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Novianty, Inna
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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.
ANALISIS DAN PERANCANGAN SISTEM INFORMASI LAYANAN TES KEPRIBADIAN SAINTARA BERBASIS WEBSITE Putri, Zaskia Alyssa; Fitrah, Muhammad; Pandara, Banu; Izzaturrahman, Haitsam; Maheswari, Vezajiva Ariesta; Wicaksono, Aditya; Novianty, Inna
Djtechno: Jurnal Teknologi Informasi Vol 6, No 3 (2025): Desember
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i3.7988

Abstract

Layanan tes kepribadian berbasis web menjadi salah satu solusi untuk membantu pengguna memahami jati diri secara mudah. Namun, masih banyak platform yang kurang informatif, tidak interaktif, serta tidak menyediakan hasil analisis yang komprehensif. Penelitian ini bertujuan untuk mengembangkan sebuah website layanan tes kepribadian SAINTARA yang menyediakan layanan tes kepribadian, informasi karakter kepribadian dan rekomendasi pengembangan diri. Metode pengembangan yang digunakan adalah prototype dengan tahapan communication, quick plan, modeling quick design, construction of prototype, deployment delivery & feedback. Website dirancang dengan hak akses yang berbeda untuk individual customer, admin customer, dan admin SAINTARA. Fitur utama yang dikembangkan meliputi proses registrasi dan login, pelaksanaan tes kepribadian, penyajian hasil tes kepribadian, serta dashboard admin untuk mengelola data pengguna. Website yang dihasilkan berhasil memfasilitasi proses layanan tes kepribadian yang cepat dan terstruktur, memungkinkan individual customer mendapatkan hasil tes kepribadian secara langsung. Pengembangan website SAINTARA menjadi solusi efektif untuk mengatasi kendala keterbatasan partisipasi pengguna, sehingga mendukung upaya keberlanjutan layanan tes kepribadian sebagai sarana pengembangan diri di era digital.
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;
Artificial Neural Network-Based Classification of Water Quality Status in Ornamental Fish Farming Using IoT Sensor Data Aziezah, Nur; Sholihah, Walidatush; Marcelita, Faldiena; Novianty, Inna; Hendriana, Andri; Kusumanti, Ima
Current STEAM and Education Research Vol. 3 No. 3 (2025): Current STEAM and Education Research, Volume 3 Issue 3, December 2025
Publisher : MJI Publisher by PT Mitra Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58797/cser.030302

Abstract

Water quality plays an important role in sustainable agriculture. Water quality also affects the quality and quantity of fishery production. In ornamental fish cultivation, water quality influences not only production, but also the shape and color of the fish. To achieve optimal results, water quality parameters need to be maintained. Manually monitoring water quality parameters faces many challenges such as being time-consuming and not providing real-time data. This study investigated the application of Artificial Neural Networks (ANNs) in classifying water quality status. This status is based on data collected using sensors in an Internet of Things (IoT)-based monitoring system. The dataset comprised five key parameters: pH, temperature, ammonia, total dissolved solids (TDS), and total suspended solids (TSS). This data was collected from aquariums cultivating the Denison barb (Sahyadria denisonii). Data preprocessing was performed using feature standardization. This aims to improve model performance. The ANN model was constructed with two hidden layers (32 and 16 neurons). This model was trained using the Adam optimizer, with categorical cross-entropy as the loss function. The dataset was divided into 80% for training and 20% for testing. The trained ANN model achieved an accuracy of 99.95%. It has low false-positive and false-negative rates. These results demonstrate the effectiveness of ANN in predicting water quality status using sensor-based data. This suggests its potential for real-time monitoring and decision-making support in small-scale ornamental fish aquaculture.
Pemberdayaan Masyarakat melalui Penerapan Pirolisis Berbasis Internet of Things untuk Peningkatan Kapasitas Pengelolaan Sampah Plastik di Kelurahan Mulyaharja, Bogor Fathonah, Lathifunnisa; Novianty, Inna; Parasti, Gema; Ariyanto, Dodik; Marcelita, Faldiena; Siskandar, Ridwan; Widodo, Bayu; Irmansyah, Irmansyah; Taya, Liora; Nur Azizah, Laila
Jurnal Abdi Masyarakat Indonesia Vol 6 No 1 (2026): JAMSI - Januari 2026
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jamsi.2496

