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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) Techno.Com: Jurnal Teknologi Informasi JREC (Journal of Electrical and Electronics) CCIT (Creative Communication and Innovative Technology) Journal Buletin Ilmiah Sarjana Teknik Elektro Journal Sensi: Strategic of Education in Information System Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Indonesian Journal of Electrical Engineering and Computer Science Jurnal Abdimas ADPI Sains dan Teknologi Journal of Integrated and Advanced Engineering (JIAE) Journal of Informatics and Communication Technology (JICT) NEAR: Jurnal Pengabdian kepada Masyarakat Journal of Informatics and Communication Technology (JICT)
Freddy Artadima Silaban
Universitas Mercu Buana
Humanities Astronomy Automotive Engineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Nursing Public Health Social Sciences Transportation Other

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Design of Condition Based Monitoring on Traction Transformers Using the Fuzzy Mamdani Method Reimondika, Fegi Arga; Silaban, Freddy Artadima
Journal Sensi: Strategic of Education in Information System Vol 10 No 2 (2024): Journal Sensi
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sensi.v10i2.3472

Abstract

Condition Based Monitoring Real-Time, direct supervision of machine condition parameters to detect potential changes, focuses on nitrogen gas pressure and oil temperature of the traction transformer at ASEAN Station, using the Fuzzy Mamdani method. This method notifies the traction transformer's condition and activates fans, providing information to operators. Arduino Uno R3 functions as a receiver and processor of sensor values. These values are processed using Fuzzy Mamdani, sent to ESP8266, and displayed on localhost. Percentage errors for nitrogen gas pressure (3.7%) and temperature (1.55%) result in a total percentage of 5.25%. The Fuzzy Mamdani output is 771.53 with a percentage error of 0.0019%, compared to MATLAB 2023b testing results of 773. Real-time monitoring shows the traction transformer is in good condition, with additional control to maintain its condition and improve reliability.
Neural Network Based Smart Irrigation System with Edge Computing Control for Optimizing Water Use Silaban, Freddy Artadima; Firdausi, Ahmad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 4 (2024): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i4.11965

Abstract

Efficient irrigation is critical in agriculture, particularly in regions with erratic rainfall. As global water scarcity intensifies, optimizing irrigation processes is essential to ensure sustainable food production. This study proposes a novel smart irrigation system leveraging neural networks and edge computing to enhance water use efficiency and crop yields. The dataset comprises environmental variables, including pH, water level, temperature, and humidity, sourced from reputable open repositories. Preprocessing steps included handling anomalies, encoding categorical variables, and feature standardization. A neural network with optimized architecture was trained using 70% of the data, validated with 15%, and tested on the remaining 15%. The system achieved a testing accuracy of 91.33%, with precision, recall, F1-score, and AUC metrics exceeding industry benchmarks (AUC: Base = 0.99, Ideal = 0.97, Dry = 0.98). The model was deployed on an NVIDIA Jetson Nano using Docker, demonstrating real-time prediction capabilities with minimal latency. The smart irrigation system automates water pump operations based on soil conditions, providing practical benefits such as reduced water waste and improved crop health. With its adaptable design and scalability, this system represents a step forward in sustainable agriculture, contributing to global efforts to address food security challenges.
Analisa Perbaikan Jatuh Tegangan Dan Rugi Daya Penyulang Distribusi Menggunakan ETAP Astuti, Iklimadani Sheviana; Silaban, Freddy Artadima
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 11 No 1 (2025): Journal CERITA : Creative Education of Research in Information Technology and Ar
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cerita.v11i1.3371

