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All Journal ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JTERA (Jurnal Teknologi Rekayasa) Eksakta : Berkala Ilmiah Bidang MIPA TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Teknologi Terpadu Jurnal Fisika Indonesia Jurnal Ilmu dan Inovasi Fisika
Nendi Suhendi Syafei
Department Of Physics, Faculty Of Mathematics And Natural Sciences, Universitas Padjadjaran, Bandung, Indonesia
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics

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Hybrid Machine Learning Model untuk memprediksi Penyakit Jantung dengan Metode Logistic Regression dan Random Forest Al Azhima, Silmi Ath Thahirah; Darmawan, Dwicky; Arief Hakim, Nurul Fahmi; Kustiawan, Iwan; Al Qibtiya, Mariya; Syafei, Nendi Suhendi
Jurnal Teknologi Terpadu Vol 8 No 1: Juli, 2022
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v8i1.539

Abstract

The heart is the main organ that must work properly and regularly. If there is interference, it will be fatal, namely the onset of a heart attack. Heart attack is included in the 10 diseases with a high risk of death. This is caused by stress factors, blood pressure, excessive work, blood sugar, and others. The purpose of this study is to predict heart disease using Machine Learning (ML) algorithms as an early preventive measure on desktop-based information systems. With Machine Learning models, the hybrid model can increase the accuracy value of an ML method that is added to other ML methods. The accuracy value obtained from the Hybrid Model Machine Learning using the Random Forest and Logistic Regression methods is 84.48%, which is an increase of 1.32%.  
Prototype of Portable Heart Monitoring System using BITalino SITOMPUL, ERWIN; SUHARTOMO, ANTONIUS; DARMAWAN, FARHAN; SYAFEI, NENDI SUHENDI; TURNIP, ARJON
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 11, No 1: Published January 2023
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v11i1.31

Abstract

ABSTRAKJantung adalah organ vital yang menuntut perhatian khusus, terutama untuk orang dengan resiko serangan jantung. Bagi orang kategori ini, diperlukan detektor detak jantung yang bekerja secara kontinu dan real-time yang dapat mendeteksi adanya gangguan jantung secara dini. Pada penelitian ini, penulis mengajukan prototipe sistem monitoring jantung portable (PSMJP) dengan menggunakan modul bio-signal BITalino. Hasil pengukuran diproses pada perangkat komputer yang terhubung dengan BITalino melalui transmisi Bluetooth. Suatu program pemroses sinyal dirancang dengan menggunakan Algorithma Hamilton. Tingkat keberhasilan deteksi pada pengujian terhadap sampel EKG mentah dan pengukuran EKG mentah adalah 100%. PSMJP diujikan kepada 15 naracoba untuk kondisi duduk dan kondisi berjalan. PSMJP berfungsi baik pada 29 dari 30 pengukuran, dimana sinyal elektrik dari jantung terbukti dapat diproses dan memberikan hasil akhir berupa fitur-fitur gelombang detak jantung dan laju detak jantung.Kata kunci: denyut jantung, algoritma Hamilton, BITalino, EKG ABSTRACTThe heart is a vital organ that requires special attention, especially for people with heart attack risk. For people of this category, a heart rate detector that works continuously and in real-time is needed so that heart problems can be detected. In this study, the authors proposed a prototype of a portable heart monitoring system (PPHMS) using the BITalino bio-signal module. The measurement results are processed on a computer device connected to BITalino via Bluetooth transmission. A signal processing program was designed using Hamilton Algorithm. The detection success rate on testing for a raw ECG sample and raw ECG measurement was 100 %. PPHMS was tested on 15 subjects for sitting conditions and walking conditions. PPHMS works well in 29 of the 30 measurements, where electrical signals from the heart are proven to be successfully processed. The final results in the form of heart wave features and heart rate can be provided.Keywords: heart rate, Hamilton Algorithm, BITalino, ECG
Pendeteksi Pelanggaran Lalu Lintas Kendaraan Lawan Arah berbasis Sensor Ultrasonik HIDAYAT, DARMAWAN; NAUFAL, FADHIL BOMA; SYAFEI, NENDI SUHENDI
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 10, No 4: Published October 2022
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v10i4.798

