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Electric Lamp Light Intensity System Using Blynk Based Internet of Things Saepurohman, Asep; Ramza, Harry; Sofwan, Agus
TIME in Physics Vol. 3 No. 1 (2025): March
Publisher : Universitas Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/timeinphys.2025.v3i1p20-30

Internet of things (IoT) is a requirement that is being developed a lot in smart homes today. Currently, many technology developers create smart devices that can make human work easier. Smart home systems are one of them. In a smart home system, physical devices can communicate via the internet network or other near cable networks to monitor or control devices in a house or building. In order to be able to monitor or control the physical device is integrated with sensors and actuators. One implementation of a smart home is controlling the light intensity of the lights which can be adjusted using the sleader command on Blynk IoT which is installed on the smartphone. The aim of this research is for users to be able to control the light intensity of house lights by using the sleader command on the Blynk IoT application by house occupants. The method used in this research is IoT. IoT-based communication methods allow data exchange between devices. The result of this research is that a lighting control system can be built using Blynk IoT. A feature has been added to this system to control the electrical power that will enter the lamp, so that it can regulate the light intensity according to needs. The success of the system is influenced by the Blynk IoT response when giving a signal to the Node MCU 8266 and the DIMMER response when receiving a command signal from the NODE MCU8266.

Pemanfaatan Data Satelit Sentinel-1 dan Sentinel-2 untuk Deteksi Kapal Transhipment di Perairan Bintan Aprianto, Rizqi Naufal; Sahar, Fahmi; Hartuti, Maryani; Pinardi, Sofia; Ramza, Harry
COMSERVA : Jurnal Penelitian dan Pengabdian Masyarakat Vol. 5 No. 2 (2025): COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/comserva.v5i2.3190

Perairan Indonesia memiliki aktivitas pelayaran yang sangat tinggi, sehingga memerlukan sistem pemantauan yang andal untuk mendukung keselamatan navigasi, pengawasan maritim, dan pengelolaan sumber daya laut. Penelitian ini bertujuan untuk memanfaatkan data Sentinel-1, Sentinel-2, dan Automatic Identification System (AIS) dalam mendeteksi kapal di perairan Bintan. Deteksi kapal dari citra Sentinel-1 dilakukan dengan algoritma Constant False Alarm Rate (CFAR), yaitu teknik deteksi objek berbasis ambang batas dan klasifikasi untuk membedakan kapal dari latar perairan. Pada citra Sentinel-2, digunakan metode interpretasi visual untuk mengidentifikasi dugaan aktivitas transhipment. Data AIS digunakan sebagai acuan untuk memverifikasi posisi dan jenis kapal yang terdeteksi. Hasil penelitian menunjukkan bahwa integrasi data Sentinel-1, Sentinel-2, dan AIS mampu meningkatkan akurasi dalam identifikasi kapal, termasuk kapal yang tidak dilengkapi perangkat AIS. Tercatat lima kejadian dugaan transhipment pada 13 September 2024 dan tujuh kejadian pada 12 November 2024. Hasil ini menjadi dasar awal bagi pihak pengamanan maritim untuk melakukan analisis lebih lanjut guna mendukung pengambilan keputusan yang tepat.

Pemberdayaan Masyarakat Dan Pemasangan Lampu Pju Di Keramba Ikan Menggunakan Solar Panel Rosalina, Rosalina; Pratiwi, Nunik; Ariyansyah, Riyan; Davy Wiranata, Ade; Sinduningrum, Estu; Ramza, Harry; Gunadi, Reza; Pinardi, Sofia; Miftahuddin, Miftahuddin; Widodo, Muh. Adnan
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 5 No. 2 (2024): Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN)
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v5i2.1418

Budi daya ikan Lele (Clarias gariepinus) saat ini sangat diminati oleh banyak orang karena mudah dipelihara dan menjanjikan peluang pasar yang diperlukan untuk mengisi perhotelan, Restoran, konsumsi rumah tangga. Tujuan dari penelitian ini adalah bagaimana memberdayakan masyarakat melalui budi daya ikan lele. Temuan ini didukung oleh penelitian terdahulu yang menunjukan manfaat yang serupa dalam memberdayakan masyarakat dengan cara membantu dalam budi daya ikan lele dalam satu kelompok penambak ikan hingga mampu membuka peluang peningkatan potensi ekonomi di masyarakat. Rekomendasi utama dari pengabdian kepada masyarakat ini adalah pentingnya memberdayakan masyarakat dalam meraih hasil usaha dalam bidang tambak ikan dan terus mendorong agar mampu mengembangkan hasilnya dalam pengemasan dan pemasaran sehingga menjadi UMKM yang mampu bersaing di dunia bisnis internasional. Adapun Metode pengabdian masyarakat yang digunakan adalah studi kasus dengan pendekatan kualitatif. Teknik pengumpulan data yang digunakan adalah observasi, wawancara dan dokumentasi. Hasil yang didapatkan adalah proses pemberdayaan masyarakat melalui kegiatan budidaya ikan lele. Pengmas ini ditujukan pada kelompok petani tambak ikan Lele “Andir Farm” berlokasi di daerah Cibinong. Dalam kesimpulan pentingnya memberdayakan masyarakat dalam upaya membuka peluang kerja guna memperbaiki ekonomi keluarga disisi lain mendukung program pemerintah mengurangi jumlah angka kemiskinan penduduk Indonesia.

