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All Journal Jurnal Teknologi Pendidikan Jurnal Ilmu Komputer dan Agri-Informatika Spektra: Jurnal Fisika dan Aplikasinya Elektrika Jurnal Nasional Komputasi dan Teknologi Informasi MULTINETICS Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan Jurnal Sains Terapan : Wahana Informasi dan Alih Teknologi Pertanian Eduvest - Journal of Universal Studies Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Kendali Teknik dan Sains
Marcelita, Faldiena
Computer Engineering Technology Study Program, College Of Vocational Studies, IPB University
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OPTIMASI PERTUMBUHAN MICROGREEN RED RADISH MELALUI OTOMATISASI PENYIRAMAN, PENYINARAN, DAN PENYESUAIAN SUHU BERBASIS IOT Safitrah, Tiara; Khabibah, Dea Ummul; Ezer, Angga Eben; Fernando, Brilliant Sandynigy; Kauripan, Edmund Banyu; Satrio, Muchammad Alifandino; Maulidan, Muhammad Hafizh; A'isy, Nabil Arif; Marcelita, Faldiena; Fathonah, Lathifunnisa
Elektrika Vol. 16 No. 2 (2024): Oktober 2024
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/elektrika.v16i2.10429

Abstract

This research aims to optimize the growth of red radish microgreens through an automation system that integrates irri-gation, lighting, and temperature adjustment based on the Internet of Things (IoT). The research method involves the use of WS2812B LED strips as the lighting source for photosynthesis, soil moisture sensors to control irrigation, and DHT22 tem-perature sensors to adjust the ideal environmental temperature. Data collection combines relevant literature data with direct observations during the red radish microgreen planting process. Data analysis is conducted through descriptive approaches to understand the growth patterns of microgreen plants and correlation analysis to identify relationships be-tween various growth parameters. Additionally, the IoT system's response to changes in environmental conditions is ana-lyzed to evaluate the system's effectiveness in regulating lighting, irrigation, and temperature. The research findings indi-cate that the IoT-based automation system effectively enhances the growth and quality of red radish microgreens. The au-tomatic implementation of LEDs improves photosynthesis rates, while efficient irrigation systems ensure plants receive adequate water. The temperature automation system maintains optimal growth conditions and reduces the risk of thermal stress. Integrating this system into a website platform also enables remote control and monitoring. This automation system not only increases plant productivity and quality but also reduces maintenance costs and time, demonstrating the signifi-cant potential of IoT technology in modern agriculture. Keywords: Automation System, Growth, Internet of Things, Microgreen, Red Radish. ABSTRAK Penelitian ini bertujuan untuk mengoptimalkan pertumbuhan microgreen red radish melalui sistem otomatisasi yang mengintegrasikan penyiraman, penyinaran, dan penyesuaian suhu berbasis Internet of Things (IoT). Metode penelitian melibatkan penggunaan LED strip WS2812B sebagai sumber pencahayaan untuk fotosintesis, sensor kelembaban tanah untuk mengontrol penyiraman, dan sensor suhu DHT22 untuk menyesuaikan suhu lingkungan yang ideal. Pengumpulan data dalam penelitian menggabungkan data literatur yang relevan serta pengamatan langsung selama proses penanaman microgreen red radish. Analisis data dilakukan melalui pendekatan deskriptif untuk memahami pola pertumbuhan tana-man microgreen dan analisis korelasi untuk mengidentifikasi hubungan antara berbagai parameter pertumbuhan. Selain itu, respons sistem IoT terhadap perubahan kondisi lingkungan dianalisis untuk mengevaluasi efektivitas sistem dalam mengatur pencahayaan, penyiraman, dan suhu. Hasil penelitian menunjukkan bahwa sistem otomatisasi berbasis IoT efektif dalam meningkatkan pertumbuhan dan kualitas microgreen red radish. Penerapan LED secara otomatis meningkatkan laju fotosintesis, sementara sistem penyiraman efisien memastikan tanaman mendapatkan air yang tepat. Sistem otomatisasi suhu menjaga lingkungan pertumbuhan optimal dan mengurangi risiko stres termal. Integrasi sistem ini dalam platform website juga memungkinkan kontrol dan pemantauan secara remote. Sistem otomatisasi ini tidak hanya meningkatkan produktivitas dan kualitas tanaman, tetapi juga mengurangi biaya dan waktu pemeliharaan, menunjukkan potensi besar teknologi IoT dalam pertanian modern.
Penerapan Inovasi Augmented Reality dalam Rangka Digital Entrepreneurship pada UMKM di Kota Bandung Jawa Barat Marcelita, Faldiena; Novianty, Inna; Sinaga, Antonya Rumondang; Sayekti, Ayutyas
Jurnal Pengabdian Masyarakat: Pemberdayaan, Inovasi dan Perubahan Vol 5, No 6 (2025): JPM: Pemberdayaan, Inovasi dan Perubahan
Publisher : Penerbit Widina, Widina Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59818/jpm.v5i6.2300

