Sri Arttini Dwi Prasetyawati
Universitas Islam Sultan Agung

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Aplikasi Mikroprosesor Tipe TMS320C6713 Untuk Penghapusan BisingSuara Kendaraan Secara Adaptif Dwi Prasetyowati, Sri Arttini; Arifin, Bustanul; Budi Susila, Eka Nuryanto
PROSIDING CSGTEIS 2013 CSGTEIS 2013
Publisher : PROSIDING CSGTEIS 2013

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Abstract

Abstrak- Bising kendaraan, adalah permasalahan yang sangat mngganggu bagi lingkungan yang dekat dengan lalulintas ramai. Solusi yang dikehendaki bukan berupa ruang kedap suara, namun ruang yang bebas dari bising kendaraan namun tetap mendengar suara yang dikehendaki. Penelitian ini meneruskan penelitian yang melakukan eksplorasi penghapusan bising kendaraan dengan menggunakan algoritma LMS (Least Mean Square) Adaptif, dimana dalam penelitian tersebut telah ditemukan nilai-nilai optimal dengan menggunakan dua tingkat proses. Penelitian ini membuat suatu model dalam bentuk hardware untuk menghapus bising kendaraan, tanpa harus kehilangan informasi yang diinginkan.Hardware yang digunakan adalah DSP (Digital Signal Processor) tipe TMS320C6713.Kata kunci: LMS adaptif, DSP tipe TMS320C6713, bising kendaraan
ARTIFICIAL NEURAL NETWORK FOR HEALTHY CHICKEN MEAT IDENTIFICATION Yumono, Fajar; Subroto, Imam Much Ibnu; Prasetyowati, Sri Arttini Dwi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (366.322 KB) | DOI: 10.11591/ijai.v7.i1.pp63-70

Abstract

Indonesia is the country with the largest number of Muslims in the world. Every Muslim is taught to consume thoyyiban halal meat or healthy chicken because it is slaughtered in the right way and stored in a good way too. But the reality in the market of many chicken meat on the market can not meet that criteria. Identification of healthy chicken meat can be done with laboratory experiments, but that is not simple and takes time. This experiment offers a cheaper, faster approach, with very high accuracy. The experimental approach is based on color and texture analysis on 5 types of meat quality based on healthy value. Color analysis was performed using artificail neural network (ANN) while texture analysis used Canny edge detection. Experimental results show that the color histogram approach with ANN is better than the texture approach, ie 94% versus 66%. It can be concluded that the freshness of a chicken does not have much effect on the texture of the meat but it has an effect on the color change in the meat.
MULTIPLE PROCESSES FOR LEAST MEAN SQUARE ADAPTIVE ALGORITHM ON ROADWAY NOISE CANCELLING Prasetyowati, Sri Arttini Dwi; Susanto, Adhi
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 2: April 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (295.179 KB) | DOI: 10.11591/ijece.v5i2.pp355-360

Abstract

Noise is a problem often found in daily life. Noise also make people could not concentrate to do their work. Efforts to reduce noise have been proposed, but, due to variety of the noise?s characteristics, every noise problem requires different solution. This research aim to cancel  the vehicle?s noise while maintaining the information heard. These conditions happened in the hospitals classrooms, or work room near the roadway. The vehicle?s noise change very fast, so the adaptive system is the good solution candidate for solving this problem. On the beginning, the simulation process had the trouble with the iterations. Matlab software only can execute the certain range of iteration. It could not cancel the noise, even the information becomes criptic. The problem is how to cancell the vehicle?s noise with the restriction software and still manage the important information. This research will modify the LMS adaptive algorithm so that the iteration could be done by the system and the main goal of the research could be reached. The modification of the algorithm is based on the filter length (L) used to adapt with the noise. Therefore, this research conducted simulation of the Adaptive Noise Cancelling with two process steps. The output of the first adaptive process have the.same characteristics with the noise that would be cancelled, thus the first adaptive process have the error near to zero.  The second adaptive process changes the input by the output of the first process and mix the information into the noise. Error occured in the final process is the information heard as the dominant output.
PERBANDINGAN ALGORITMA FLOODFILL DAN DJIKSTRA’S PADA MAZE MAPPING UNTUK ROBOT LINE FOLLOWER Utomo, Ary Sulistyo; Dwi Prasetyowati, Sri Arttini; Arifin, Bustanul
Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Vol 1, No 1 (2015): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI 6 2015
Publisher : Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik

