Article Per Year (5 Year)
p-Index From 2021 - 2026
3.334
P-Index
This Author published in this journals
All Journal BERKALA FISIKA Jurnal Pendidikan Matematika dan IPA Jurnal Teknik Kimia USU Jurnal Online Mahasiswa (JOM) Bidang Keguruan dan Ilmu Pendidikan Jurnal Transformatika MPI (Media Pharmaceutica Indonesiana) Jurnal Penelitian Pembelajaran Fisika E-Dimas: Jurnal Pengabdian kepada Masyarakat Sinkron : Jurnal dan Penelitian Teknik Informatika JIKO (Jurnal Informatika dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknologi Informasi dan Terapan (J-TIT) Bubungan Tinggi: Jurnal Pengabdian Masyarakat Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Pijar MIPA Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Adopsi Teknologi dan Sistem Informasi Unnes Science Education Journal Scientific Journal of Informatics SWAGATI: Journal of Community Service JIPFRI (Jurnal Inovasi Pendidikan Fisika dan Riset Ilmiah) Berita Biologi
Mega Novita
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

Published : 28 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 28 Documents
Search

 1   2   3 
ANTIOXIDANT ACTIVITY PROFILING OF RED BAJAKAH TAMPALA (Spatholobus littoralis Hassk) FRACTIONS USING THE DPPH RADICAL SCAVENGING METHOD Amanda, Nathasya Gracya; Sari, Ghani Nurfiana Fadma; Novita, Mega; Marlina, Dian
Berita Biologi Vol 24 No 3 (2025): Berita Biologi
Publisher : BRIN Publishing (Penerbit BRIN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/berita_biologi.2025.11322

Abstract

Indonesia’s rich biodiversity harbors numerous plants with medicinal properties, including Red Bajakah Tampala (Spatholobus littoralis Hassk.), which has long been used in traditional medicine for its therapeutic benefits. Despite its promising ethnomedicinal reputation, scientific validation of its antioxidant potential remains limited. This study aims to evaluate the antioxidant properties of Red Bajakah Tampala and identify key bioactive compounds responsible for its bioactivity. The plant's antioxidant capacity was assessed using the DPPH assay, and the chemical composition was analyzed through phytochemical screening and thin-layer chromatography (TLC). The ethyl acetate fraction exhibited the strongest antioxidant activity, with an IC₅₀ value of 12.87 ppm, followed by the n-hexane fraction (24.08 ppm) and the water fraction (57.23 ppm). Phytochemical screening revealed the presence of flavonoids, tannins, triterpenoids, phenols, and saponins, which contribute to the plant's antioxidant effects. These findings provide scientific evidence supporting the traditional use of Red Bajakah Tampala as a natural antioxidant, with implications for its potential use in therapeutic and cosmetic applications. Further research into the molecular mechanisms and practical applications of Bajakah-based formulations is recommended.
Ultra-Low-Cost Hybrid OCR–LLM Architecture for Production Grade E-KTP Extraction Saputro, Anjar Tiyo; Herlambang, Bambang Agus; Novita, Mega
Scientific Journal of Informatics Vol. 12 No. 4: November 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i4.38200

Abstract

Purpose: The purpose of this study is to be able to avoid limitations of inexpensive ID card data extraction services and preserve privacy, which can simultaneously achieve reliable operation even under an environment with minimum infrastructure, in particular if no dependency on GPU-based servers are required. Method: The proposed approach is a microservice pipeline with three stages: (1) local lightweight pre-processing on devices, (2) Tesseract CPU-based OCR. js, (3) fast text tokenization through a small premature external LLM. The system is developed as TypeScript backend utilizing the Hono framework with all image processing taking place locally in order to keeping user data private. Result: The result of the experimental evaluations with real ID card samples is that the system can run stably in low-performance VPS (1 vCPU, 1 GB RAM) with operation cost approximately IDR 2.5047 per extraction process and its accuracy level is acceptable for use in a production environment. Moreover, the results indicate that system latency is dominated by LLM inference at the cloud. Novelty: The main contribution and novelty of this study is that we demonstrate, for the first time, a cost-effective (privacy-preserving) OCR-LLM hybrid pipeline without demanding expensive GPU models at large scale which makes our system suitable under limited storage and resource constraints on-premises or edge environments in small organizations including micro-SaaS services.
Anti-Acne Activity of Robusta Green Coffee Bean Extract against Cutibacterium acnes Putri, Cinthiya Ekwinta; Puspitasari, Ismi; Novita, Mega; Marlina, Dian
MPI (Media Pharmaceutica Indonesiana) Vol. 7 No. 2 (2025): DECEMBER
Publisher : Fakultas Farmasi, Universitas Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24123/mpi.v7i2.7857

