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Optimizing Google Apps in Improving the Skills and Productivity of the Young Generation of Bojong Village Pondok Kelapa Sofyan, Yan; Yudha, Afri; Syofian, Suzuki; Tri Mahardika, Bagus
JEPTIRA Vol 2 No 2 (2024): JOURNAL OF COMMUNITY ENGAGEMENT JEPTIRA
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/jep.v2i2.68

Abstract

Effective and efficient administrative and office management remains a primary challenge for organizations in the digital era. This community service activity aims to enhance the understanding and skills of Bojong youth in utilizing Google applications (Google Drive, Google Docs, Google Sheets, and Google Forms) as solutions for administrative management. The methods applied include theoretical training, hands-on practice, and evaluation of application implementation in daily workflows. The results indicate that using Google applications accelerates data processing by up to 30%, reduces paper usage by 40%, and improves collaboration and communication effectiveness among participants. Additionally, this training fosters a transition toward a digital work culture that is adaptive and responsive to technological challenges. Thus, using Google applications has proven to be a practical and relevant solution for supporting better organizational administrative governance.
Rancang Bangun Sistem Pemantau Gerak Otot Tangan Pada Pasien Stroke Berbasis Internet Of Things (IoT) Musyaffa, Luth Fais; Setiyaningsih, Timor; Syofian, Suzuki
Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Vol. 14 No. 1 (2024): Jurnal Sains & Teknologi
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70746/jstunsada.v14i1.506

Abstract

Monitoring hand muscle movements in stroke patients is a crucial aspect of the rehabilitation process to track therapy progress. However, manual monitoring by medical personnel requires significant time and effort. To address this issue, this study aims to design and develop a hand muscle movement monitoring system based on the Internet of Things (IoT). The system is designed to monitor finger movements using flex sensors attached to a glove, with data transmitted wirelessly to a web-based monitoring platform. The methodology used in this research involves the development of both hardware and software to record and transmit finger movement data in real-time. The system is also equipped with notifications via buzzers and LEDs to assist patients in adhering to therapy schedules set by medical professionals. Testing was conducted on stroke patients and healthy individuals to measure the system's effectiveness. The results indicate that this system can accurately and consistently monitor hand muscle movements in stroke patients. Trials conducted over five consecutive days on stroke patients showed that the average finger measurements ranged from 9.11 to 9.97, with significant differences in finger strength compared to healthy individuals. These findings suggest that this monitoring system is effective in supporting the rehabilitation process of stroke patients, enabling medical personnel to monitor and evaluate patient progress more accurately.
Rancang Bangun Sistem Pengawasan Infus Berbasis Teknologi Internet Of Things (IoT) Achmad Jayadi; Syofian, Suzuki
Journal TIFDA (Technology Information and Data Analytic) Vol 1 No 1 (2024): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i1.27

Abstract

Perkembangan teknologi Internet of Things (IoT) semakin luas diterapkan dalam berbagai aspek kehidupan sehari-hari termasuk dalam bidang kesehatan. Salah satu penerapan IoT yang dikembangkan adalah sistem pengawasan infus untuk meningkatkan pengawasan kontrol dan keamanan pasien dalam proses pengobatan infus. Penelitian ini memfokuskan pada pengembangan sistem pengawasan infus yang menggunakan sensor Load Cell untuk mendeteksi sisa cairan infus dan sensor LM393 untuk mendeteksi tetesan infus serta kenaikan darah. Mikrokontroler ESP32 digunakan sebagai pusat kendali yang terhubung dengan aplikasi monitoring memungkinkan pemantauan jarak jauh secara real-time melalui aplikasi mobile. Hasil pengujian menunjukkan bahwa sistem ini bekerja efektif dalam mengukur berat infus, mendeteksi tetesan infus, serta memberikan notifikasi yang tepat waktu saat terjadi kenaikan darah atau saat infus mendekati habis. Dengan demikian, sistem pengawasan infus berbasis IoT yang dikembangkan dalam penelitian ini dapat diandalkan untuk digunakan dalam lingkungan perawatan kesehatan, meningkatkan efisiensi dan akurasi dalam pengawasan infus pasien.
Perancangan Sistem Gudang Cerdas untuk Pemantauan Lingkungan Gudang Berbasis Internet of Things (IoT) Firmansyah, Adi; Syofian, Suzuki
Journal TIFDA (Technology Information and Data Analytic) Vol 1 No 2 (2024): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i2.34