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Abstract

Robot line follower (RLF) adalah robot yang dapat berjalan mengikuti suatu maze yang berupa garis secara otomatis.RLF dapat digunakan untuk aplikasi mengantarkan barang dari suatu tempat awal ketempat tujuan dengan tepat dan akurat. Untuk menyelesaikan permasalahan tersebut dibutuhkan suatu algoritma yang digunakan untuk mencari jalur terpendek. Pada penelitian ini digunakan dua algoritma yaitu algoritma djikstra’s dan floodfill. Pengujian dilakukan dengan cara menjalankan RLF dari titik start menuju ketitik finish dan sebaliknya dengan jalur terpendek. Input RLF untuk menyusuri garis berupa photodiode berjumlah 8 buah diproses dalam mikrokontroler Atmega16 untuk mengendalikan 2 buah motor. Area yang digunakan berukuran 200 x 200 cm mempunyai tebal garis lintasan  2cm dengan jarak terdekat pada setiap simpangnya adalah 40 cm.. Warna garis adalah putih dan background berwarna hitam.Hasil penelitian menunjukkan bahwa kestabilan RLF menyusuri garis lintasan dicapai pada nilai pengaturan PIDKp=45, Ki=10 dan KD=100. Dengan pengaturan nilai tersebut masing-masing algoritma menghasilkan jarak terdekat yang sama karena maze yang digunakan sama. Tetapi proses pencarian titik finish dengan algoritma floodfill lebih cepat dibandingkan menggunakan algoritma djikstra’s. Dengan algoritma floodfill,waktu pencarian titik finish lebih cepat dan jarak tempuh lebihdekat.Persentase rata-rata efisiensi waktu floodfill terhadap djikstra’s senilai  52,65 %. Kata kunci: robot line follower, kendali PID, djikstra’s, floodfill, maze mapping
Investigation of Diesel’s Residual Noise on Predictive Vehicles Noise Cancelling using LMS Adaptive Algorithm Dwi Prasetyowati, Sri Arttini; Susanto, Adhi; Widihastuti, Ida
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 3: EECSI 2016
Publisher : IAES Indonesia Section

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Abstract

Every noise problems require different solution. In this research, the noise that must be cancelled comes from roadway. Least Mean Square (LMS) adaptive is one of the algorithm that can be used to cancel that noise. Residual noise always appears and could not be erased completely. This research aims to know the characteristic of residual noise from vehicle’s noise and analysis so that it is no longer appearing as a problem. LMS algorithm was used to predict the vehicle’s noise and minimize the error. The distribution of the residual noise could be observed to determine the specificity of the residual noise. The statistic of the residual noise close to normal distribution with = 0,0435, = 1,13 and the autocorrelation of the residual noise forming impulse. As a conclusion the residual noise is insignificant.
Cosine Similarity Measurement for Indonesian Publication Recommender System D, Darso; Subroto, Imam Much Ibnu; Sri Arttini Dwi, Prasetyowati
Journal of Telematics and Informatics Vol 5, No 2: September 2017
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (604.037 KB) | DOI: 10.12928/jti.v5i2.

Abstract

So many publications are increasing every year and it causes an overflow of data and it makes the information function on the site cannot be delivered entirely to the visitors. As a scientific publication site, the IPI garuda portal (Index of Indonesian publications) has more than 4000 Indonesian journals in the database. Therefore it will be designed a system that can provide information and knowledge for the user. The system can also provide recommendations related articles and relevant for users. Recommendations are made by calculating similarities between related documents. The similarity calculation method used in this research was cosine similarity. The steps taken were pre-processed, weight calculation, vector length and then they were calculated using cosine similarity so that the value would be achieved that ranged from 0 to 1. Performance testing of recommendation system used precision and recall. Performance system with average precision value about 0.664 meant that the document had good system accuracy, and then the average recall point with value about 0.962 meant that documents were successfully returned by the system.
EMG SIGNAL RECOGNITION OF GAIT PATTERN USING BACK PROPAGATION NEURAL NETWORK FOR STROKE DISEASE REHABILITATION Arie WK, Diah; Prasetyowati, Sri Arttini Dwi; Marwanto, Arief
Journal of Telematics and Informatics Vol 6, No 2: June 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v6i2.

