One of the abnormalities in the heart that can be assessed from an ECG signal is premature ventricle contraction (PVC). PVC is a form of arrhythmia in the form of irregularity in beat ECG signals. In this study, a multilevel wavelet entropy method was developed to distinguish PVC and normal ECG signals automatically. Data was taken from the MIT-BIH arrhythmia database with the process carried out is normalization, median filtering, beat-parsing, MWE calculation and classification using SVM. The results of the experiment showed that MWE level 5 with DB2 as mother wavelet and Quadratic SVM as classifier resulted in the highest accuracy of 94.9%. MWE level 5 means only five features needed for classification. The number of features is very little compared to previous research with a quite high accuracy.

Authentication and Identification is primary part of biometric technology. Currently, electrocardiogram (ECG) is not only being used as a diagnostic tool for clinical purposes, but also as a new biometric tool for high level security system because of its liveliness and uniqueness that is hard to imitate and manipulate. There are many fiducial (signal mark) that is classified from ECG morphology (QRS Complex, P, T waves) has already been researched for this purpose. For non fiducial, many researches are focus on dynamic character from heartbeat (ECG Signal). Heart Rate Variability (HRV) analysis is part of non fiducial classifier. This paper reviews Heart Rate Variability analysis (time and frequency domain) as part of multi matches, one of scenario from multimodal biometric. Sample of person’s heartbeat signal is taken from ECG Database MIT-BIH (MIT and Harvard) and the result of every parameter will be analyzed by Biometric Performance Standards Tools (ISO/IEC IS 19795-1) such as: False Non-Match Rate (FNMR), False Match Rate (FMR) and Thresholds EER (Equal Error Rate). Analysis should show accuracy of multi matches Heart Rate Variability (HRV). As integrator tool, LabView is used to collect offline ECG, process the data and generate HRV Analysis.

The cadmium (Cd (II)) detection sensor consists of working electrode, counter electrode and reference electrode made with thick film technology on sensitive material-based carbon electrodes (G/N/IL/SPCE) and coated with Bismuth film. Carbon (C) paste, Ag | AgCl is used as working electrode, counter electrode and reference electrode material on alumina substrate by screen printing. The working electrode was doped with Graphene (G), Nafion (N) and Ionic liquid (IL). Furthermore, Bismuth-Film (BiF) is coated with electrodeposition on the surface of the working electrode. Electrode characterization with SEM is conducted to see the morphology of sensitive materials. It showed that the particles were distributed evenly on the surface of the electrode with spherical particles. Analysis using EDS shows the element’s atomic composition is C 91.57%, N 3.48%, O 3.23%, Bi 0.01%. The performance of the cadmium sensor was tested with a potentiostat in a standard Cd solution with a concentration of 0.005 mgL-1 – 1 mgL-1 indicating an average output voltage range of 10.36 volts - 10.37 volts. This can be explained that the sensor can detect Cd (II) content properly according to performance.

Disaster has been a part of our life. It comes unexpectedly, whenever and wherever that is. Because of the uncertainty, we have to care and Parepare ourselves to face it. Indonesia as an archipelago has a high risk of disaster, especially flood, particularly in Jakarta. It happened regularly every year. It also happens in other cities in Indonesia.Water scarcity in dry season and flood in rainy season become center of attention and influence us in many aspects of life. This study focus on on Prevention and Earl warning system. Online realtime information system is developer to get the data to be analized. The method is to capture the amount of rainwater volume in a watershed (Watershed), to calculate the amount of water as a contributor to flood / overflow of river water.The solution is to use the absorption well as one of the ways to prevent flood disaster, to get the optimal value as a flooding solution, the formula of hydrological formula and rainfall analysis data have been captured by realtime and online-based monitoring tools.In order to get accurat result, fuzzy method is used on matlabstools.Key words: floods, weather station ,zero run off, DASABSTRAKBencana sudah menjadi bagian dari kehidupan manusia yang datang tanpa diduga, dimana dan kapan saja terjadinya. Karena ketidak pastian tersebut , kita harus peduli dan menyiapkan diri untuk menghadapi bencana. Indonesia sebagai negara kepulauan yang rawan bencana terutama bencana banjir, dan ini menjadi seperti rutinitas setiap tahun terjadinya musibah banjir. Selain di Jakarta di daerah lain Indonesiapun terjadi bencana seperti ini bahkan seluruh dunia mengalami masalah bencana banjir ini, bahkan sampai memakan korban.Kelangkaan air pada musim kemarau dan Banjir pada musim Hujan menjadi fokus perhatian dari sebagian masyarakat dan tanpa terasa berimbas pada hampir seluruh lapisan masyarakat. Sehingga peneliti juga sangat menekankan pada kedua bencana ini, dimana pada umumnya semua pihak berfokus pada peringatan dini bencana; terutama berfokus pada penanganan bencana banjir. Pada tulisan ini peneliti melakukan sesuatu hal yang berbeda dimana konsepnya adalah pencegahan agar bencana banjir berkurang atau seperti kondisi bumi sebelumnya dimana pada wilayah tersebut tidak terjadi bencana banjir.Metode yang dilakukan adalah dengan menangkap jumlah volume air hujan pada suatu DAS (Daerah Aliran Sungai), untuk dihitung berapa jumlah air sebagai penyumbang banjir/ meluapnya air sungai. Untuk itu dibutuhkan suatu sistem informasi berbasis realtime dan online agar mendapatkan data untuk dianalisa sebanyak mungkin.Solusi yang dilakukan adalah menggunakan sumur resapan sebagai salah satu cara pencegahan bencana banjir, untuk mendapatkan nilai yang optimal sebagai solusi banjir maka dilakukan rumus rumus hidrologi serta data-data analisa curah hujan yang sudah ditangkap oleh perangkat monitoring realtime dan berbasis online, agar hasil perhitungan menjadi cukup akurat digunakan metode fuzzy pada tools matlabs.Kata Kunci : Banjir, Bencana Banjir,weather station,zero run off,DAS

