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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) TELKOMNIKA (Telecommunication Computing Electronics and Control) JURNAL ELEKTRO ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika CogITo Smart Journal MITRA: Jurnal Pemberdayaan Masyarakat Jurnal Mantik Jurnal Pengabdian Masyarakat Charitas Metris: Jurnal Sains dan Teknologi Cylinder : Jurnal Ilmiah Teknik Mesin
Bachri, Karel Octavianus
Universitas Katolik Indonesia Atma Jaya
Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences

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Cognitive artificial-intelligence for doernenburg dissolved gas analysis interpretation Karel Octavianus Bachri; Umar Khayam; Bambang Anggoro Soedjarno; Arwin Datumaya Wahyudi Sumari; Adang Suwandi Ahmad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.11612

Abstract

This paper proposes Cognitive Artificial Intelligence (CAI) method for Dissolved Gas Analysis (DGA) interpretation adopting Doernenburg Ratio method. CAI works based on Knowledge Growing System (KGS) principle and is capable of growing its own knowledge. Data are collected from sensors, but they are not the information itself, and thus, data needs to be processed to extract information. Multiple information are then fused in order to obtain new information with Degree of Certainty (DoC). The new information is used to identify faults occurred at a single observation. The proposed method is tested using the previously published dataset and compared with Fuzzy Inference System (FIS) and Artificial Neural Network (ANN). Experiment shows CAI implementation on Doernenburg Ratio performs 115 out of 117 accurate identification, followed by Fuzzy Inference System 94.02% and ANN 78.6%. CAI works well even with small amount of data and does not require trainings.
SMART ROOM MONITORING MENGGUNAKAN MIT APP INVENTOR DENGAN KONEKSI BLUETOOTH Micha Thesania Katarine; Karel Octavianus Bachri
Jurnal Elektro Vol 13 No 1 (2020): Jurnal Elektro: April 2020
Publisher : Prodi Teknik Elektro, Fakultas Teknik Unika Atma Jaya Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/jurnalelektro.v13i1.1824

Abstract

This study aims to design a smart room monitoring system (smart room) to determine the condition of the room in the house. This smart room system is based on Bluetooth and is assisted by the MIT App Inventor application which can do remote monitoring. This system is controlled by the Arduino Mega microcontroller which is connected to the sensor and Bluetooth. The sensors used are MQ2 to detect gas leaks, LM35 to detect room temperature, and PIR sensors to detect human presence. The MQ2 Sensor is placed near the LPG gas canisters, the PIR sensor is placed at entrance, while the LM35 sensor is placed at the center of the room, with neither direct blow from the Air Conditioner nor direct exposure to sunlight. Experiment shows that the sensor and the system work, and the application can also be connected to the system so that the sensors are monitored. In the MIT App Inventor application, the data received from Bluetooth is a PIR sensor that detects the presence of people in the room, the LM35 sensor can detect room temperature, and the MQ2 sensor can detect the presence of leaking gas.
Analysis on the Cogging Torque of Permanent Magnet Machine for Wind Power Applications Tajuddin Nur; Linda Wijayanti; Anthon de Fretes; Karel Octavianus Bachri
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.v7.2082

Abstract

This paper discusses the new feature implemented in most social media messaging applications: the unsent feature, where the sender can delete the message he sent both in the sender and the recipient devices. This new feature poses a new challenge in mobile forensic, as it could potentially delete sent messages that can be used as evidence without the means to retrieve it. This paper aims to analyze how well Autopsy open-source mobile forensics tools in extracting and identifying the deleted messages, both that are sent or received. The device used in this paper is a Redmi Xiaomi Note 4, which has its userdata block extracted using linux command, and the application we’re using is WhatsApp. Autopsy will analyze the extracted image and see what information can be extracted from the unsent messages. From the result of our experiment, Autopsy is capable of obtaining substantial information, but due to how each vendor and mobile OS store files and databases differently, only WhatsApp data can be extracted from the device. And based on the WhatsApp data analysis, Autopsy is not capable of retrieving the deleted messages. However it can detect the traces of deleted data that is sent from the device. And using sqlite3 database browser, the author can find remnants of received deleted messages from the extracted files by Autopsy.
Design and Implementation of Piping Installation for Catfish Farming in Sampora Village Karel Octavianus Bachri; Sandra Octaviani; Marsul Siregar; Widodo Basuki; Tajuddin Nur; Christine Natalia
MITRA: Jurnal Pemberdayaan Masyarakat Vol 4 No 1 (2020): MITRA: Jurnal Pemberdayaan Masyarakat
Publisher : Institute for Research and Community Services

