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Implementasi Kalman Filter Pada Kendali Roket EDF Wisnu Pamungkas; Bakhtiar Alldino Ardi Sumbodo; Catur Atmaji
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 7, No 1 (2017): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

EDF (electric ducted fan) rocket is a flying object shapes like bullet with electric ducted fan motor as the booster. This rocket fly autonomously by utilizing accelerometer, gyroscop, and magnetometer sensor to determine the attitude of the rocket against the earth’s gravitational and magnetic field of the earth. In controlling the rocket required a control system capable of controlling a rocket with sensor data that has been processed into the value of the attitude that has been filtered.In this study, designed a filter that will be implemented on the microcontroller rocket. The filters are Kalman filter is implemented while the control used is the control proportional integral derivative (PID) with Ziegler-Nichols tuning method.The result of this research is an implementation of kalman filter to EDF rocket control system. Based on the experiment that has been done, control system using a Kalman filter has a standard deviation value against the value of linear regression on a roll attitude of 2.73, a pitch of 3.03, and yaw of 6.96 degrees. While the standard deviation of the ideal value on a roll attitude of 3.43, a pitch of 2.92 and yaw of 5.21 degrees.

Sistem Kendali Gimbal 2-Sumbu Sebagai Tempat Kamera Pada Quadrotor Menggunakan PID Fuzzy M Saiful Haris; Andi Dharmawan; Catur Atmaji
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 7, No 2 (2017): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

The function of camera gimbal control system that use in this research is to serves with the angle changes that occur due quadrotor maneuver. The PID control with tuning classical method has weakness, which is the PID variable not independently adjust to the environment, thus proposed using PID fuzzy control.Gimbal camera used in this study has a mechanical design with two joint (pitch and roll) and the BLDC motor as actuator. The angle changes that occur in the pitch and roll axis will be a feedback system. Then, fuzzy logic will tune the PID variable based on that feedback.Results of testing the system on 2-axis gimbal camera shows the PID fuzzy control generates better response in parameter risetime, overshoot, and settlingtime compared with PID control. Error input value range of [-30° 30°] and delta error of [-10° 10°] on the pitch and roll axes. The range of the output value for the pitch axis is, Kp at [40.2 46.2], Ki at [10.7 20.7], and Kd of [0.05 to 0.15]. The range of the output value for the roll axis is, Kp at [6.4 16.4], Ki at [17.3 to 27.3], and Kd at [0.08 0.16]. Speed response speed of pitch axis is 0.12 second and the roll axis is 1.07 seconds.

Peningkatan Skalabilitas Mini Weather Station Portable berbasis Internet of Things Nur Achmad Sulistyo Putro; Catur Atmaji; Kristiawan Devianto; Zandy Yudha Perwira
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 9, No 2 (2019): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Indonesia is a country that has unique weather that provides not only abundant natural resources but also can causes disasters at any time. To reduce the threat of losses, observing weather elements using a weather station is a solution that can be used. The development of systems related to environmental monitoring and weather stations is not new. However, most research focuses on various innovations in utilization, low cost and power savings. These studies have not touched on the aspect of ease of system development, especially in the concept of adding nodes. Indonesia, as a country with diverse regional topography, needs an integrated weather monitoring system with the concept of centralized data collection to get a complete picture.In this study, a portable mini weather station system was built named Amicagama. This system is built with the concept of high scalability which means the system is designed to be used publicly, with each user able to manage the nodes which are their respective weather stations. Management by each user here means that each user can manage weather data to be submitted, add nodes at a new location, and can delete nodes at a certain location if something unexpected happens.

Deteksi Kesalahan Pengucapan Huruf Jawa Carakan dengan Jaringan Syaraf Tiruan Perambatan Balik JK Aditya Christya Buditama; Catur Atmaji; Agfianto Eko Putra
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.53437

Javanese is an Indonesian culture which needs to be preserved, but many Javanese students make mistakes in the pronunciation of Javanese letters and find it difficult to analyze errors by human teachers because of the limited time and subjective assessment, so a system is needed to detect incorrect pronunciation of Javanese letters. Mispronunciation detection system has been widely applied in foreign languages, but the system has not been implemented for Javanese carakan letters. This research develops the Javanese letters mispronunciation detection system using Back-Propagation Artificial Neural Networks (BP-ANN). The dataset is obtained from the recorded pronunciation of hanacaraka texts by 24 speakers with 5 repetitions. ALNS method then used to automatically segment the signal into syllables. ANN-PB use statistical value of Mel-Frequency Cepstral Coefficient (MFCC) method with 7 and 14 coefficients. 10-Fold Cross Validation is used to validate and test the system. The Javanese mispronunciation detection using 7MFCC coefficients produces the highest accuracy of 80,07%. While the Javanese mispronunciation detection using 14 MFCC coefficients produces an accuracy of 82.36% at the highest.