Abstract

Electromyography (EMG) is the electrical activity obtained from muscles activity. Gait pattern of leg muscles will be measured and recognized by EMG signals. The EMG signal on the leg muscles is measured by six electrodes which are filtered with 0.33Hz high pass filter (HPF) and a low pass filter (LPF) for anti aliasing. Maximum frequency of EMG is 600 Hz, that sampled perfectly by Analog to Digital Converter (ADC) using 2 KHz. Artificial Neural Networks (ANN) algorithm is applied to obtain the accuracy and optimization of EMG signal. The performance of the results are investigates based on two type of human condition, first is healthy person and second is severe person. The combination of EMG measurements with ANN has gives better results compares than without an ANN model. The results showed that the measurement for healthy individuals during normal walking conditions was 4.56 volts with a frequency of 0,00582Hz; the measurement of stroke patients which walking at normal speed is 8.80 volts and the frequency is 1,231Hz. Therefore, proposed prototype that combined using ANN algorithm has increased capability of  measurement of EMG signal for normal and severe humans models. Keywords : EMG, ANN, Gait
OPTIMIZING GROUP DISCUSSION GENERATION USING K-MEANS CLUSTERING AND FAIR DISTRIBUTION Wardhana, Alfano Endra; Subroto, Imam Much Ibnu; Prasetyowati, Sri Arttini Dwi
Journal of Telematics and Informatics Vol 6, No 2: June 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v6i2.

Abstract

The development of computer-based learning system today can provide a different learning process in a teaching and learning process, but the problems faced by a teacher is the difficulty in grouping discussion group that has a different value of knowledge and skills, because usually this selection of discussion groups in e-learning is done based on the wishes of each student or randomly regardless of the data of knowledge and skills. This research was conducted with the aim of grouping the discussion groups based on the indicators of knowledge and skill by using k-means clustering analysis at SMK Sore Tulungagung. The knowledge and skills scores of class X students in Pekerjaan Dasar Elektromekanik subjects, The Competence of Electricity Installation Engineering will be used as the basic scores. Then, the students of class X were divided into 2 groups, namely the k-means based group and the random based group for further research. The mean score of knowledge and skills are before the learning process and after the results of the evaluation of the discussion group on the k-means based and the random based group. The k-means based class score increases 4,083 from the average. Before the learning, it was 83.292 and it becomes 87.375 after the evaluation, while the random based class only experienced an increase 0,083 from the average. Before the learning it was 81,250 and it becomes 81,333 after the learning evaluation. Based on the result, grouping the discussion group in a fair way in e-learning on the indicators of knowledge and skills using k-means clustering method shows more visible improvement, so k-means clustering is a more optimal method.
Emittance Quality of Terrestrial Digital Multimedia Broadcasting (TDMB) Prasetyowati, Sri Arttini Dwi; ., Gunawan; Budiyono, Aries
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 1: EECSI 2014
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1091.294 KB) | DOI: 10.11591/eecsi.1.387

Abstract

Television terrestrial broadcasting technology, even fix or mobile have a rapid development along with the development of digital technology. Many countries decided to move from analog TV broadcasting to digital TV broadcasting. Sultan Agung Islamic University (UNISSULA), one of the private university in Central Java had begun to develop the Terrestrial Digital Multimedia Broadcasting (TDMB), as a research to support the migration from analog TV broadcasting to digital TV broadcasting. Because of that goal, must be observed the range of the scope by testing the TDMB Transmitter in UNISSULA. The tool of the test is drive test measurements by Purposive Random Sampling on the three research area, there are, the main road in Semarang, eastern part of the transmitter, Southern part of the transmitter. The Measurement is limited to strength and quality signal.
IAES International Conference on Electrical Engineering, Computer Science and Informatics Riyadi, Munawar A; Dwi Prasetyowati, Sri Arttini; Sutikno, Tole; Stiawan, Deris
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 3: EECSI 2016
Publisher : IAES Indonesia Section

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Abstract

The 3rd International Conference of Electrical Engineering, Computer Science and Informatics (EECSI) 2016 was held in Semarang, Indonesia from 23th to 25thNovember, 2016. The conference was organized by Universitas Islam Sultan Agung as the host in collaboration with Universitas Diponegoro, Universitas Ahmad Dahlan and Universitas Sriwijaya, and with full technical support from IAES Indonesia Section. Authors and participants from 10 countries made the conference truly international in scope. Participants have delivered their talks of valuable research outputs that vary from many fields of electrical engineering (power electronics, telecommunication, electronics engineering, control system and signal processing) to the field of computer science and informatics. These wide range of topics have colorized this conference.This volume of IOP Conference Series: Materials Science and Engineering contains selected articles from those presented in the conference. After presentation, the revised papers were peer reviewed by fellow reviewers to ensure the quality of published materials. Finally, Editors decided to select and publish as many as 49 papers. It is hoped that the presented papers can offer more insight towards broad audience.On behalf of Editors, we appreciate enormous work of all staffs and reviewers in the preparation of this volume. We would like to express our sincere thanks to all authors and presenters for their valuable contributions. We hope to see you again in the next event of EECSI 2017 which will be held in Yogyakarta, Indonesia, next year.