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/mitra.v4i1.1061

Abstract

Atma Jaya Catholic University of Indonesia has Faculty of Engineering, which is committed to empower its surrounding communities. This empowerment is implemented based on its core values. The present community empowerment activities have been planned through a series of agreements and the main goal of the activities is to develop the entrepreneurship based on the strength of the area. This paper discusses the assistance given by Faculty of Engineering in designing piping installation for supporting aquaponic activities in Desa Sampora. The project was divided into three steps. First, this project focused on observation and data collecting. This first step also involved discussion with experts. Second, it focused on the design process. The result of the first step was used in the design. Third, the design was implemented and installed in the location. All the steps required careful planning to minimize errors. The expected target of these activities was an aquaponic piping design that is feasible to implement to support sustainable and productive entrepreneurship. The final result was piping installation that can grow 120 plants, is easy to clean up, and has area efficiency.
Perbaikan Kurva Beban Harian pada Industri Kecil: Studi Kasus PT. X Soewono, Arka D.; Kelvin, Dimas; Bachri, Karel Octavianus
Jurnal Elektro Vol 17 No 1 (2024): Jurnal Elektro: April 2024
Publisher : Prodi Teknik Elektro, Fakultas Teknik Unika Atma Jaya Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/jurnalelektro.v17i1.5404

Abstract

This paper presents the improvement of daily load and load balance curve of home-scale garment industry with the study case in PT. X. Research is started with load measurement on every machine, proceeded by plotting schedule of each machine. The next step is rescheduling daily load and per-phase load balancing. Initial data shows unbalance load sharing between phase with the average load of 4916 kW and standard deviation of 2077. After being rescheduled and phase rearrangement, the interphase load sharing is more balance, with the average load of 4903 kW and standard deviation of 952.
Comparison of Actual Results and PVSyst Simulation in the Design of Off-Grid Solar Power Generation System (PLTS) in Karuni Village, Southwest Sumba Siregar, Marsul; Pardosi, Cristoni Hasiholan; Bachri, Karel Octavianus; Nur, Tajuddin; Pandjaitan, Lanny W.
Jurnal Elektro Vol 17 No 1 (2024): Jurnal Elektro: April 2024
Publisher : Prodi Teknik Elektro, Fakultas Teknik Unika Atma Jaya Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/jurnalelektro.v17i1.5419

Abstract

This research aims to compare the actual production with the simulations using the PVSyst software for the Off-Grid Solar Power Plant (PLTS) in Karuni Village, Southwest Sumba. The Off-Grid PLTS in Karuni Village is a vital solution for improving remote areas' electricity access. Actual energy production data from the PLTS were obtained from monitoring systems, while simulation results were obtained through PVSyst. The analysis results indicate a difference of approximately 10% between the actual and simulated results. It observed that it is influenced by variability in local weather conditions, maintenance, system management levels, and limitations of the simulation model. The implications of this research emphasize the importance of using accurate data in simulations, improving PLTS system maintenance, and developing more sophisticated simulation models. Recommendations for further research include further analysis of factors influencing the differences in results. This study provides valuable insights into the planning and management of Off-Grid PLTS. It offers perspectives on enhancing the accuracy of future PLTS system planning and management.
Rancang Bangun Fasilitas Cuci Tangan Pintar Untuk Lembaga Bimbingan Belajar Hikari Darmawan, Marten; Soewono, Arka Dwinanda; Hutagalung, Rory Anthony; Bachri, Karel Octavianus; Anthony , Jean; Setiawan, Axel Gilbert
Jurnal Pengabdian Masyarakat Charitas Vol. 3 No. 02 (2023): Jurnal Pengabdian Masyarakat Charitas Desember 2023
Publisher : Program Studi Teknik Industri, Fakultas Teknik, Universitas Katolik Indonesia Atma Jaya Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/charitas.v3i02.4965