Abstract

Digital transformation encourages micro, small, and medium enterprises (MSMEs) to adopt innovative technologies to remain competitive in the modern business ecosystem, including the use of Augmented Reality (AR) as an interactive promotional medium. This study aims to enhance the digital entrepreneurship capacity of MSMEs in Bandung City through the implementation of AR as a technology-based immersive marketing strategy. The program was carried out through a series of training activities covering an introduction to digital entrepreneurship concepts, basic AR principles, hands-on AR content creation, publication of AR-based Android applications on the Play Store, and mentoring for AR integration into MSME marketing platforms. The methods included assessing MSME needs, conducting technical training, facilitating strategic discussions on digital marketing, and evaluating program effectiveness through pre–post test surveys. The results indicate an improvement in participants’ digital understanding and skills, reflected in an increase in evaluation scores from 12 to 13, as well as their ability to produce and implement AR content for promotional purposes. The implementation of AR proved to enhance MSMEs’ readiness to adopt digital technologies and opened opportunities for more engaging and consumer-adaptive marketing models. Overall, this study concludes that AR is a strategic tool capable of strengthening the digital transformation of MSMEs and contributes significantly to the development of a more creative, competitive, and sustainable digital entrepreneurship ecosystem.ABSTRAKTransformasi digital mendorong pelaku UMKM untuk mengadopsi teknologi inovatif agar mampu bersaing dalam ekosistem bisnis modern, termasuk pemanfaatan Augmented Reality (AR) sebagai media promosi interaktif. Penelitian ini bertujuan untuk meningkatkan kapasitas digital entrepreneurship UMKM di Kota Bandung melalui penerapan AR sebagai strategi pemasaran digital berbasis teknologi marketing imersif. Kegiatan dilakukan melalui serangkaian pelatihan yang mencakup pemahaman konsep kewirausahaan digital, pengenalan dasar-dasar AR, praktik pembuatan konten AR, hingga publikasi aplikasi AR berbasis Android ke Play Store, serta pendampingan integrasi AR dalam media pemasaran UMKM. Metode pelaksanaan meliputi pemetaan kebutuhan UMKM, pelatihan teknis, diskusi strategis pemasaran digital, dan evaluasi efektivitas program melalui survei pre–post test. Hasil menunjukkan peningkatan pemahaman dan keterampilan digital peserta, yang ditandai dengan kenaikan skor evaluasi dari 12 menjadi 13 serta kemampuan peserta menghasilkan dan menerapkan konten AR untuk kebutuhan promosi. Implementasi AR terbukti meningkatkan kesiapan UMKM dalam memanfaatkan teknologi digital serta membuka peluang model pemasaran inovatif yang lebih menarik dan adaptif terhadap perilaku konsumen. Secara keseluruhan, kegiatan ini menyimpulkan bahwa AR merupakan alat strategis yang mampu memperkuat transformasi digital UMKM dan memberikan kontribusi signifikan bagi pengembangan ekosistem kewirausahaan digital yang lebih kreatif, kompetitif, dan berkelanjutan.
Penerapan Smart Drop Box Berbasis Internet of things (IoT) untuk Pengelolaan Sampah Plastik: Studi Kasus di Kota Medan Marcelita, Faldiena; Novianty, Inna; Sayekti, Ayutyas; Rumondang, Antonya
Jurnal Pengabdian Masyarakat: Pemberdayaan, Inovasi dan Perubahan Vol 5, No 6 (2025): JPM: Pemberdayaan, Inovasi dan Perubahan
Publisher : Penerbit Widina, Widina Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59818/jpm.v5i6.2262

