Gamelan Music Onset Detection based on Spectral Features

This research detects onsets of percussive instruments by examining the performance on the sound signals of gamelan instruments as one of  traditional music instruments in Indonesia. Onset plays important role in determining musical rythmic structure, like beat, tempo, measure, and is highly required in many applications of music information retrieval. Four onset detection methods that employ spectral features, such as magnitude, phase, and the combination of both are compared in this paper. They are phase slope (PS), weighted phase deviation (WPD), spectral flux (SF), and rectified complex domain (RCD). Features are extracted by representing the sound signals into time-frequency domain using overlapped Short-time Fourier Transform (STFT) and by varying the window length. Onset detection functions are processed through peak-picking using dynamic threshold. The results showed that by using suitable window length and parameter setting of dynamic threshold, F-measure which is greater than 0.80 can be obtained for certain methods

Spectral-based Features Ranking for Gamelan Instruments Identification using Filter Techniques

 In this paper, we describe an approach of spectral-based features ranking for Javanese gamelan instruments identification using filter techniques. The model extracted spectral-based features set of the signal using Short Time Fourier Transform (STFT). The rank of the features was determined using the five algorithms; namely ReliefF, Chi-Squared, Information Gain, Gain Ratio, and Symmetric Uncertainty. Then, we tested the ranked features by cross validation using Support Vector Machine (SVM). The experiment showed that Gain Ratio algorithm gave the best result, it yielded accuracy of 98.93%

Health Behavior Associated with Quality of Life among Elderly with Hypertension

Background: The quality of life of elderly people has become increasingly important with the demographic shift to greying population. Quality of life is defined by personal feelings, details, outlook, and day to day experiences, which include how happy and positive one feels, how comfortable and secure, how productive and desired, how healthy and free an individual considers themselves, etc. This study aimed to determine health behavior associated with quality of life among elderly with hypertension. Subjects and Method: This was a cross sectional study conducted at Puskesmas (community health center) Rowosari, Semarang, Central Java. A sample of 62 elderly with hypertension was selected for this study by simple random sampling. The dependent variable was quality of life. The independent variables were adherence to treatment, physical exercise, diet, and smoking. Quality of life was measured by Short Form-36. Dietary pattern was measured by food recall. The other data were collected by questionnaire. The data were analyzed by chi square with prevalence ratio (PR) as the measure of association. Results: Adherence to treatment (PR= 10.27; CI 95%= 2.85 to 36.94; p<0.001), physical exercise (PR= 12.00; CI 95%= 2.26 to 63.86; p= 0.001), good diet (PR= 1.80; CI 95%= 1.40 to 2.34; p= 0.001), and smoking abstinence (PR= 3.36; CI 95%= 1.04 to 10.90; p= 0.038) were associated with better quality of life in elderly with hypertension. Conclusion: Adherence to treatment, physical exercise, good diet, and smoking abstinence are associated with good quality of life in elderly with hypertension

Model Analysis-by-synthesis Aplikasi Pembangkit Suara Gamelan Sintetik

Pengarsipan musik gamelan dalam bentuk digital pada jaman serba digital ini akan memudahkan penyebarandan pengenalan ke generasi muda. Pengarsipan dalam bentuk digital bisa dilakukan secara otomatis denganmemasukan notasi lagu yang tertulis di kertas ke dalam aplikasi pembangkit suara gamelan. Pembangkitansuara gamelan memerlukan beberapa parameter yaitu notasi atau balungan gendhing, jenis instrumen yangdigunakan, alat pemukul yang dipakai, teknik pemukulan, kekuatan pukulan, dan tempo lagu. Pada penelitianini hanya beberapa parameter yang diperhatikan; yaitu frekuensi dasar, frekuensi harmonisa, fase, tempo danjenis instrumen yang dimainkan. Jenis suara gamelan yang dibangkitkan adalah full synthetic dan semisynthetic. Pada penelitian yang menggunakan metode analysis-by-synthesis ini diperoleh bahwa untuk suarayang dihasilkan full synthetic masih belum memuaskan, terutama belum bisa menirukan suara dentingan khaslogam yang dipukul. Sedangkan suara gamelan yang dihasilkan secara semi synthetic memiliki kualitas yangsetara dengan suara gamelan yang dihasilkan oleh para penabuh gamelan