Abstract

Kelurahan Mulyaharja, Kota Bogor, menghadapi permasalahan tingginya volume sampah plastik rumah tangga yang belum terkelola dengan baik. Sebagian sampah dibakar atau dibuang ke lingkungan sekitar, sehingga menimbulkan pencemaran dan risiko kesehatan masyarakat. Program pengabdian ini menerapkan teknologi pirolisis berbasis Internet of Things (IoT) untuk mengonversi sampah plastik menjadi bahan bakar alternatif melalui pendekatan participatory community-based implementation. Metode kegiatan meliputi analisis kebutuhan, perancangan dan pembuatan alat, pelatihan, serta pendampingan operasional bagi warga Kelurahan Mulyaharja. Hasil pengabdian menunjukkan bahwa prototipe pirolisis berbasis IoT berhasil beroperasi stabil pada skala komunitas. Sebanyak lebih dari 70% warga peserta mampu mengoperasikan alat secara mandiri sesuai prosedur keselamatan kerja. Hasil survei menunjukkan 76% warga sangat peduli terhadap lingkungan, dan 86% menyatakan kegiatan ini memberikan manfaat nyata. Selain itu, terjadi penurunan praktik pembakaran dan pembuangan sampah ke sungai, serta mulai terbentuk kelompok pengelola alat berbasis masyarakat. Produk minyak hasil pirolisis telah dimanfaatkan sebagai bahan bakar alternatif untuk peralatan sederhana. Program ini memperkuat kapasitas masyarakat dalam pengelolaan sampah, mendukung keberlanjutan teknologi berbasis komunitas, serta mendorong koordinasi antara warga, pengurus RW, dan kelurahan.
Co-Authors Achmad, Rafi Febrian Aditya Wicaksono Al-Attas, Ahmad Farrell Raafii Alaiyya Aziz, Thufeil Muhammad Nur BAYU WIDODO Caesar, Muhammad Rizky Chairunisa, Dwi Yulinar Chairunnisa, Dwi Yulinar Chusnu, Muhamad Dewanto, Muhammad Arif Bagus DODIK ARIYANTO Endang Purnama Giri Erviyana, Nadia Fadhilah, Naufal Kamil Fahlevy, Annaliah Fathonah, Lathifunnisa Firdaus, Naufal Rizqullah Firdayanti, Firdayanti Ghani, Muhammad Rafi Ari Hawali, Wafi Hendriana, Andri Heriyanto Syafutra Ima Kusumanti Irmansyah . Izzaturrahman, Haitsam Ka-sasi, R.I. Damai Khafiyyan, Farih Maheswari, Vezajiva Ariesta Marcelita, Faldiena Mindara, Gema Parasti Muchlisinia, Newi Muhammad Fitrah, Muhammad Nisa, Afifah Rodhiyatun Nugroho, Gesit Tri Nur Aziezah Nur Azizah, Laila Pandara, Banu Parasti, Gema Perdhana, Mochammad Bintang Prayoga, Dwi Putri, Zaskia Alyssa Qonita, Vellisya Afifa Rahayu, Baracahya Panata Cendikia Rahmadaniar, Ihda Ramadhan, Herlambang Nurasyid Ramadhani, Ghani Trie Aqeela Rayhan, Rayhan Ridwan Siskandar Riyanti, Ade Rumondang, Antonya Sativa, Oktaryza sayekti, ayutyas Setiawan, Aep Shaefullah, Amien Shaum Shaum, Amien Sholihah, Walidatush Sinaga, Antonya Rumondang Stefanny, Arlyn Sugiana, Lili Rahmawati Tambunan, Muhammad Rafid Habibi Taya, Liora