Abstract

Indonesia is one of the countries affected by the COVID-19 pandemic. One of the most effective ways to prevent the spread of the COVID-19 virus is by regularly washing hands with soap for 20 seconds. With the pandemic conditions improving and the government lifting COVID restrictions, learning institutions can continue learning activities with the requirement that they obey strict health protocols. One of the private tutoring institutions in Tangerang that has resumed operations is Hikari Private Tutoring. With many people using the same facilities for educational activities, Hikari Private Tutoring is required to provide facilities for washing hands. Based on the inputs from Hikari Private Tutoring management, a touchless hand-washing facility was designed to minimize COVID-19 transmission. The hand washing facility also has an LCD to play videos of correct hand washing procedures and show how long the user has washed their hands. At the end of this activity, the manager and staff of Hikari Private Tutoring were asked to fill out a questionnaire. The results showed that they were satisfied with the functionality of the touchless hand-washing facilities. This hand-washing facility can hopefully help educate the public, particularly the staff and students of Private Tutoring, on the correct technique to wash their hands and prevent the spread of COVID-19.
Survey Paper: Optimization and Monitoring of Kubernetes Cluster using Various Approaches Hadikusuma, Ridwan Satrio; Lukas; Karel Octavianus Bachri
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12424

Abstract

This research compares different methods for optimizing and monitoring Kubernetes clusters. Three referenced journals are analyzed: "Kubernetes cluster optimization using hybrid shared-state scheduling framework" by Oana-Mihaela Ungureanu, Călin Vlădeanu, Robert Kooij; "Monitoring Kubernetes Clusters Using Prometheus and Grafana" by Salma Rachman Dira, Muhammad Arif Fadhly Ridha; and "Cluster Frameworks for Efficient Scheduling and Resource Allocation in Data Center Networks: A Survey" by Kun Wang, Qihua Zhou, Song Guo, and Jiangtao Luo. These journals explore various approaches to optimizing and monitoring Kubernetes clusters. This review concludes that selecting appropriate technologies for optimizing and monitoring Kubernetes clusters can enhance performance and resource management efficiency in data centre networks. The research addresses the problem of improving Kubernetes cluster performance through optimization and efficient monitoring. The required methods include utilizing hybrid state-sharing scheduling frameworks, implementing Prometheus and Grafana for monitoring, and employing efficient cluster frameworks. The study's findings demonstrate that adopting a hybrid shared-state scheduling framework can improve Kubernetes cluster performance. Additionally, leveraging Prometheus and Grafana as monitoring tools offer valuable insights into cluster health and performance. The survey also reveals various cluster frameworks that enable efficient scheduling and resource allocation in data centre networks. In conclusion, this research emphasizes the significance of employing suitable technologies to optimize and monitor Kubernetes clusters, leading to enhanced performance and efficient resource management in data centre networks. By leveraging appropriate scheduling frameworks and monitoring tools, organizations can optimize their utilization of Kubernetes clusters and ensure efficient resource allocation
Student Organization Website with E-Voting Feature by Using Student Card Verification Concept Design Paskalis, Yohanes Maria Jonathan Glenn; Bachri, Karel Octavianus
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13734

