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All Journal Prosiding Semnastek JURNAL TEKNOLOGI INFORMASI Jurnal Pengabdian Teknologi, Ekonomi dan Humaniora Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Journal Technology Information and Data Analytic
Suzuki Syofian
Universitas Darma Persada
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences Other

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PENGGUNAAN ARTIFICIAL INTELIGENT (AI) UNTUK PENINGKATAN KUALITAS PENELITIAN UNTUK PENELITI DAN TENAGA PENDIDIK DI JAKARTA TIMUR Syofian, Suzuki; Setiawan, Aji; Budiman, Adam Arif; Setyaningsih, Timor
JEPTIRA Vol 1 No 1 (2023): JURNAL PENGABDIAN MASYARAKAT JEPTIRA
Publisher : Fakultas Teknik Universitas Darma Persada

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

Abstract

Pengabdian masyarakat (PKM) membahas inisiatif pengabdian masyarakat yang bertujuan untuk meningkatkan kompetensi tenaga pengajar di tingkat sekolah dan universitas melalui pelatihan penggunaan berbagai tools AI. Fokus utama adalah pada platform AI seperti ChatGPT, PerplexAI, Humata AI, ChatPDF, dan sejenisnya. Metodologi pengabdian masyarakat dilakukan dengan menyelenggarakan serangkaian pelatihan intensif yang mencakup pengenalan, pemahaman, dan penerapan praktis tools AI dalam lingkungan pendidikan. Beberapa tools praktek yang digunakan diharapkan mampu membantu para peneliti untuk mudah dan cepat dalam menyusun laporan penelitian.
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.
ANALISIS SENTIMEN TANGGAPAN PELANGGAN INDIHOME DI PLATFORM SOSIAL MEDIA FACEBOOK DAN TWITTER MENGGUNAKAN SUPPORT VECTOR MESIN DAN PENDEKATAN KLASIFIKASI NAÏVE BAYES (STUDI KASUS: PT. TELKOM INDONESIA) Norman, Suzuki Syofian; Kusuma, Dhino Rahmad; Afifa, Linda Nur
Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Vol. 13 No. 1 (2023): Jurnal Sains & Teknologi
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70746/jstunsada.v13i1.221

Abstract

In the digital era, the internet has become an inseparable part of everyday life, including the ease of finding information and sharing opinions through social media such as Twitter and Facebook. On these two platforms, users can provide reviews about products, including IndiHome services. The large number of reviews on social media reflects the high level of feelings users have for the service. However, currently PT. Telkom Indonesia does not fully know the opinions and reviews of IndiHome customers on social media, both positive and negative. This study aims to improve understanding of the positive and negative opinions of customers towards IndiHome and to compare the effectiveness of the Support Vector Machine and Naive Bayes algorithms in sentiment analysis. Thus, PT. Telkom Indonesia can take the necessary steps to increase public trust in IndiHome and evaluate the performance of the classification results using the Support Vector Machine and Naïve Bayes methods. The data used in this study amounted to 5000 data, but after the data preparation stage, the remaining 2000 data. From the data that has gone through the preparation stage, there are 638 data with positive sentiment and 1341 data with negative sentiment. The test results on the Support Vector Machine model achieve an accuracy of 91%, while the Naive Bayes model achieves an accuracy of 85%.
ANALISIS SENTIMEN TINGKAT KEPUASAN PELANGGAN TERHADAP LAYANAN KURIR J&T EXPRESS MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) BERDASARKAN ULASAN PENGGUNA DI GOOGLE PLAYSTORE: ANALISIS SENTIMEN TINGKAT KEPUASAN PELANGGAN TERHADAP LAYANAN KURIR J&T EXPRESS MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) BERDASARKAN ULASAN PENGGUNA DI GOOGLE PLAYSTORE Norman, Suzuki Syofian; Mahendra, Saddam
Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Vol. 13 No. 2 (2023): Jurnal Sains & Teknologi
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70746/jstunsada.v13i2.450

