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All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JOIV : International Journal on Informatics Visualization InComTech: Jurnal Telekomunikasi dan Komputer Journal of Electronics, Electromedical Engineering, and Medical Informatics IJAIT (International Journal of Applied Information Technology) Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) Computer Science and Information Technologies Mejuajua eProceedings of Applied Science ARMADA : Jurnal Penelitian Multidisiplin JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Jurnal INFOTEL Journal of Applied Engineering and Social Science Proceeding of Community Service and Engagement
Giva Andriana Mutiara
Telkom University
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PEMBUATAN MEDIA PENYIRAMAN TANAMAN KEBUN OTOMATIS DI PETERNAKAN PADARINGAN SMART FARMING CILENGKRANG Muhammad Rizqy Alfarisi; Giva Andriana Mutiara; Periyadi Periyadi; Ichlasul Amal Restu Wardhana; Fauzi Ishak
The Proceeding of Community Service and Engagement (COSECANT) Seminar Vol. 3 No. 1 (2023): Prosiding COSECANT : Community Service and Engagement Seminar
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cosecant.v3i1.7121

Abstract

Di tempat peternakan padaringan terdapat kebun yang ditanami beragam tanaman sayur. Pemilik kebun perlumelakukan irigasi secara rutin untuk menjaga kelembapan dari tanaman agar tanaman tumbuh subur. Dalammelakukan irigasi perlu diperhatikan intensitas air untuk setiap tanaman. Dalam melakukan pengairandibutuhkan tenaga yang lebih untuk menjaga tumbuh pertumbuhan tanaman. Terkait permasalahan ini makadikembangkan sebuah sistem penyiraman air yang memudahkan pemilik kebun untuk melakukan pengairan.Sistem yang dikembangkan menggunakan sensor relay, mikrokontroler arduino mega, dan sensor kelembapanuntuk mengatur penyiraman. Berdasarkan nilai kelembapan tanah, mikrokontroler arduino mega akanmengendalikan relay yang terhubung dengan solenoid valve untuk mengirimkan air dari pipa ke kebun. Padatanggal 08 Desember 2023 dilaksanakan pemasangan sistem penyiraman tersebut pada kebun padaringan.Dengan adanya sistem penyiraman otomatis ini, diharapkan dapat membantu petani dalam mengoptimalkansistem irigasi tanaman secara efektif dan efisien.
PEMBUATAN SISTEM MONITORING STORAGE PEMBERIAN PAKAN KAMBING PERAH DI DESA MARGAMULYA Muhammad Rizqy Alfarisi; Giva Andriana Mutiara; Mohammad Rizky Septianto; ichlasul Amal Restu wardhana; Reivo Akbar Novarist; Rafid Shidqi Rabbani
The Proceeding of Community Service and Engagement (COSECANT) Seminar Vol. 4 No. 1 (2024): The Proceeding of Community Service and Engagement (COSECANT) Seminar
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cosecant.v6i1.7858

Abstract

Pemanfaatan teknologi informasi digital sudah diterapkan diberbagai bidang kehidupan dan salah satunya diterapkan dalam bidang peternakan ruminansia kecil. Saat ini kelola peternakan hewan ruminansia seperti kambing dan domba masih sangat bergantung pada monitoring tenaga manusia dalam pemberian pakan dan pemantauan suhu dan kelembaban yang terjadi pada area kandang domba atau kambing, kebutuhan akan system monitoring berbasis IoT (Internet of Things) akan membantu para peternak untuk memantau kondisi ketersedian jumlah pakan dan kondisi kebersihan lingkungan kandang untuk menjaga kesehatan hewan ternak tersebut. Hasil dari kegiatan pengabdian masyarakat ini menunjukan bahwa pemanfaatan teknologi dapat membantu dalam bidang peternakan dan juga sebagai edukasi pada Masyarakat untuk meningkatkan kualitas ternak yang lebih baik dengan memanfaatkan teknologi, dalam pelaksanaannya kegiatan ini melibatkan Masyarakat dari kelompok ternak neqtasari margamulya. Kesimpulan dari penerapan teknologi dalam bidang peternakan ini adalah untuk membantu para kelompok ternak neqtasari desa margamulya dalam meningkatkan kualitas hasil ternak serta menjadi langkah awal adopsi memanfaatkan teknologi yang berkontribusi dalam edukasi Masyarakat dalam modern farming.
Implementation of Real-Time Face Recognition for Secure Weapon Storage Access Control Anisa Anisa; Giva Andriana Mutiara; Muhammad Rizqy Alfarisi
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 8 No 2 (2026): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v8i2.1608

