ABSTRAKData World Health Organization (WHO) pada tahun 2014 menunjukkan bahwa di Indonesia sebanyak 37% dari seluruh penyebab kematian adalah penyakit yang berhubungan dengan jantung. Kehadiran teknologi dan pemanfaatan Internet of Things (IoT) diharapkan dapat membantu mengurangi resiko kematian akibat penyakit jantung tersebut. Pada penelitian ini, pengukuran dan pengamatan sinyal jantung melalui tele-auskultasi sinyal elektrokardiogram (EKG) dilakukan. Untuk mengamankan sinyal EKG dalam proses transmisi melalui jaringan Internet digunakan metode anonimasi sinyal berbasis algoritma Jusak-Seedahmed. Hasil pengujian menunjukkkan bahwa algoritma Jusak-Seedahmed dapat melakukan proses anonimasi dan proses rekonstruksi sinyal dengan baik. Pengujian korelasi silang antara sinyal hasil rekonstruksi dan sinyal EKG asli sebelum anonimasi menghasilkan korelasi sebesar 1 pada lag=0. Sinyal EKG hasil rekonstruksi ditampilkan dalam aplikasi mobile untuk memudahkan analisis oleh dokter.Kata kunci: elektrokardiogram, keamanan, anonimasi, IoT, FFT ABSTRACTBased on the latest data released by the World Health Organization in 2014, deaths caused by cardiovascular disease in 2012 have reached 37% of the total number of non-communicable diseases deaths in Indonesia. Therefore, it is expected that the applications of the Internet of Things (IoT) might be used to reduce the risk of death due to the heart related problems. In this research, a tele-auscultation technique for measuring and monitoring electrocardiogram (ECG) signal was built. To secure transmission of the ECG signal over the Internet, we implemented a recently proposed Jusak-Seedahmed algorithm. Our examinations showed that the algorithm performed the anonymization and reconstruction processes well. Crosscorrelation analysis showed that correlation between the reconstructed and the original ECG signal at lag=0 was 1. Furthermore, a mobile-based application had been built to display the reconstructed ECG signal for further analysis.Keywords: electrocardiogram, security, anonimization, IoT, FFT