Abstract

ABSTRAKPelanggaran lalu lintas lawan arah kendaraan sepeda motor adalah pelanggaran yang banyak terjadi. Hal ini kerap menimbulkan korban. Makalah ini melaporkan prototipe sensor untuk deteksi pelanggaran lalu lintas lawan arah kendaraan sepeda motor di area lalu lintas Universitas Padjadjaran (Jatinangor) untuk keperluan pengelola dalam pengaturan lalu lintas kampus. Sistem sensor dibangun dari dua buah sensor ultrasonik (MB1030 MaxSonar EZ-3) untuk membaca arah pergerakan kendaraan. Sensor kendaraan mendeteksi pola spasial dan temporal gerakan kendaraan yang melintas. Pola pembacaan sensor ultrasonik diproses oleh mikrokontroller ATmega 328P dan hasilnya ditampilkan pada peraga LCD dan peraga buzzer. Data yang ditampilkan berupa jumlah pelanggaran lawan arah dan indikasi bunyi. Berdasarkan hasil pengujian, sistem dapat mendeteksi pelanggaran lawan arah sebesar 87,14%. Sistem ini juga dapat membedakan objek yang melintas antara kendaraan motor dengan pejalan kaki. Secara keseluruhan, sistem yang dibangun berfungsi sesuai rancangan untuk mendeteksi pelanggaran kendaraan sepeda motor lawan arah.Kata kunci: lawan arah, ultrasonik, kirim-pantul, spasial-temporal, mikrokontroler ABSTRACTOpposite direction traffic violations are the most occurrences of traffic violations. This often causes fatal human injuries. This paper reports a design of sensor for detection of opposite direction traffic violations of motorcycle vehicles in the internal traffic area of Universitas Padjadjaran, Jatinangor campus, for in-campus traffic management purposes. The sensor system is built from two ultrasonic sensors (MB1030 MaxSonar EZ-3) to detect the direction of vehicle object movement. The sensors detect the direction according to the spatial and temporal patterns. The ultrasonic sensor reading pattern is processed by the ATmega 328P microcontroller and the results are displayed on an LCD and a sound buzzer. The displayed parameter is the number of opposite directioan violation and a beep sound. Based on the testing results, the system can detect a violation of the opposite direction by 87.14%. This system enables to distinguish motor vehicles and pedestrians objects. In conclusion, the system functions as designed to detect violations of motorcycle in the opposite direction.Keywords: traffic violation, ultrasonic sensors, pulse-echo, spatial-temporal, microcontroller
Reliability Study of Oil and Gas Pipelines Using the Normal Distribution Method Suhendi Syafei, Nendi; Hidayat, Darmawan; Rohadi, Nanang; Joebaedi, Khafsah; Supriyana, Eddy
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 22 No. 1 (2021): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (827.147 KB) | DOI: 10.24036/eksakta/vol22-iss1/246

Abstract

Gas and oil pipelines have decreased function and damaged due to corrosion. This research aims to analyze and predict the life of gas and oil pipelines within a certain time span. The method used is a reliability study using a normal distribution. The analysis results show it is predicted that the pipe reliability probability in 2030 will decrease and the probability of failure will increase. The probability of reliability is 0.843572786617270 and the probability of failure is 0.156427213382730 in 2030. With the long distance pipeline, maximum depth as shown in the attachment the average thick remain is 0.2200 inches, the average corrotion rate is 0.0317 mm/year, with prediction thick remain from 2000 to 2030 in inches.
Co-Authors Agus Supriatna Al Azhima, Silmi Ath Thahirah Al Qibtiya, Mariya Antonius Suhartomo Arif Choerudin Suanda Arjon Turnip Badrulfalah Badrulfalah Bambang Mukti Wibawa Bambang Mukti Wibawa Bambang Mukti Wibawa Bernard Y. Tumbelaka Bernard Y. Tumbelaka Bernard Y. Tumbelaka DARMAWAN HIDAYAT Darmawan Hidayat, Darmawan Darmawan, Dwicky Darmawan, Farhan Dwicky Darmawan Eddy Supriyana Emilliano Emilliano Erwin Sitompul Fauzi Akhmad Febi Luthfiani Ikhsan Nurdianis Ismail, Taofik Iwan Kustiawan Kankan Parmikanti Khafsah Joebaedi Liu Kin Men Mariya Al Qibtiya Meutia Rahmatika Nanang Rohadi, Nanang NAUFAL, FADHIL BOMA Nurdianis, Ikhsan Nurul Fahmi Arief Hakim Otong Nurhilal S S Rizki Setianto Setianto Setianto Setianto, Setianto Silmi Ath Thahirah Al Azhima Sri Suyaningsih Suanda, Arif Choerudin Suryaningsih Suryaningsih Taofik Ismail Tumbelaka, Bernard Y. Wibawa, Bambang Mukti