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All Journal POSITRON Jurnal Sains Dasar Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA

Agustika, Dyah Kurniawati

Jurusan Pendidikan Fisika, Fakultas MIPA, Universitas Negeri Yogyakarta

Author-ID : 2977224

Computer Science & IT Education Electrical & Electronics Engineering Energy Physics

Published : 8 Documents Claim Missing Document

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Articles

FREQUENCY COMPONENT EXTRACTION OF HEARTBEAT CUES WITH SHORT TIME FOURIER TRANSFORM (STFT) Sumarna, Sumarna; Purwanto, Agus; Agustika, Dyah Kurniawati
Jurnal Sains Dasar Vol 5, No 1 (2016): April 2016
Publisher : Faculty of Mathematics and Natural Science, Universitas Negeri Yogyakarta

Abstract Electro-acoustic human heartbeat detector have been made with the main parts : (a) stetoscope (piece chest), (b) mic condenser, (c) transistor amplifier, and (d) cues analysis program with MATLAB. The frequency components that contained in heartbeat. cues have also been extracted with Short Time Fourier Transform (STFT) from 9 volunteers. The results of the analysis showed that heart rate appeared in every cue frequency spectrum with their harmony. The steps of the research were including detector instrument design, test and instrument repair, cues heartbeat recording with Sound Forge 10 program and stored in wav file ; cues breaking at the start and the end, and extraction/cues analysis using MATLAB. The MATLAB program included filter (bandpass filter with bandwidth between 0.01 – 110 Hz), cues breaking with hamming window and every part was calculated using Fourier Transform (STFT mechanism) and the result were shown in frequency spectrum graph. Keywords: frequency components extraction, heartbeat cues, Short Time Fourier Transform

THE METHOD OF BASELINE MANIPULATION TO OVERCOME THE SENSOR DRIFT ON GAS SENSOR TEST FOR HERBAL DRINKS DISCRIMINATION Dyah Kurniawati Agustika; Kuwat Triyana
Jurnal Sains Dasar Vol 5, No 1 (2016): April 2016
Publisher : Faculty of Mathematics and Natural Science, Universitas Negeri Yogyakarta

Abstract Gas sensor system is widely used for the detection of aroma. The main problem in this system is the sensor drift that makes poor reproducibility of the sensor. The reproducibility of the sensor can be improved by applying the feature selection of the sensor’s output response and baseline manipulation. This research focused on determining methods that can reduce the dift sensor of gas sensor by using basaeline manipulation and selecting the optimal type of baseline manipulation when gas sensor system detects three different types of herbal drinks. The data that have been feature selected were then applied to three different types of baseline manipulation (differential, relative and fractional) and inserted into the pattern recognition system, Principal Component Analysis (PCA). From the analysis of PCA baseline manipulation that gives optimal results is differential one with the value of PC1 82.71%. This shows that differential baseline manipulation is effective in reducing the occurrence of sensor drift. Keywords: electronic nose, gas sensor, baseline manipulation, feature selection

The Improvement of Phonocardiograph Signal (PCG) Representation Through the Electronic Stethoscope Sumarna Sumarna; Juli Astono; Agus Purwanto; Dyah Kurniawati Agustika
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

A conventional stethoscope (an acoustic stethoscope) is an acoustic medical device that is always used for preliminary examination of patients with any heart abnormalities. The main disadvantage of acoustic stethoscope is its dependence on how to use it and the experience of the examining physician. This paper presents a simple electronic stethoscope design in Phonocardiograph system that is free from subjectivity of doctors or other medical personnel. This electronic stethoscope is made sensitive in order to capture as many acoustic signal as possible from the activities of the human body, especially the heart and lungs. The design of this electronic stethoscope consists of chest piece, a pipe with proper acoustic impedance, mic condenser, mic preamp, and battery. The output of the mic preamp is connected to the mic channel on the laptop. The recording signal then processed separately. The repeatability of output signal was investigated in this paper. The signal was analyzed by using the Fast Fourier Transform (FFT). The result showed that the frequency responsea of the output signals are consistent, hence the instrument is reliable. Furthermore, the frequency response of the system with filter that connecting chest piece and mic condensor were also investigated.

