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All Journal Jurnal Teknologi Informasi dan Multimedia Prosiding National Conference for Community Service Project Telcomatics Journal of Information System and Technology (JOINT) Conference on Community Engagement Project (Concept) Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan
Sabariman Sabariman
Universitas Internasional Batam
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Other

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Journal : telcomatics

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Characterization of The Heat Transfer in Film Boiling with Spray Quenching for Different Material Properties Sabariman Sabariman
Telcomatics Vol 2 No 2 (2017)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A hot aluminum alloy AA6082 and nickel disc of 560 °C and 850 °C was cooled by a spray nozzle with the spray flux of 4.2, 10 and 13.7 kg/m2s. The temperature history during the cooling process was recorded with use of an infrared camera. The energy balance equation is the basis for the numerical procedure of Heat Transfer Coefficient (HTC) calculation in the film-boiling regime. It is found that HTC is almost independent from kind of metals. HTC has a stronger function of surface temperature. With use of single droplet model in film boiling developed, vapor film thickness can be calculated to predict this trend.
Prototype of Automatic Cafe Management System (ACMS) Based on Internet of Things (IOT) Sabariman Sabariman; Erris Fernandy
Telcomatics Vol 7 No 1 (2022)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v7i1.6797

Abstract

The COVID-19 Pandemic changes people’s lifestyle nowadays. Physical interactions between person have lessened due to laws passed by central governments concerning its limitations. It’s no surprise this impacted businesses that needs face-to-face meetings, such as cafés or restaurants. Based on such facts, prototype for Automatic Café Management System (ACMS) based on Internet of Things (IOT) is designed. ACMS allows customers to order food through web-based system that can be accessed with their gadgets. The system is equipped with a line follower robot to act as waiter/waitress. With such system, physical contacts in café or restaurant settings can be reduced significantly.
Design Sistem Kendali Temperature Otomatis dan Fitur Baby Monitoring dengan IOT pada Inkubator Grashof Tipe G - 62 Sabariman Sabariman; Nofriyadi Nofriyadi
Telcomatics Vol 7 No 2 (2022)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v7i2.7323

Abstract

Riset ini ditujukan untuk mendesain sistem kontrol otomatis pada inkubator bayi Grashof type G-62. Dengan menggunakan Logika Fuzzy, berat bayi dan kelembaban kabin diset sebagai input. Dalam fungsi waktu, parameter-parameter yang dikontrol selama pengoperasian inkubator bayi tersebut adalah berat, detak jantung, suhu badan, kelembaban dan suhu kabin. Semua nilai parameter ini kemudian ditransmisikan secara real time melalui fitur Internet of Thing (IoT) yang disematkan pada sistem. Metode Filter Kalman diaplikasikan untuk mengurangi error pada pembacaan sensor berat load cell. Sistem kontrol berhasil menginterpretasikan secara akurat kombinasi input berupa data berat bayi dan kelembaban kabin untuk kemudian menyesuaikan suhu kabin yang ideal bagi bayi.
Perancangan Prototype Brankas Menggunakan Sistem Pengenalan Wajah Dengan Metode Convolutional Neural Network (CNN) Andik Yulianto; Willy Andreas; Sabariman Sabariman
Telcomatics Vol 8 No 1 (2023)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v8i1.7852

Abstract

A safe-deposit box is a box used for keeping precious items. Safe-deposit boxes are designed to be difficult for people to open by force. There are various security systems that may be used in it, such as mechanical key, combinational lock, PIN, etc. However, a safe-deposit box is still prone to unpermitted access because anyone who knows the PIN or possesses the key is still able to open it. This research aims to create a safety-box prototype which has a face recognition system implemented on it to ensure no unauthorized person may access this box. Experiment is performed on three different classes, which are “erwin”, “unknown”, and “willy”. Class of “erwin” and “willy” are defined as safe owners, while “unknown” is defined as anyone who is not both owners. Classification on safe owners is considered success if the percentage output in corresponding classes is at least 90 %. Classification on “unknown” class is considered success if the result is at least 90 % or percentage on each class is lower than 90 %. Accuracy for each class is 0 %, 71.43 %, dan 100 %.
Perancangan Alat Pengolahan Sampah Organik Berbasis Internet of Things (IoT) untuk Produksi Gas Metana dan Pupuk Kompos Jastin; Vincen; Habib Bahy Hussein; Bonni Saputra; Sabariman Sabariman; Andik Yulianto
Telcomatics Vol. 11 No. 1 (2026)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v11i1.11046