Abstract

The security of weapon storage warehouses is a critical concern that requires an access control system with exceptionally high reliability, particularly in minimizing false acceptance, where unauthorized individuals are incorrectly granted access. In high-risk facilities, even a single false acceptance incident can lead to serious security consequences. Conventional systems based on physical keys or access cards present limitations, including risks of loss, duplication, and access forgery. Therefore, a biometric-based solution is necessary to enhance identification accuracy and strengthen overall security. This study aims to design and implement a reliable, high-security facial-recognition-based access control system for weapon storage facilities. The proposed system integrates a Multi-task Cascaded Convolutional Neural Network (MTCNN) for face detection, FaceNet for feature extraction, and a Support Vector Machine (SVM) for identity classification. The system is implemented as a standalone application on an edge computing device (mini PC) integrated with an electronic door lock. All detection and decision-making processes are performed locally without reliance on cloud services. System evaluation was conducted under various testing scenarios, including variations in lighting intensity, camera distance, facial attributes, and unregistered face testing. Experimental results show that the system achieved an accuracy of 96.25%. A precision of 100% indicates that no unauthorized access was granted. The recall reached 92.50%, reflecting a small proportion of rejected authorized users. The F1-score of 96.11% demonstrates balanced performance. The False Acceptance Rate was 0%, confirming complete prevention of illegal access. The False Rejection Rate was 7.50%, which remains acceptable in high-risk security environments. The system consistently rejected all unregistered faces and operated in real time with an average door unlocking response time of approximately 1.3 seconds. In conclusion, the proposed system provides reliable recognition performance with a strong emphasis on preventing false acceptance. These findings indicate its suitability for enhancing security in high-risk weapon storage facilities.
Smart brake pad early warning system: enhancing vehicle safety through real-time monitoring Afif Syam Fauzi; Giva Andriana Mutiara; Muhammad Rizqy Alfarisi; Tedi Gunawan; Muhammad Aulia Rifqi Zain
Computer Science and Information Technologies Vol 6, No 2: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i2.p122-135

Abstract

A contributing factor to traffic accidents is brake pad failure, which diminishes braking system performance and extends braking distance. This work develops a prototype utilizing internet of things (IoT) to measure brake pad thickness, hence enhancing driver awareness through real-time monitoring. The system establishes the thickness detection threshold at 75% (3-4 mm) and 50% (5–6 mm) as a cautionary parameter. The thickness parameter employs an American wire gauge (AWG) 18 cable to connect to the ESP32 microcontroller. The web-based IoT monitoring interface employs Laravel. This method enables drivers to get prompt notifications regarding the decrease in brake pad thickness, hence permitting urgent preventative maintenance to mitigate the risk of accidents. The system underwent testing through friction at a rotational speed of 600 to 6,000 rpm. The test findings indicated that the sensor precisely measured the brake pad thickness with a prototype response time of a second. This system is suitable for implementation on old model vehicles that do not have an early warning system. The installation of this technology is anticipated to enhance driver knowledge of the state of the brake pads, hence potentially diminishing the danger of brake system failure caused by unmonitored pad wear.
Pelatihan Simulator IoT untuk Siswa SMK Nasional bandung Nina Hendrarini; Giva Mutiara Andriana; devie Ryana Suchendra
JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Vol. 1 No. 3 (2023): JITER-PM
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jiter-pm.v1i3.6138