Abstract

Susut energi adalah energi hilang dalam proses distribusi aliran listrik. Susut energi di PLN UID Jakarta Raya meningkat 4.7% atau 106.11 GWh dari tahun 2021 ke 2022, yang merupakan kenaikan terbesar kedua unit Jawa Bali di PT. PLN (Persero) setelah UID Jawa Timur dengan susut 140.54 GWh, UID Jawa Tengah dan DIY sebesar 65.19 GWh, UID Banten sebesar 64.53 GWh dan UID Jawa Barat sebesar 33.89 GWh. Faktor utama susut energi adalah rugi daya, yang membutuhkan analisis parameter beban dan tegangan. Penelitian ini menganalisa kondisi penyulang distribusi dengan beban besar dan panjang, yaitu penyulang Sigap, dengan menggunakan Load Flow Analysis pada aplikasi ETAP. Tujuannya untuk menampilkan rugi daya dan tegangan jatuh pada kondisi eksisting penyulang, maupun setelah rekonfigurasi sebagai solusi perbaikan. Hasil simulasi menunjukkan kondisi eksisting tegangan ujung penyulang turun sebanyak 5,7% dari tegangan pelayanan dengan rugi daya 337.886 kW. SPLN No.72 Tahun 1987 memperbolehkan turun tegangan maksimal sebesar 5 %. Simulasi rencana rekonfigurasi menunjukkan bahwa rencana 1 berhasil memperbaiki tegangan ujung dari 18,87 kV menjadi 19,258 kV dan mengurangi rugi daya sebesar 84.9628 kW. Sedangkan rencana 2 berhasil memperbaiki tegangan ujung menjadi 19.82 kV dan rugi daya berkurang 195.6461 kW yang menjadikannya solusi perbaikan yang paling efektif untuk memperbaiki tegangan dan rugi daya.
Neural Network Approach Using PyTorch to Predict the Growth of Various Types of Plants Silaban, Freddy Artadima; Firdausi, Ahmad
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 2 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i2.3884

Abstract

In the era of rapid technological advancement, agriculture faces increasing challenges in optimizing production efficiency and managing resources sustainably. In Indonesia, various plant types are essential agricultural commodities, yet their productivity is often disrupted by erratic weather, poor land management, pest infestations, and land-use change. This study proposes a predictive model for plant growth using a neural network implemented in the PyTorch framework, integrating multiple environmental features such as temperature, humidity, soil moisture, nutrients, pH, and NPK levels. Unlike previous works that typically focus on specific crops or limited variables, this research introduces a multivariate approach combining diverse agro-environmental data to classify plant types accurately. The model architecture was tuned using GridSearchCV, resulting in optimal hyperparameters (e.g., batch size 32, learning rate 0.001, activation: tanh), achieving high performance with Area Under the Curve (AUC) values nearing 1.0 across most classes. Visualization of network weights reveals how input features are transformed through hidden layers, providing interpretability and transparency in decision-making. The proposed system demonstrates strong generalization capability, as validated on unseen data, and offers real-time prediction feasibility for deployment on edge devices such as NVIDIA Jetson Nano. This work contributes a novel, data-driven approach to smart agriculture by enabling precise growth prediction across multiple plant types, enhancing strategic planning for resource allocation and crop management. Future work includes model adaptation for time-series forecasting and validation with live sensor inputs in real-world agricultural environments.
Internet of Things Based Solar Battery Monitoring System Muzazanah, Annisa Tyas; Silaban, Freddy Artadima
Techno.Com Vol. 24 No. 3 (2025): Agustus 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i3.13499

Abstract

There are two factors in the solar panel system that affect battery life, namely the battery discharge factor and the environmental factor temperature which the battery is placed in. The battery is damaged quickly if it is empty for a long time. The application of solar cells is widely used in street lighting and office buildings. However, in several research, it was observed there were deficiencies, namely both current and voltage measurements were still carried out manually using a multimeter so that the data taken had not been recorded continuously. The purpose of this research is to design the Solar Panel System Battery Telemetry to be a solution and to solve the problem of knowing the battery condition is monitored regularly. This system uses ESP32 as an IoT-based microcontroller that is connected to the internet. The website is used to display data from the output of a solar panel battery. Based on the results of the analysis and testing that has been carried out, the design system can run according to the initial concept and can record the current, voltage, and temperature in real-time resulting from the performance of the solar panel system. The results of measurements on 10 wp solar panel with an average power of 7.32 watts with a maximum current of 0.6 A and presentation of a solar panel efficiency of 0.82%. The use of solar panel system batteries with a power requirement of 9 Watt 12V (lamp load) does not experience losses during the charging process.   Keywords - Battery, Solar Panel, Internet of Things, Real Time, Website
Flood Detection Design based on the Internet of Things Silaban, Freddy Artadima; Taufiq, Yufimar; Silalahi, Lukman Medriavin; Sihombing, Grace Lamudur Arta
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i4.9209