Steady-state response feature extraction optimization to enhance electronic nose performance Dyah Kurniawati Agustika; Shidiq Hidayat; Kuwat Triyana; Doina D Iliescu; Mark S Leeson
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2050

Feature extraction of electronic nose (e-nose) output response aims to reduce information redundancy so that the e-nose performance can be improved. The use of different sensor types and sample targets can affect the optimization of feature extraction. This research used six types of metal oxide sensors, TGS 813, 822, 825, 826, 2620, and 2611 in an e-nose system to detect three types of herbal drink. Five kinds of feature extraction methods on the original response curve in a steady-state response were used, namely, baseline difference, logarithmic difference, local normalization, global normalization, and global autoscaling. The results of feature extraction were fed into a Principal Component Analysis (PCA) system. As a result, global autoscaling and normalization had the highest total sum of the first and second principal components of 96.96%, followed by local normalization (90.18%), logarithm, and baseline difference (88.92% and 79.26%, respectively). The validation of PCA results was performed using a Backpropagation Neural Network (BPNN). The highest accuracy, 97.44%, was obtained from the global autoscaling method, followed by global normalization, local normalization, logarithm, and baseline difference, with an accuracy level of 94.87%, 92.31%, 89.74%, and 82.05%, respectively. This demonstrates that the selection of the feature extraction method can affect the classification results and improve e-nose performance.

Pelatihan Biosand Filter Untuk Mengangani Masalah Kesadahan (Kadar Kapur) Dalam Air Minum Bagi Masyarakat Kelurahan Giritontro, Kabupaten Wonogiri Juli Astono; Sumarna Sumarna; Dyah Kurniawati Agustika; Anggiyani Ratnaningtyas Eka Nugraheni; Dina Dina
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol 1, No 2 (2017)
Publisher : Yogyakarta State University

Sesuai dengan Peraturan Menteri Kesehatan RI No. 492/Menkes/Per/IV/2010 tentang Persyaratan Kualitas Air Minum, kesadahan dalam air layak minum tidak dapat lebih dari nilai baku mutu sebesar 500 mg/l. Tingginya kadar kapur didaerah Wonogiri yang dapat menyebabkan terganggunya kesehatan menimbulkan kesadaran masyarakat untuk mengolah air minum. Oleh karenanya dilakukan program pengabdian kepada masyarakat (PPM) di daerah kelurahan Giritontro, Kabupaten Wonogiri yang bertujuan mengangani masalah kesadahan (kadar kapur) dalam air minum dengan menggunakan Biosand Filter. Pada PPM ini, diperoleh hasil bahwa teknologi Biosand Filter dapat mengurangi tingkat kesadahan hingga 78%.

Pelatihan Penerapan Magnetic Generator Sebagai Sumber Energi Alternatif Bagi Masyarakat Kelurahan Giritontro, Kabupaten Wonogiri Sumarna Sumarna; Juli Astono; , Agus Purwanto; Nur Kadarisman; Dyah Kurniawati Agustika
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol 1, No 2 (2017)
Publisher : Yogyakarta State University

Terbatasnya energi sumber daya mineral mempengaruhi ketersediaan listrik di berbagai pelosok Indonesia. Untuk mengatasi permasalahan ini, kelompok Pengabdian Kepada Masyarakat (PPM) kami membuat program pelatihan sumber energi listrik alternatif bagi masyarakat di daerah Kelurahan Girotontro, Kabupaten Wonogiri. Sumber energi listrik alternatif yang dibuat menggunakan akumulator sebagai penyedia daya d.c terhubung ke inverter sebagai pengubah transmisi d.c. ke a.c sehingga dapat menyalakan lampu. Masyarakat sangat antusias dalam mengikuti pelatihan dan juga dalam mencoba membuat sumber energi listrik alternatif karena dapat menjawab permasalahan listrik yang ada di daerah mereka.