Internet of Things (IoT) Based Temperature and Humidity Detector Prototype in the UHAMKA Data Center Room Rizkiawan, M. Asep; Ramza, Harry; Sofwan, Agus
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.28035

Internet of Things (IoT) is a concept where an object or entity is imbued with technology such as sensors and software, aiming to communicate, control, connect, and exchange data with other devices as long as they remain connected to the internet. In this research, the developed IoT is employed to monitor and control the conditions of a data center space. The research methodology follows the system development life cycle, utilizing the Blynk application and a modified Arduino Uno with the esp8266 microcontroller, relay, and DHT-22 sensor for real-time temperature and humidity detection. The IoT development's outcomes were tested through black box and white box approaches. The research results demonstrate that the IoT network prototype functions effectively, enhancing the performance of the data center space. Temperature measurements were acquired from the DHT22 sensor, and alternative temperature measurements were taken without utilizing the DHT22 sensor, instead using a tool known as a thermometer, revealing measurement errors. Based on the calculation of the average percentage of temperature error on the DHT22 sensor, it can be concluded that the temperature error rate reaches 0.051%, while for humidity it reaches 0.064%, with an average delay time of 6.542 ms. Additionally, users have convenient access through both a website and mobile platform for seamless monitoring.

Geospatial Data Integration for the Flood Vulnerable Area Classification in Jratunseluna Watershed Assaidi, Humaid; Khomarudin, Muhammad Rokhis; Badron, Khairayu; Ismail, Ahmad Fadzil; Ramza, Harry
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4233

Flood is a threat that has significant impacts on communities and the environment. To improve the management of disaster risk, this research takes an integrated approach by utilizing geospatial data from various sources. The main objective of this research is to provide an integrated approach to determining flood-vulnerable area classes. This research focuses on the processing of various geospatial data such as DEM (Digital Elevation Model) imagery, Landsat 8 satellite imagery, Hydrological data based on SHuttle Elevation Derivatives at multiple Scales (HydroSHEDS) water flow accumulation imagery, and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) rainfall imagery which are used as data sources to model the flood vulnerable area classification of The Jratunseluna watershed. Landsat 8 satellite imagery is used as a source for landuse land cover (LULC) classification, it is done to score each land category to the level of ability to absorb and drain excess water, the remaining data is used to score the earth elevation, accumulated water flow, and rainfall from the area. The weights and scores are used as the basis values to create a flood-vulnerable area classification model. The result of this research is a flood-vulnerable area classification map generated from a pre-made model.

ANALISIS KINERJA JARINGAN 4G LTE MENGGUNAKAN METODE DRIVE TEST DI KELURAHAN KAMPUNG RAMBUTAN, JAKARTA TIMUR Akram, Ar'rafi; Melvandino, Figo Hafidz; Bragaswara, Wildan Yuda; Ramza, Harry
Jurnal Informatika dan Teknik Elektro Terapan Vol. 11 No. 3 (2023)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v11i3.3140

Saat ini, sistem komunikasi seluler telah menjadi suatu kebutuhan penting bagi masyarakat. Penelitian ini bertujuan untuk menganalisis kinerja jaringan 4G LTE melalui drive test dengan parameter RSRP (Reference Signal Received Power), RSSI (Received Signal Strength Indicator), RSRQ (Reference Signal Received Quality), dan SNR (Signal-to-Noise Ratio). Nilai data dari hasil drive test pada provider XL Axiata, nilai kategori sangat baik berada di kawasan SMPN 257 Jakarta dengan RSSI -75 dBm, RSRP -68 dBm, RSRQ -12 dB, dan SNR 12 dB, nilai kategori sangat buruk di kawasan SMA Teladan 1 dengan RSSI -91 dBm, RSRP -98 dBm, RSRQ -16 dan SNR -2 dB. Pada provider Telkomsel, nilai kategori sangat baik berada di kawasan SDN Susukan 09 dengan RSSI -75 dBm, RSRP - 69 dBm, RSRQ -8 dB, dan SNR 20 dB, nilai kategori sangat buruk di kawasan SMA Teladan 1 dengan RSSI -95 dBm, RSRP -107 dBm, RSRQ -15 dan SNR -3 dB. Pada provider Indosat Ooredoo, nilai kategori sangat baik berada di kawasan SMPN 257 Jakarta dengan RSSI -51 dBm, RSRP -78 dBm, RSRQ -13 dB, dan SNR 10,4 dB, nilai kategori sangat buruk di kawasan SDIT Al-Kahfi dengan RSSI -59 dBm, RSRP -99 dBm, RSRQ -20 dan SNR 6 dB.