Klasifikasi Gerakan Jari Tangan Berdasarkan Sinyal Electromyogram Pada Lengan Catur Atmaji; Yusuf Waraqa Santoso; Roghib Muhammad Hujja; Andi Dharmawan; Danang Lelono
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 11, No 1 (2021): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.60741

An electromyogram is a recording of muscle activity. These signals have been used both for medical diagnosis and engineering such as finger motion detection in healthy people and rehabilitation patients. Many studies have been conducted to map the relationship between electromyogram and finger movements, one of which is the relationship between the number of channels used and the complexity of the system. The number of channels used is directly proportional to the complexity of a system. The more complex the system, the heavier the data processing is so that it requires greater resources. Therefore, this study focuses on the construction of a classification system for human finger movements using fewer channels. The number of channels used in this study is 4. Root Mean Square is applied in a sliding window as feature extraction. The classifier used is the artificial neural network. System validation is done with 10-fold cross-validation. The test results of the average accuracy value for the thumb, index finger, middle finger, ring finger, little finger, grip, and relaxation were 89%, 90%, 93%, 95%, 93%, 94%, and 91% respectively which can be said to be quite good considering the number of channels relatively few compared to previous studies.

Klasifikasi Suara Paru-Paru Berdasarkan Ciri MFCC Dody Rafiqo; Yohanes Suyanto; Catur Atmaji
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.70813

The lungs are an important organ in the human respiratory system, which functions to exchange carbon dioxide from the blood with oxygen in the air. Detection of respiratory disorders and lung disorders can be done in various ways; view medical records, physical examination, detection by x-ray and also auscultation of breathing. Digital signal processing can be used as a method to detect lung disorders based on the sound produced. In this study, lung sounds were classified into normal, crackle, wheeze, and crackle-wheeze classes using the Mel Frequency Cepstral Coefficient (MFCC) and Convolutional Neural Network (CNN) methods.Observations were made by varying the MFCC feature extraction using MFCC 8 and 13 coefficients, the number of frames are 50 and 60, and the width of the frames used was 0,1, 0,15 and 0,2 seconds. The result of feature extraction is then applied to the CNN classification system, and the confusion matrix is used to get the accuracy and precision values. The highest accuracy and precision values were obtained at 71,85% and 65,70% on the MFCC 13 coefficient with an average of 71,18%. Based on these results, the system that has been created can classify normal lung sounds, crackle, wheeze and crackle-wheeze quite well.

Pemodelan Harmonik untuk Pelafalan Makhraj Huruf Hijaiah Muhammad Fadhlullah; Catur Atmaji
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.71664

Learning to pronounce hijaiah letters needs to be assessed objectively, so it is necessary to form digital audio resulting from the synthesis of Harmonic Plus Residual (HPR) modeling, which conducted with two pronunciation methods, taskin and tasydid. The experiment consists data acquisition, signal cutting, framing and windowing, detection of fundamental and harmonic frequencies, synthesis of HPR, to produce synthetic signals. The results of the synthetic signals then analyzed qualitatively by signal spectrogram analysis and scoring.From the experimental results, it can be concluded that this study was ultimately unable to determine the best HPR parameters, but concluded that the tasydid method was the best method for learning pronunciation and for the HPR model synthesis. This is because the tasydid method with different parameters but all of them can produce good synthetic signal, both in terms of comparative analysis of similar signal spectrograms and from the results of scoring with an average value of 10. On the other hand, the taskin method harf shows unsatisfactory results, where the synthetic sound is mostly just noise, so the scoring results is under 9, and is reinforced by the results of the spectrogram comparison between the original and synthetic signals which visually different.

Implementasi Sintesis Suara Saron Menggunakan Petikan Senar Gitar Dengan Metode Pitch Shifting Andreas Febrillianto Primawan; Yohannes Suyanto; Catur Atmaji
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.80818

Â Gamelan is traditional Indonesian musical instruments that is often used in traditional events and parties.The community's need for the gamelan has actually increased, but unfortunately the price of gamelan is very expensive and the gamelan itself is difficult to move from one place to another place. Besides that, the limited tones that can be played by gamelan reduce the level of public interest in playing this instrument. Current technological developments make it possible to perform voice synthesis with several methods. One method that can be used is pitch shifting.This study aims to generate a synthetic saron sound based on plucking a guitar string. Analysis of the saron sound signal in the frequency domain is carried out to obtain the semitone values needed in the synthesis process. Synthetic saron signal generation is done by calling synthetic saron sounds that are stored in soundfont form, with reference data in the form of high and low pitch obtained from the guitar input pitch detection. Onset detection of guitar strokes is used as the initial trigger for calling out synthetic saron tones. The test was carried out by looking for similarities between the sound data of the original saron and synthetic saron using the cross-correlation method. The test results obtained a similarity accuracy rate of 91.6%. On the results of testing the guitar strum signal with the generation output, the average delay time for each strum is 0.152 seconds. From the results obtained, the system is classified as fast and accurate enough to be implemented in everyday life.

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