Abstract

Penelitian ini bertujuan mengembangkan dan mengimplementasikan sistem Smart Warehouse berbasis Internet of Things (IoT) untuk memonitor dan mengontrol lingkungan gudang secara otomatis menggunakan modul ESP8266 untuk integrasi sensor, aktuator, dan aplikasi berbasis web yang memungkinkan pemantauan real-time serta kontrol otomatis. Sensor yang digunakan meliputi suhu dan kelembaban (DHT21), intensitas cahaya (BH1750), gas CO (MQ135), PIR, dan sensor api (KY-026), dengan otomatisasi kipas angin, exhaust fan, dan pencahayaan berdasarkan deteksi gas CO, keberadaan orang, serta intensitas cahaya. Sensor api mendeteksi potensi kebakaran, mengaktifkan alarm secara cepat, dan meningkatkan keamanan gudang melalui pemantauan yang dapat diakses pengguna dari dasbor berbasis web yang memudahkan pengambilan keputusan operasional. Hasil pengujian menunjukkan sistem ini mampu memberikan pemantauan akurat dan respons otomatis efisien dengan tingkat kepuasan pengguna yang tinggi dalam efektivitas serta kemudahan pemantauan lingkungan gudang.
Pengembangan Teknologi Internet Of Things Pendeteksi Kebakaran untuk Ruang Server dilengkapi Pemantauan Real-Time dan Notifikasi Whatsapp Serta Monitoring menggunakan Grafana Rizkhi, Muhammad; Syofian, Suzuki
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i2.43

Abstract

Fire is a serious threat that can cause physical, economic, and loss of life. Often triggered by human factors, nature, or equipment such as electricity and LPG, fires require rapid detection and response. Internet of Things (IoT) technology provides solutions with smart sensors that monitor the environment in real-time to detect temperature, smoke, or hazardous gases. This study develops an IoT-based fire detection system for server rooms that integrates fire sensors, MQ-2 smoke sensors, DHT-11 temperature sensors, CCTV for visual monitoring, and notification via WhatsApp. The Grafana monitoring platform is used for sensor data visualization. The case study was conducted at PT Askara Internal, with the aim of improving server room security and reducing fire risks, as well as increasing operational resilience through innovative and effective technology.
Implementasi Deep Learning Menggunakan Vision Transformer Untuk Klasifikasi Penyakit Daun Padi Febriyanto, Tri; Syofian, Suzuki
Journal TIFDA (Technology Information and Data Analytic) Vol 1 No 2 (2024): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i2.47

Abstract

Padi merupakan makanan pokok penting yang berperan signifikan dalam meningkatkan kesejahteraan masyarakat Indonesia. Namun, produksi padi sering terancam oleh berbagai penyakit daun yang disebabkan oleh patogen seperti jamur, hama, bakteri, dan virus. Beberapa penyakit daun padi yang umum termasuk Blas (Blast), Bercak Coklat (Brown Spot), Hawar Daun Bakteri (Bacterial Leaf Blight), dan Tungro. Kemajuan teknologi saat ini, khususnya dalam bidang Deep Learning, menawarkan solusi potensial untuk mengatasi tantangan tersebut. Deep Learning, sebagai sub-bidang Machine Learning, mengadopsi algoritma yang terinspirasi dari cara kerja otak manusia. Penelitian ini menggunakan metode Vision Transformer (ViT) dengan arsitektur ViT B16 untuk mengklasifikasikan penyakit daun padi. Dataset yang digunakan terdiri dari 1253 gambar, termasuk 419 gambar untuk penyakit Bercak Coklat, 355 gambar untuk penyakit Blast, 209 gambar untuk penyakit Hawar Daun Bakteri, dan 270 gambar untuk penyakit Tungro. Dataset dibagi menjadi 70% untuk pelatihan, 15% untuk validasi, dan 15% untuk pengujian. Pelatihan dilakukan dengan batch size 32, 50 epoch, dan menggunakan optimizer Adam. Hasil penelitian menunjukkan bahwa model yang dikembangkan mencapai akurasi, presisi, recall, dan f1-score sebesar 96%.
Overview of LabVIEW as a Graphical Programming Tool for Developing Industrial Technology Proficiency Istoni, Reza; Chan, Yefri; Hasanah, Nur; Isniah, Sarah; Sumartono, Budi; Syofian, Suzuki; Setiyaningsih, Timor
JEPTIRA Vol 3 No 1 (2025): JOURNAL OF COMMUNITY ENGAGEMENT JEPTIRA
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/jeptira.v3i1.94

Abstract

The purpose of this session is to expose participants with technical and vocational educational backgrounds to LabVIEW graphics programming software. In technical and industrial domains like biotechnology, aircraft, and telecommunications, LabVIEW is a commonly used system development tool. Hands-on practice and a demonstrative approach are used in the in-person instruction. LabVIEW's foundations, industrial applications, and hardware and software integration are all covered in the curriculum. The training results show that participants have a better understanding of visual programming and its possible uses in the business. This program is a component of a larger strategy to promote Industry 4.0-aligned technological literacy.