Abstract

The issue of plastic waste management remains a major concern in the city of Medan. This highlights the importance of innovation in implementing an Internet of Things (IoT)-based Smart Drop Box, which became the objective of the community service program carried out. This technology enables users to recycle plastic waste more easily and effectively. The plastic waste sorting process, specifically for plastic bottles, begins by inserting the bottles into the device, which automatically detects them and converts them into points that can be redeemed for cash through an application. The implementation method of this community service activity consists of four stages: field observation, the development and testing of the Smart Drop Box device, and a survey of residents in the Sunggal Indah Complex, Medan City. The activity was attended by 25 residents from the complex as well as representatives from the local administrative office. The results of the community service program show that the implementation of this device increased public awareness and understanding regarding the importance of waste sorting. Survey data indicate a significant improvement in waste-sorting behavior after the activity, from a score of 3 to 4.5. This demonstrates that the use of IoT technology can encourage positive changes in plastic waste management. The implementation of the Smart Drop Box is expected to serve as a sustainable solution to address plastic waste issues while fostering environmental awareness among the community.ABSTRAKPermasalahan pengelolaan sampah plastik masih menjadi fokus utama di Kota Medan.  Hal ini menjadikan pentingnya inovasi terkait penerapan alat Smart Drop Box berbasis Internet of Things (IoT) yang menjadi tujuan kegiatan pengabdian masyarakat yang telah dilaksanakan. Teknologi ini memungkinkan pengguna untuk mendaur ulang sampah plastik dengan lebih mudah dan efektif. Proses pemilahan sampah berupa botol plastik diawali dengan memasukkan botol plastik ke dalam alat yang akan terdeteksi secara otomatis dan dikonversi menjadi poin yang dapat ditukar dengan uang tunai melalui aplikasi. Metode pelaksanaan kegiatan pengabdian masyarakat ini terdiri dari empat tahap yaitu kegiatan observasi lapangan, pembuatan dan pengujian alat Smart Drop Box, serta survei terhadap masyarakat di Kompleks Sunggal Indah, Kota Medan. Kegiatan ini diikuti oleh warga kompleks sebanyak 25 orang serta pengelola Kelurahan terkait. Hasil kegiatan pengabdian kepada masyarakat menunjukkan bahwa implementasi alat ini meningkatkan kesadaran dan pemahaman masyarakat tentang pentingnya pemilahan sampah. Data survei mengindikasikan adanya peningkatan signifikan dalam perilaku pemilahan sampah setelah kegiatan dari nilai 3 menjadi 4.5. Hal ini membuktikan bahwa penggunaan teknologi IoT dapat mendorong perubahan positif dalam pengelolaan sampah plastik. Implementasi Smart Drop Box diharapkan dapat menjadi solusi berkelanjutan dalam menghadapi permasalahan sampah plastik serta membangun kesadaran masyarakat terhadap lingkungan.
Calibration of Dissolved Oxygen Sensors in IoT Systems for Water Quality Monitoring in Aquaculture Mindara, Gema Parasti; Sholihah, Walidatush; Novianty, Inna; Fathonah, Lathifunnisa; Marcelita, Faldiena; Siskandar, Ridwan; Ariyanto, Dodik; Widodo, Bayu; Setiawan, Aep; Firdaus, Naufal Rizqullah
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 3 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 3, December 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.103.06

Abstract

Dissolved Oxygen (DO) is an important parameter for maintaining water quality in aquaculture systems. The accuracy of DO sensors significantly affects the reliability of Internet of Things (IoT)-based monitoring systems. This study aimed to calibrate the DO sensor using a two-point calibration method and evaluate the accuracy of the sensor readings compared with those of a reference device (standard DO meter). A key novelty of this study lies in its multi-media calibration, performed directly on six distinct aquaculture water types, providing field-realistic validation conditions not commonly explored in previous studies. Furthermore, the accuracy of the calibrated sensor is evaluated quantitatively using MAE, RMSE, and percentage deviation to ensure rigorous performance assessment. The system was developed using an ESP32 microcontroller, DO sensor (SEN0237), DS18B20 temperature sensor, and ADS1115 ADC module. Testing was performed on six types of aquaculture water media and compared with a standard DO meter using a comparative approach. In total, n = 6 field measurement points (one stabilized reading per water medium) were used to compute MAE, RMSE, and percentage deviation. The comparison results showed that the calibrated sensor had high accuracy, with a Mean Absolute Error (MAE) of 0.1083 mg/L and a Root Mean Square Error (RMSE) of 0.2654 mg/L. Significant deviations occurred only in one type of water medium, whereas the other five showed results consistent with the reference device, indicating stable sensor readings. These findings confirm that proper calibration can improve the accuracy and reliability of IoT systems used for water-quality monitoring. Regular calibration is required to maintain the sensor performance, particularly for long-term use in dynamic aquaculture water environments.
Dashboard Web Real-Time untuk Monitoring Sortasi Biji Kopi Berbasis Computer Vision Caesar, Muhammad Rizky; Rahayu, Baracahya Panata Cendikia; Nugroho, Gesit Tri; Al-Attas, Ahmad Farrell Raafii Alaiyya; Marcelita, Faldiena; Novianty, Inna; Ariyanto, Dodik
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 6 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i6.10120