KLASIFIKASI AKTIVITAS OLAHRAGA BERDASARKAN CITRA FOTO DENGAN MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK Akram, Ar'rafi; Rachmadinasya, Safira Adinda; Melvandino, Figo Hafidz; Ramza, Harry
Jurnal Informatika dan Teknik Elektro Terapan Vol. 11 No. 3s1 (2023)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v11i3s1.3496

In an era of advancing technology and information, sports are also receiving increasing attention from various sectors, including enthusiasts and participants in the sports industry. However, to better understand and manage the sports world, a thorough analysis and understanding of various aspects of sports are necessary, including classification and recognition of different types of sports. One potent and effective approach to image pattern recognition is the Convolutional Neural Network (CNN). CNN is a classification method particularly suitable for classifying digital images. The architecture of CNN is designed effectively to recognize objects within images. The dataset employed comprises 2348 samples for training, 294 samples for testing, and 294 samples for validation. The training process of the CNN model using DenseNet121 architecture yields an accuracy rate of 99%, with a validation accuracy rate of 88.78%. Through this research, it is expected that the application of CNN will create a system capable of automatically and accurately identifying the types of sports being performed by individuals or groups based on images or captured visuals of sporting activities.

Data Center Room Monitoring Based on Temperature and Humidity with Internet of Things Rizkiawan, M. Asep; Ramza, Harry; Nuroji, Nuroji; Sofwan, Agus
Jambura Journal of Electrical and Electronics Engineering Vol 6, No 2 (2024): Juli - Desember 2024
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v6i2.23344

The idea of the Internet of Things (IoT) encompasses the application of technologies such as sensors and software to an object for the purpose of communicating, controlling, connecting, and exchanging data with other devices while connected to the Internet. In this study, the IoT concept developed was used to monitor and regulate conditions within the data center. The development method used is the life cycle method of system development. The development process involved modifying the Arduino Uno with an esp8266 microcontroller and a DHT-22 sensor to detect temperature and humidity in real time. The testing of IoT development was done using the black box and white box methods. Research results show that the prototyped IoT network can operate well and successfully improve data center performance. In addition, users can also access the system through websites and mobile applications to facilitate the monitoring process.

Pemanfaatan Data Satelit Sentinel-1 dan Sentinel-2 untuk Deteksi Kapal Transhipment di Perairan Bintan Aprianto, Rizqi Naufal; Sahar, Fahmi; Hartuti, Maryani; Pinardi, Sofia; Ramza, Harry
COMSERVA : Jurnal Penelitian dan Pengabdian Masyarakat Vol. 5 No. 2 (2025): COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/comserva.v5i2.3190

Perairan Indonesia memiliki aktivitas pelayaran yang sangat tinggi, sehingga memerlukan sistem pemantauan yang andal untuk mendukung keselamatan navigasi, pengawasan maritim, dan pengelolaan sumber daya laut. Penelitian ini bertujuan untuk memanfaatkan data Sentinel-1, Sentinel-2, dan Automatic Identification System (AIS) dalam mendeteksi kapal di perairan Bintan. Deteksi kapal dari citra Sentinel-1 dilakukan dengan algoritma Constant False Alarm Rate (CFAR), yaitu teknik deteksi objek berbasis ambang batas dan klasifikasi untuk membedakan kapal dari latar perairan. Pada citra Sentinel-2, digunakan metode interpretasi visual untuk mengidentifikasi dugaan aktivitas transhipment. Data AIS digunakan sebagai acuan untuk memverifikasi posisi dan jenis kapal yang terdeteksi. Hasil penelitian menunjukkan bahwa integrasi data Sentinel-1, Sentinel-2, dan AIS mampu meningkatkan akurasi dalam identifikasi kapal, termasuk kapal yang tidak dilengkapi perangkat AIS. Tercatat lima kejadian dugaan transhipment pada 13 September 2024 dan tujuh kejadian pada 12 November 2024. Hasil ini menjadi dasar awal bagi pihak pengamanan maritim untuk melakukan analisis lebih lanjut guna mendukung pengambilan keputusan yang tepat.

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