Penyuluhan Alat Deteksi Kesadahan Dalam Air Berbasis Light Dependent Resistor Di Kelurahan Giritontro, Kecamatan Giritontro, Kabupaten Wonogiri Sumarna Sumarna; Dyah Kurniawati Agustika; Agus Purwanto; Nur Kadarisman; Anggiyani Ratnaningtyas Eka Nugraheni; Dina Dina
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol 2, No 2 (2018): Vol 2, No 2 (2018)
Publisher : Yogyakarta State University

Beberapa daerah di Wonogiri memiliki tanah yang mengandung kapur, sementara itu sebagian masyarakat mengonsumsi air yang berasal dari dalam tanah. Pada kegiatan pengabdian kepada masyarakat tahun 2016 ditemukan permasalahan dalam masyarakat di kelurahan Wonogiri yaitu sulitnya mendeteksi adanya kapur dalam air yang mereka konsumsi. Sebagai akibatnya banyak masyarakat yang menderita penyakit dalam yang diakibatkan pengendapan kapur di dalam tubuh mereka seperti penyakit ginjal. Oleh karenanya, tim PPM Fakultas MIPA Universitas Negeri Yogyakarta membangun sistem pendeteksi adanya kapur dalam cairan berbasis Light Emitting Diode (LED) dan Light Dependent Resistor (LDR). LED digunakan untuk menyinari cairan dengan kadar kapur yang berbeda-beda, kemudian LDR akan mendeteksi cahaya LED yang melewati cairan tersebut. Besar kecilnya nilai luaran LDR akan bergantung kadar kapur dalam cairan. Masyarakat sangat antusias dan mulai menggunakan alat ini untuk mendeteksi adanya kapur di air yang mereka konsumsi. Kata kunci: Kesadahan, LDR, LED Workshop On Detector of Water Hardness Based On Light Dependet Resistor In Giritontro Village, Giritontro District, Wonogiri RegencyAbstract Some areas in Wonogiri contain hardness in its soil, while some people consume water that come from the soil. In community service activity in 2016, we found problems in the community in Giritontro, Wonogiri that is the difficulties to detect the hardness in the water that people consume. As a result, many people who suffer from internal diseases caused by the deposition of lime in their bodies such as kidney disease. Therefore, the PPM team of the Faculty of Mathematics and Natural Sciences of Yogyakarta State University built a hardness detection system in liquid based Light Emitting Diode (LED) and Light Dependent Resistor (LDR). LEDs are used to irradiate fluids with different lime levels, then LDR will detect the LED light passing through the liquid. The size of the LDR output value will depend on the lime content in the liquid. People are very enthusiastic and start using this tool to detect the presence of limestone in the water they consume. Keywords: Hardness, LDR, LED

Automatic Recognition of Pelung and Canary Bird Sounds Using Machine Learning and Signal Enhancement Agustika, Dyah Kurniawati; Kadarisman, Nur; Sumarna, Sumarna; Purwanto, Agus
POSITRON Vol 15, No 1 (2025): Vol. 15 No. 1 Edition
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Univetsitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/positron.v15i1.93137

Bird sound classification is a valuable tool in ecological monitoring and species identification, particularly for non-invasive assessment in natural environments. However, challenges such as limited labeled data and environmental noise often reduce the reliability of classification models. This study presents a lightweight bird sound classification pipeline that integrates signal preprocessing, audio augmentation, and machine learning to address these issues. Two bird species with distinct vocal characteristics, Pelung (a crossbreed involving Bangkok chickens) and Canary (Serinus canaria), were used as case subjects. A total of 40 original 2-second audio clips were extracted from longer field recordings, then processed through frame-based energy attenuation, bandpass filtering (1"“8 kHz), and RMS normalization. Ten augmentation techniques were applied to each original file to improve generalization, generating 400 augmented files for model training. Feature extraction was performed using 13-dimensional Mel Frequency Cepstral Coefficients (MFCCs), and Principal Component Analysis (PCA) was used to visualize the effect of filtering. Classification was conducted using a Support Vector Machine (SVM) with a radial basis function (RBF) kernel. Results showed that filtering improved classification accuracy from 90% to 95% on the original data. Furthermore, using only augmented data for training and original data for testing yielded 100% classification accuracy, demonstrating excellent generalization. This study highlights the effectiveness of combining adaptive preprocessing and augmentation for reliable bird sound classification under limited and noisy conditions.

Co-Authors , Agus Purwanto AGUS PURWANTO Anggiyani Ratnaningtyas Eka Nugraheni Dina Dina Dina Dina Doina D Iliescu Juli Astono Juli Astono Kuwat Triyana Kuwat Triyana Mark S Leeson Nur Kadarisman Purwanto, Agus Shidiq Hidayat Sumarna Sumarna Sumarna Sumarna Sumarna Sumarna

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