Abstract

This paper presents the design of an Internet of Things (IoT)-based organic waste processing device to produce methane gas and compost. The system uses a large sealed plastic container fitted with a biogas nanometer gauge on the lid and an ESP32 microcontroller for data acquisition. A capacitive soil moisture sensor measures the moisture of decomposed organic material, while an MQ-4 gas sensor monitors methane concentration inside a separate 5-liter plastic storage tank. Organic waste is fermented naturally, and gas is transferred manually through establishing valves while the pressure reaches a described threshold. All sensor information are dispatched to the Blynk cellular software for real-time tracking and visualization. This low-price answer gives a realistic technique to changing family natural waste into renewable power and natural fertilizer.
Pendekatan Klasifikasi Random Forest untuk Identifikasi URL Berbahaya yang Akurat Haeruddin Haeruddin; Elvert; Andik Yulianto; Sabariman Sabariman
Telcomatics Vol. 10 No. 2 (2025)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v10i2.11173

Abstract

Internet users currently face significant risks from malicious URLs that facilitate phishing attacks, malware distribution, and data theft. Traditional blacklisting methods have become ineffective against evolving cyberattack techniques. This study proposes a Random Forest classification approach for more accurate malicious URL detection, focusing on critical URL features including URL length, presence of special keywords, subdomain structure, and special character usage. these features train the Random Forest model to distinguish between safe and malicious URLs. We evaluate model effectiveness using accuracy, precision, and recall metrics. This research aims to develop a Random Forest-based malicious URL detection system that is more accurate and adaptive than conventional methods. The study examines both the advantages and limitations of this approach, along with its potential as a reliable detection solution for dynamic digital environments. Evaluation results demonstrate an overall accuracy of 94%, weighted average F1-score of 0.94, and macro average F1-score of 0.94.
Evaluasi Komparatif Model Transferlearning untuk Klasifikasi Tanaman Aquascape Muhammad Ilham Ashiddiq Tresnawan; Ni'matul Ma'muriyah; Sabariman; Lesley Peterson Lee
Telcomatics Vol. 11 No. 1 (2026)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v11i1.12440

Abstract

The popularity of aquascaping has increased significantly in recent years. However, beginners often face difficulties in identifying aquatic plant species due to their highly similar visual characteristics, which may lead to improper plant care. This study evaluates and compares the performance of three Convolutional Neural Network (CNN) architectures, namely MobileNetV3 Large, ResNet18, and EfficientNet-B0, for classifying six aquascape plant species: Anubias, Bucephalandra, Cryptocoryne Wendtii, Floaters, Hornwort, and Vallisneria Spiralis. The dataset consists of 1,998 images resized to 224 × 224 pixels and enhanced through data augmentation techniques, including rotation, horizontal flip, color jitter, and Gaussian blur, to improve model generalization. The models were trained using the PyTorch framework with transfer learning, fine-tuning based on ImageNet pretrained weights, the AdamW optimizer, class weighting, and an early stopping strategy. Experimental results show that ResNet18 achieved the highest test accuracy of 92.7%, followed by EfficientNet-B0 with 90.3% and MobileNetV3 Large with 88.7%. These findings indicate that the residual learning architecture of ResNet18 is particularly effective for aquatic plant classification on the proposed dataset, while MobileNetV3 Large remains a suitable alternative for deployment on resource-constrained devices.
Co-Authors Abdurrakhman Alhakim Adi Alexsandro Andik Yulianto Andik Yulianto Ayu Yulia Mutiara Bonni Saputra Daniel Lim Destiana Safitri Dewi Dewi Elvert Erika Chanada Erris Fernandy Erwin Yoe Eva Awaliya Felix Yeovandi Florentina Jasmine Getrudis Yetiana Wadhi Gladys Christiani Goharwin Goharwin Habib Bahy Hussein Haeruddin Haeruddin, . Jastin Kelvin Ramadhani Tambunan Lau, Eric Lesley Peterson Lee Lilian Nurul Wildani Lip Son Mardiana Ng Michelle Lim Muhammad Baharudin Muhammad Ilham Ashiddiq Tresnawan Mungkap Mangapul Siahaan Ni'matul Ma'muriyah Nofriyadi Nofriyadi Novi Sandra Prasetyo, Stefanus Eko Prisicilia Mareta Rainal Agus Setiawan Rico Kartono Riswanto Riswanto Sama, Hendi Serina Serina Sevilla Nadia Amanda Shely Juniarty Syahputra, Bayu Tiara Plorist Sibarani Vennes Owen Vincen Willy Andreas Yulianto, Andik Zulkarnain Zulkarnain