integrated device was made to monitor the activities of children with autism, as well as providing music therapy automatic face recognition based on Eigenface method.This device perform when the children with autism under certain conditions (e.g. crying, the teacher would not work orders, etc.), then by capturing the the facial image, the system will process to compare the similarity with the existing database. Then, the shortest distance of euclidean is chosen. If the captured of facial image is similar to the one existing database, then the music is performed as music therapy for children with autism. The results of this system, indicates that the child's responses become more calm, easy concentration, and the repetitive attitude is reduced. While the accuracy of the system achieves by 80% (compare with the old and new database) and 20%. (without new database). ©2017 JNSMR UIN Walisongo. All rights reserved.
Perancangan dan Pembuatan Data Acquisition Device Sebagai Sistem Akuisisi Data untuk Kendali Mobil Formula Student Leonard Fidelcristo Supit; Tri Wahyu supardi; Triyogatama Wahyu Widodo
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 13, No 1 (2023): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.83395

Abstract

Data Acquisition Device (DAQ) is an electronic component used in formula student vehicles. To optimize the performance of the formula student vehicle and its driver, it is necessary to analyze and monitor the data acquisition system. Parameters acquired on the car include the position of the brake pedal/throttole and wheel speed.DAQ system has 5 input channels namely 3 analog input pins and 2 digital input pins, and 3 output channels, which is the controller pin, fault pin, and brake light pin. The DAQ system in this research is designed and made using Teensy 3.6, a signal conditioning circuit consisting of an RC low pass filter, voltage follower, non-inverting amplifier, and logic level shifter. DAQ system uses CANBUS to read and process sensor data.             DAQ system can acquire data from the KTC Linear Motion Position sensor PZ-12-A-50P with an accuracy value of 99,91%; Hall-effect Rotary Position sensor RTY120LVNAX with an accuracy value of 99,94% for both the first and second sensors; and Proximity sensor LJ12A3-4-Z/BX with an accuracy value of 99,58% for the first sensor and 99,46% for the second sensor. DAQ is able to run controller signal processing, detect faults, and activate brake light signal according to FSAE rules.