Abstract

Pengabdian masyarakat ini diselenggarakan kepada siswa SMK Nasional Bandung dengan tujuan memperkenalkan dan mengajarkan konsep Internet of Thing (IoT). Pelatihan ini dilaksanakan dengan diawali penjelasan tentang teori IoT, terutama manfaat dan implementasi pada saat wabah Covid berjangkit. Teori yang disampaikan mencakup pengenalan tentang IoT, perangkat keras yang umumnya diintegrasikan dengan sistem ini dan perangkat lunak yang digunakan dalam IoT, serta protokol komunikasi dalam IoT. Kegiatan kemudian dilanjutkan dengan praktikum pembuatan alat otomatis berbasis sensor dan mikrokontroller Arduino. Kegiatan ini bertahap dan direncanakan akan berlanjut pada program pengabdian masyarakat selanjutnya. Hasil dari pengabdian masyarakat ini diharapkan dapat memperluas wawasan berpikir siswa SMK dalam meningkatkan kompetensi mereka dalam bidang IoT. Hal ini dikarenakan teknologi ini ke depannya banyak dibutuhkan di masyarakat.
Driver Drowsiness Prediction Using CNN-LSTM Model Based on Facial Expression and Eye Movement Annisa Aprilia Putri Sakri; Angga Rusdinar; Giva Andriana Mutiara; Periyadi Periyadi
ARMADA : Jurnal Penelitian Multidisiplin Vol. 4 No. 8 (2026): ARMADA : Jurnal Penelitian Multidisplin, Agustus 2026
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi 45 Mataram

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

Abstract

Driver fatigue and drowsiness represent primary institutional catalysts for fatal highway traffic anomalies worldwide. This comprehensive investigation introduces an adaptive, multi-task deep learning architecture merging Convolutional Neural Networks and Long Short-Term Memory configurations to dynamically evaluate driver states through localized facial expressions and non-invasive ocular metrics. Utilizing MediaPipe FaceMesh, the framework maps 468 distinct landmark parameters under fluctuating illumination constraints to monitor regional variations across the eyes and mouth. The quantitative metrics are extracted by formulating real-time computations of the Eye Aspect Ratio and Mouth Aspect Ratio. Spatiotemporal feature representation is accomplished using a pre-trained ResNet50V2 feature extractor integrated with a 128-unit recurrent LSTM layer to process sequences across a 20-frame context window. The multi-branch dense layer concurrently outputs predictive status conditions for drowsiness, yawning frequency, and categorical facial expressions. System validation metrics indicate an overall classification accuracy of 88% for structural drowsiness tracking and 90% for yawning anomalies. This system is a “proof of concept” designed to be implemented for drivers to reduce traffic accidents caused by driver fatigue.
Co-Authors Adis Kusyadi Nugraha Afif Syam Fauzi Aldy Mulia Alfarisi, Muhammad Rizqi Althoriq, Muhammad Adib Anang Sularsa Andri Surya Dinata Angga Rusdinar Anisa Anisa Annisa Aprilia Putri Sakri Ardiansah, Taufik Ilham Edy Ardiyansah, Pungky Aris Pujud Kurniawan Azzam, Dylan Avilla Saeful Bethani Suryawardani Budiargo, Topan Devie Ryana Suchendra Dharmawan, Muhamad Haris Dicky Muhammad Dimas Salim Dwiyanto, Rizki Ananta Erlangga Birawa Doza Ersy Ervina Fadillah, Wildan Muhammad Yasin Fahmi Danah Pratama Fanny Husnul Hanifa Fauzi Ishak Fikri Muhammad Arifin Gita Indah Hapsari Gunawan, Tedi Guntur Prabawa Kusuma Hadian, Nadya Nanda Adisty Haq, Fikri A` Laya Hardy Adiluhung Husein Tarigan Ichlasul Amal Restu Wardhana ichlasul Amal Restu wardhana Ishak, Fauzi Ismail Ismail Ismail, Ismail Kurnia Wijayanti Lisda Meisaroh, Lisda Luky Rohendi Marlindia Ike Sari Mertu, Aidi Mochammad Zuliansyah Mohammad Rizky Septianto Muhammad Arifin, Fikri Muhammad Aulia Rifqi Zain Muhammad Ikhsan Sani Muhammad Rizky Alfarisi Muhammad Rizqy Alfarisi Muhammad, Dicky Nanna Suryana Nina Hendrarini Othman Mohd Pangestu, Diki Agus Periyadi Periyadi Periyadi  Piter Natanael Siboro, John Putra H, Calvin Satria Dewangga Putra, Dika Achmad Raden Sri Dewanto Wijaya Putra Rafid Shidqi Rabbani Ramadhanu Putra Regiana Prianggara Prasetya Reivo Akbar Novarist Rini Handayani Roy Chaidir Sujana, Aprianti Putri . Syaibir, Farhan Wardhana, Ichlasul Amal Restu Wiraguna, Ida Bagus Yogi