Abstract

Courier Service Is One Of The Services That Are Widely Used By The Public, Especially In The Current Digital Era. In This Context, Courier Services Allow Shippers To Deliver Goods Or Documents Without The Need To Be Present Directly To The Destination Location. J & T Express, As One Of The Shipping Expedition Service Providers In Indonesia, Is The First Choice For Many People. Although Technology Continues To Evolve And Competition Is Increasingly Fierce, The Quality Of Courier Services Is A Key Factor That Customers Need To Pay Attention To. However, It Should Be Noted That The J&T Express Application In The Google Play Store Received A Low Rating, And This Is The Background Of This Study. the main focus of this study was to identify the level of customer satisfaction with j&t express courier services through reviews available on the google play store. within the framework of this study, sentiment analysis was conducted using the support vector machine algorithm, by applying crisp-dm methodology. the results showed that from the business understanding stage to the modeling stage, the performance of the support vector machine can be considered good. in addition, this study also resulted in an implementation that can be accessed through a website with the address jnt-sentiment.streamlit.app. hopefully, this research can contribute to j & t express in understanding the views of customers and improving the quality of their services
P PENGEMBANGAN TEKNOLOGI INTERNET OF THINGS PENDETEKSI KEBAKARAN UNTUK RUANG SERVER DILENGKAPI PEMANTAUAN REAL-TIME MELALUI CLOSED CIRCUIT TELEVISION (CCTV) DAN NOTIFIKASI WHATSAPP SERTA MONITORING MENGGUNAKAN GRAFANA: PENGEMBANGAN TEKNOLOGI INTERNET OF THINGS PENDETEKSI KEBAKARAN UNTUK RUANG SERVER DILENGKAPI PEMANTAUAN REAL-TIME MELALUI CLOSED CIRCUIT TELEVISION (CCTV) DAN NOTIFIKASI WHATSAPP SERTA MONITORING MENGGUNAKAN GRAFANA Rikhi, Muhammad; Setiyaningsih, Timor; Norman, Suzuki Syofian
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.v14i1.492

Abstract

PENGEMBANGAN TEKNOLOGI INTERNET OF THINGS PENDETEKSI KEBAKARAN UNTUK RUANG SERVER DILENGKAPI PEMANTAUAN REAL-TIME MELALUI CLOSED CIRCUIT TELEVISION (CCTV) DAN NOTIFIKASI WHATSAPP SERTA MONITORING MENGGUNAKAN GRAFANA. Kebakaran merupakan ancaman serius yang dapat menyebabkan kerugian fisik, ekonomi, dan kehilangan nyawa. Seringkali dipicu oleh faktor manusia, alam, atau peralatan seperti kelistrikan dan Gas LPG, kebakaran membutuhkan deteksi dan respons yang cepat. Teknologi Internet of Things (IoT) menyediakan solusi dengan sensor pintar yang memantau lingkungan secara real-time untuk mendeteksi suhu, asap, atau gas berbahaya. Penelitian ini mengembangkan sistem deteksi kebakaran berbasis IoT untuk ruang server yang mengintegrasikan sensor api, sensor asap MQ-2, sensor suhu DHT-11, CCTV untuk pemantauan visual, dan notifikasi melalui WhatsApp. Platform monitoring Grafana digunakan untuk visualisasi data sensor. Studi kasus dilakukan di PT Askara Internal, dengan tujuan meningkatkan keamanan ruang server dan mengurangi risiko kebakaran, serta meningkatkan ketahanan operasional melalui teknologi inovatif dan efektif. Fires are a serious threat that can cause physical, economic, and life losses. Often triggered by human factors, nature, or equipment such as electrical and LPG gas, 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 research 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 notifications via WhatsApp. The Grafana monitoring platform is used for sensor data visualization. A case study was conducted at PT Askara Internal, aiming to enhance server room security and reduce fire risk, as well as improve operational resilience through innovative and effective technology.
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%.
Co-Authors Achmad Jayadi Achmad Jayadi Adam Arif Budiman Adi Firmansyah Afifa, Linda Nur Afri Yudha Agam Aria Damar Aji Setiawan Alpin Alpin Arif Winandar Bagus Tri Mahardika Budi Sumartono Febriyanto, Tri Herianto Isniah, Sarah Kusuma, Dhino Rahmad Mahendra, Saddam Musyaffa, Luth Fais Nur Hasanah Nur Syamsiah Richard Indra Setya S Rikhi, Muhammad Rizkhi, Muhammad Ronaldo Ronaldo Setyaningsih, Timor Sofyan, Yan Timor Setiyaningsih Tri Mahardhika, Bagus Wiwit Try Widyantoro Yahya yefri chan