Abstract

Student organizations hold an election to decide their next head and vice head every year. The best voting method for student organizations is to use an independent website with a voting system. The voting system can use students’ identity card and their student email as base for verification. OCR and face detection can be used for extracting all the needed information to validate the student card and verify it with the corresponding student email input. Other than the voting system, the website can be used to promote the student organization itself. The website was built using Nuxt for its front-end, Firebase for its back-end, and Cloud Vision API for its OCR and face detection module. There is a Lighthouse test, a stress test for the voting system, and a test to determine the optimal file size for the voting system. The results are a website that has an average Lighthouse score of 97.58. The stress test, which used a script that does submission repeatedly, results suggest that the voting system can handle up to 2000 voters at the same time. The optimal file size determined by the authors to be 500KB as the result of its test. The conclusions are a great performing website with a voting system can be built using Nuxt and Firebase, the voting system can be improved by adding another step of verification, and it’s best to use and image with a file size above 250KB when using Cloud Vision API for optimal results
Heart Sound Processing for Early Diagnostic of Heart Abnormalities using Support Vector Machine Paschalis, Sebastian Michael; Hutapea, Duma Kristina Yanti; Bachri, Karel Octavianus
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 8 No. 1 (2024)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v8i1.1031

Abstract

This paper addresses the critical issue of cardiovascular disease (CVD), the leading cause of global mortality, emphasizing the imperative for effective and early detection to mitigate CVD-related deaths. The research problem underscores the urgency of developing advanced diagnostic tools to identify heart abnormalities promptly. The primary objective is to create a Support Vector Machine (SVM) algorithm for accurate classification of different heart conditions, namely Normal heart, Mitral Stenosis, and Mitral Regurgitation. To achieve this objective, the study utilizes a dataset of heart sounds available online using a 10-fold cross-validation method. The focus is on evaluating the efficacy of various kernel functions within the SVM framework for heart sound classification. The findings demonstrate that the linear kernel exhibits superior accuracy and robustness in effectively classifying heart conditions. Notably, the proposed classification method attains an impressive 96% accuracy, highlighting its potential as a reliable tool for early detection of cardiovascular diseases. This research contributes to the ongoing efforts to enhance diagnostic capabilities and ultimately reduce the global burden of CVD-related fatalities.
Co-Authors Adang Suwandi Ahmad Alexander, Justin Alvinson, Gregorius Anthon de Fretes, Anthon de Fretes Anthony , Jean Arwin Datumaya Wahyudi Sumari Bachtiar, Marsellinus Bambang Anggoro Soedjarno Bunardi, Marcelinus Eric Catherine Olivia Sereati Christine Natalia Duma Kristina Yanti Enny Widawati Fernanto, Nico Fortino, Antonius Edwin Hadikusuma, Ridwan Satrio Herianto, David Jonathan, Edoardo Karangga, Yusaphat Phosa Kartadinata, Budi Kelvin, Dimas Kevin Kevin kevin Khayam, Umar Kusmanto, Willy Lestari, Hesti Tri Lukas Maria Angela Kartawidjaja Marsellinus Bachtiar Wahju Marten Darmawan Melisa Mulyadi Micha Thesania Katarine Michael Deni Perdana Putera Nabil, Alfi Nova Eka Budiyanta Nur, Tajuddin Osmond, Edbert Pandjaitan, Lanny W. PANJAITAN, LANNY Pardosi, Cristoni Hasiholan Paschalis, Sebastian Michael Paskalis, Yohanes Maria Jonathan Glenn PRAWIRA, WASKITO Putera, Michael Deni Perdana PUTRA, SADIANA Rizki Surya Permana Rory Anthony Hutagalung Sachi, Haenuki Sandra Octaviani Sandra Octaviani Satryanatha, Josaphat Febrian Setiawan, Axel Gilbert Siregar, Marsul Soewono, Arka Soewono, Arka D. Soewono, Arka Dwinanda Sutomo, Febryan Tajuddin Nur Theresia Ghozali Trifenaus Prabu Hidayat Veronica Windha Mahyastuty Wahju, Marsellinus Bachtiar Widodo Basuki Wijaya, Nickolas Dario Wijaya, Toby Wijayanti, Linda Wilson