Abstract

Flood detection devices and water levels from several previous research studies were not optimal because they were still running and manual information, such as through loudspeakers, in some research, electronic devices have been used, but no information has been obtained, and it is not optimal if there is a danger sign. So this research is a study on the development of an automatic flood detection system and water level based on the IoT (Internet of Things). The system uses a NodeMCU Esp8266 controller with a combination of potentiometer sensors mounted on a water-level mechanic and connected to the Thingspeak IoT platform. Based on the results of the analysis and testing that have been done, the system is designed to combine the previous research algorithms so that it works more optimally and is better. The flood detection system and water level are made in two parts: one is placed upstream and the other is placed downstream, where the devices are connected. The device will turn on a danger alert when the altitude percentage is more than 85% of the maximum height. The lag time in the upload and download process is included in the Fast category (≤10 seconds). The resulting information can be monitored through the media portal website.
Design of a conductive material detection system Silaban, Freddy Artadima; Budiyanto, Setiyo; Silalahi, Lukman Medriavin
IAES International Journal of Robotics and Automation (IJRA) Vol 9, No 4: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v9i4.pp292-299

Abstract

The development of technology and industry development in the 4.0 era is very fast along with these developments in the control of production results such as medicine, food, and safety must be faster and more accurate. To face free trade and global economic competition, every company is required to produce products that have good quality by the standards. By using an experimental method which is the development of this study aims to make a conductive material detector (metal detector) for the pharmaceutical industry, the food industry, and security as compared to using conductive material sensors that are integrated with the Arduino microcontroller. Application testing is carried out to find out whether the Blynk application on an android smartphone with Blynk on a Debian server that has been made previously runs well or not and the alarm system testing uses a buzzer and LED to detect conductive material passing through. Conductive sensor test results showed that the instrument can detect 6 conductivity materials such as stainless steel, aluminum, steel, zinc, copper, and tin. The average response time to detect conductive material is 3 seconds, the average ADC value of the conductive material is 0.55. The test results also successfully send information and data to the Blynk application so that it can be monitored online.
Co-Authors Adi Kurnia Agus Dendi Rochendi Agus Dendi Rochendi Agus Dendi Rochendi Ahmad Firdausi Alvin Sepbrian Arga Gilang Rolanda Arif Rahman Hakim Astuti, Iklimadani Sheviana Berlin Silaban Dimas Jatikusumo Eko Cahyono Evanendra Nur Wisnu Putra Gao Hongmin Gunawan Osman Imelda Uli Vistalina Simanjuntak Kito Kurniawan Lukman Madriavin Silalahi Lukman Madriavin Silalahi Lukman Medriavin Silalahi Lussiana ETP Mochamad Furqon Ismail Muhammad Budi Haryono Muhammad Hafizd Ibnu Hajar Muhammad Ikhsan Muzazanah, Annisa Tyas Rachmat Muwardi RAHAYU, FAJAR Reimondika, Fegi Arga Rendy Elmianto Rochendi, Agus Dendi Selamet Kurniawan Septi Andryana Setiyo Budiyanto Sicilia Riris Oktaviany Sihombing, Grace Lamudur Arta Simanjuntak, Imelda Uli Vistalina Taufiq, Yufimar Triyanto Pangaribowo Ucuk Darusalam Wahyu Kusuma Raharja Yustisi Ayunda Putri