Electro Cardyogram (ECG) is signal that produced by Medical Equipment named Electrocardyograph. Reading and Intepretation of ECG Record used manually by Paramedics as a main tool to diagnose heart abnormality and other disfunction internal body part. ECG Analyzer is digitally reading ECG by electronic. When applied with signal processing and Expert System, it will get accureate reading and intepretationn For ECG Electronic signal processing (such as ECG Analyzer), need Noise-Free ECG Signal. For this purpose, Denoising Filter as pre conditioning signal processing strongly recommend.Purpose of this paper is to get denoising filter (Transfer Function and Electronic Circuit). This Result can be integrated with ECG Analyzer in the future. Approach for denoising filter design in this paper using Butterworth Approximation (s-domain). To get ideal coefficient of Denoising Filter, this paper used Particle Swarm Optimization (PSO) as Optimization iteration. Matlab used for Filter Design and Optimization. Proteus applied for Electronic Circuit Simulation. ECG Offline Data tested as sample input to see the response. As a result, already got Transfer Function and Electronic Circuit Prototype as per ECG Free-Noise requirement.Keywords : Electro Cardio Gram (ECG), Denoising Filter, Analog Filter, Particle Swarm OptimizationABSTRAKSinyal ECG (Electro Cardiogram) adalah sinyal yang dihasilkan Peralatan Medis yang bernama Electrocardyograph. Bacaan dan Intepretasi record ECG secara manual, digunakan sebagai alat bantu utama paramedis dalam mendiagnosa ketidaknormalan jantung dan organ tubuh yang lain. ECG Analyzer adalah digitalisasi bacaan ECG secara elektronik. Dimana melalui pengolahan sinyal (Signal processing) dan Algoritma Expert System, nantinya akan didapat intepretasi bacaan yang akurat. Untuk analisa bacaan sinyal ECG secara elektronik (ECG Analyzer), diperlukan sinyal ECG yang bebas derau (noise). Untuk keperluan itu, diperlukan blok denoising filter yang merupakan pre-conditioning sinyal elektronik.Tujuan riset ini adalah untuk mendapatkan denoising filter berupa Transfer Function dan rangkaian elektronik teroptimasi. Yang bisa digunakan selanjutnya untuk pengintegrasian dengan ECG Analyzer. Pendekatan untuk desain denoising filter ini adalah Aproksimasi Analog (Butterworth Approximation). Sedang untuk optimasi (mendapatkan koefisien koefisien filter ideal) digunakan algoritma optimasi Particle Swarm Optimization (PSO). Digunakan Matlab untuk desain dan optimasi Denoising Filter dan Proteus untuk simulasi electronic circuitnya. Data ECG Offline diujikan sebagai sample input. Dari desain dan optimasi akhir telah didapat Transfer Function dan prototype rangkaian elektronika analog yang bebas noise dan siap untuk diintegrasikan dengan ECG Analyzer baik secara analog maupun digital nantinyaKata kunci: Electro Cardio Gram (ECG), Filter Denoising, Filter Analog, Optimasi Penyebaran Partikel