Effect of Child Growth and Development Training on The Knowledge and Attitude among Community Health Workers in Semarang, Central Java

Background: Measuring and monitoring a child’s growth is important to judge the adequacy of diets or supplementary food being given. Monitoring child's development is critical to find out if a child's development is on track. It is important to act early if there are signs of potential development delay because early treatment is so important for improving a child's skills and abilities. This study aimed to determine effect of child growth and development training on the know¬ledge and attitude among community health workers in Semarang, Central Java. Subjects and Method: This study was a quasi-experimental with pretest and posttest with no control design conducted at Rowosari Puskesmas (community health center), Semarang, Central Java. The study subjects involved 62 community health workers (CHWs). The dependent variables were knowledge and attitude about child growth and development. The independent variable was training on how to measure and monitor child growth and development. The data were collected by questionnaire, and analyzed by Wilcoxon test. Results:Knowledge was higher after training (Mean= 77; SD= 9.8) than before (Mean= 68; SD= 11.2), and it was statistically significant (p= 0.001). Attitude was higher after training (Mean= 80; SD= 12.8) than before (Mean= 70; SD= 10.1), and it was statistically significant (p= 0.001). Conclusion: Training is effective in improving knowledge and attitude about child growth and development monitoring among CHWs. Keywords: knowledge, attitude, growth,development, monitoring, children, community health workers

EpCare: Prototipe Sistem Detektor Pre-Iktal Pasien Epilepsi Berbasis Fitur CSI dari Sinyal EKG 1 Kanal Menggunakan AD8232

Kejang epilepsi dapat terjadi di sembarang waktu dan tempat, dan dalam kondisi tertentu dapat menyebabkan cedera fatal. Oleh karena itu, kebutuhan akan perangkat wearable yang dapat mengirimkan peringatan kepada pengguna akan kejang yang akan datang adalah penting. Perangkat ini harus dapat merasakan kelainan pada sinyal biomedis pengguna dan mengirimkan peringatan sebelum kejang. Penelitian ini mengembangkan sistem yang mendeteksi kondisi pre-iktal pasien epilepsi berdasarkan fitur Cardiac Sympathetic Index (CSI) dari sinyal Elektrokardiogram (EKG). Listrik jantung pasien diukur menggunakan 3 elektroda yang dihubungkan ke AD8232 untuk mewakili sinyal 1 kanal. Algoritma Pan-Tompkins diimplementasikan untuk mendapatkan interval RR dari sinyal EKG. Kemudian fitur CSI dihitung berdasarkan nilai RR-interval. Distribusi setiap 100 interval RR dijadikan sebagai dasar untuk menentukan nilai ambang batas CSI. Ketika nilai CSI melebihi ambang batas ini, sistem akan mengirimkan peringatan ke aplikasi seluler, yang disebut EpCare. Eksperimen dilakukan pada dua kelompok data, yaitu kelompok data primer dari non-penderita epilepsi dan kelompok data sekunder dari penderita epilepsi. F-measure dari eksperimen yang menggunakan ambang batas dari orang normal sebesar 0.64, sedangkan F-measures dari eksperimen yang menggunakan ambang batas individual penderita epilepsy sebesar 0.50. AbstractEpileptic seizures may occur at anytime and anywhere, and in certain conditions may lead to fatal injury. Therefore, the need for wearable device that can alert user to an impending seizure is important. This device should be able to sense abnormality in user’s biomedical signals and send alert prior to seizure. This research develops a system that detects pre-ictal condition of epilepsy patient based on Cardiac Sympathetic Index (CSI) feature from Electrocardiogram (ECG) signals. Patient’s heart electricity is measured using 3 electrodes which are connected to AD8232 to represent 1 channel signal. Pan-Tompkins algorithm is implemented to obtain RR intervals of ECG signals. Then, CSI feature is calculated based on the values of RR-intervals. A distribution of every 100 RR-intervals is made as basis to determine a threshold value of CSI. When CSI value exceeds this threshold, system will send alert to a mobile application, called EpCare. Experiments were conducted on two groups of data, which are primary one from non-epileptic persons, and secondary one from epileptic patients. F-measures of experiments used threshold of non-epileptic person is 0.64, while F-measures of experiments used individual threshold of epileptic person is 0.50.