Abstract

Abstrak - Sortasi biji kopi pasca-sangrai merupakan tahapan krusial dalam quality control untuk menjamin konsistensi produk. Namun, proses manual rentan terhadap subjektivitas dan ketidakkonsistenan, khususnya bagi UMKM kopi dengan keterbatasan infrastruktur. Penelitian ini mengembangkan PiKopi, sistem monitoring sortasi terintegrasi dengan dashboard web untuk visualisasi dan pengambilan keputusan berbasis data. Sistem mengintegrasikan tiga komponen utama: (1) modul deteksi cacat berbasis Convolutional Neural Network (CNN) pada perangkat edge computing Raspberry Pi untuk identifikasi real-time, (2) backend API RESTful berbasis Flask dengan database PostgreSQL untuk manajemen data klasifikasi, dan (3) dashboard web responsif berbasis React.js untuk visualisasi data real-time. Arsitektur API-driven memisahkan frontend dan backend, memungkinkan akses monitoring dari berbagai perangkat tanpa instalasi aplikasi. Dashboard menampilkan statistik sortasi real-time, grafik distribusi kualitas, riwayat batch, dan log aktivitas dengan interface yang user-friendly. Model CNN mencapai akurasi deteksi 92% dengan sensitivity dan specificity yang seimbang. Hasil pengujian fungsional menunjukkan sistem mampu melakukan klasifikasi otomatis dan menyajikan data sortasi secara real-time kepada pengguna. Sistem ini memfasilitasi pengambilan keputusan berbasis data, meningkatkan konsistensi mutu produk, serta mengurangi ketergantungan pada inspeksi visual manual bagi pelaku UMKM kopi.Kata kunci: dashboard web; monitoring real-time; sortasi kopi pasca-sangrai; quality control; arsitektur API-driven; Abstract - Post-roasting coffee bean sorting is a crucial stage in quality control to ensure product consistency. However, manual sorting processes are prone to operator subjectivity and inconsistency, particularly for small and medium enterprises (SMEs) with limited infrastructure. This research develops PiKopi, an integrated coffee sorting monitoring system with a web dashboard for visualization and data-driven decision making. The system integrates three main components: (1) a defect detection module based on Convolutional Neural Network (CNN) on Raspberry Pi edge computing devices for real-time identification, (2) a RESTful API backend based on Flask with PostgreSQL database for classification data management, and (3) a responsive web dashboard based on React.js for real-time data visualization. The API-driven architecture separates frontend and backend, enabling monitoring access from various devices without application installation. The dashboard displays real-time sorting statistics, quality distribution charts, batch history, and activity logs with a user-friendly interface. The CNN model achieves detection accuracy of 92% with balanced sensitivity and specificity. Functional testing results demonstrate that the system successfully performs automated classification and presents real-time sorting data to users. This system facilitates data-driven decision making, improves product quality consistency, and reduces reliance on manual visual inspection for coffee SMEs. Keywords: web dashboard; real-time monitoring; post-roast coffee sorting; quality control; API-driven architecture;
Co-Authors A'isy, Nabil Arif Agus Buono Al-Attas, Ahmad Farrell Raafii Alaiyya Ana Turyanti Aprilianti, Dhila BAYU WIDODO Caesar, Muhammad Rizky Dany Fadhilah DODIK ARIYANTO Endang Purnama Giri Ezer, Angga Eben Fathonah, Lathifunnisa Fernando, Brilliant Sandynigy Firdaus, Naufal Rizqullah Hendriana, Andri Hikmah Rahmah Ima Kusumanti Inna Novianty Inyasdi Kahvi, Muhamad Restu Kauripan, Edmund Banyu Khabibah, Dea Ummul Khairunisa, Aulia Khairunnisa Hayyu Kusnadi Khonza Izzati Maulidan, Muhammad Hafizh Mindara, Gema Parasti Muhammad, Fadhel Naufal, Fawwaz Nelvi, Annisa Amanda Novianty, Inna Novianty, Inna Novianty Noviyanti, Inna Nugroho, Gesit Tri Nur Aziezah Nur Aziezah Olivia Sekar Nindia Paramitadevi, Yudith Vega Rahayu, Baracahya Panata Cendikia Rahmah, Hikmah Ridwan Siskandar Rumondang, Antonya Safitrah, Tiara Salsabila Diba Cahyani Satrio, Muchammad Alifandino sayekti, ayutyas Setiawan, Aep Sholihah, Walidatush Sinaga, Antonya Rumondang Walidatush Sholihah