Abstract

Acne vulgaris, a common chronic skin disorder, is primarily caused by the overgrowth of Cutibacterium acnes and often treated with synthetic agents that may cause side effects and resistance. The increasing demand for therapeutics with improved safety profiles and natural alternatives has encouraged the exploration of herbal remedies, including robusta green coffee beans (Coffea canephora). This study aimed to evaluate the anti-acne activity of robusta coffee bean ethanol extract against C. acnes. The extract was prepared through maceration and subsequently evaluated using to phytochemical screening, thin layer chromatography, and in vivo testing on New Zealand rabbits. Results confirmed the presence of flavonoids, alkaloids, tannins, steroids, and triterpenoids. In vivo assays demonstrated that the 75% extract concentration achieved a 96.69% reduction of acne lesions, comparable to the positive control at 99.35%, while lower concentrations showed moderate activity. These findings highlight the potential of robusta coffee bean extract as a promising natural anti-acne agent. The study implies that robusta extract can be further developed into herbal-based dermatological formulations, although future research should focus on isolating active compounds and conducting clinical trials for broader application.
Implementation and Comparative Analysis of CNN and Transfer Learning Models (EfficientNetB0, MobileNetV2, and ResNet50) for Rice Leaf Disease Detection Based on Digital Images Utami, Tri Wahyu; Novita, Mega; Latifa, Khoiriya
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11616

Abstract

Rice leaf diseases significantly reduce agricultural productivity, making early and accurate detection essential, particularly in rice-producing regions such as Indonesia. This study proposes an automated rice leaf disease detection system based on Convolutional Neural Networks (CNN) and transfer learning. The dataset, obtained from the Mendeley Data Repository, consists of 6,889 images classified into eight categories: Bacterial Leaf Blight, Brown Spot, Healthy Rice Leaf, Leaf Blast, Leaf Scald, Narrow Brown Leaf Spot, Rice Hispa, and Sheath Blight. The dataset was divided into 70% training, 15% validation, and 15% testing. A baseline CNN model and three pre-trained models—EfficientNetB0, MobileNetV2, and ResNet50—were evaluated using accuracy, precision, recall, F1-score, and confusion matrix analysis. The baseline CNN achieved a test accuracy of 48.26%, while EfficientNetB0 achieved 58.41%. In contrast, MobileNetV2 and ResNet50 demonstrated significantly better performance, with test accuracies of 79.98% and 76.60%, respectively. MobileNetV2 exhibited the most balanced performance across all classes, showing superior generalization capability and computational efficiency. The best-performing model was integrated into a Streamlit-based application, enabling real-time rice leaf disease detection through image upload. The results confirm that transfer learning substantially improves classification accuracy and robustness compared to conventional CNNs. This study highlights the potential of lightweight deep learning models for practical implementation in smart agriculture systems and provides a reliable solution for automated rice disease detection in real-world conditions.
Transformasi UMKM Desa Doplang melalui Koperasi Digital, Produk Wellness, IoT Smart Watering, dan Branding Wisata Novita, Mega; Senowarsito, Senowarsito; Hermana, Rifki; Sutomo, Sutomo
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 6 No. 2 (2025): ADMA: Jurnal Pengabdian dan Pemberdayaan Mayarakat: In-Progress
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v6i2.5726

Abstract

Desa Doplang di Kabupaten Semarang memiliki potensi besar pada komoditas bunga sedap malam, namun pemanfaatannya selama ini terbatas pada produk hias dengan nilai ekonomi rendah. UMKM setempat menghadapi kendala inovasi produk, akses pasar, dan kelembagaan ekonomi yang lemah. Program pengabdian multi-tahun sebelumnya (2023–2024) telah menghasilkan pelatihan dasar dan diversifikasi produk awal, tetapi aspek keberlanjutan kelembagaan, penerapan teknologi hemat sumber daya, dan strategi branding desa wisata belum terwujud optimal. Artikel ini bertujuan mendeskripsikan transformasi UMKM Desa Doplang pada tahun 2025 sebagai puncak program pemberdayaan melalui penguatan koperasi digital, pengembangan produk wellness, dan inovasi IoT smart watering. Kegiatan dilaksanakan dengan pendekatan partisipatif melibatkan UMKM, PKK, Karang Taruna, Pokdarwis, dan BumDes, melalui tahapan sosialisasi, pelatihan, penerapan teknologi, pendampingan, dan evaluasi. Hasil kegiatan menunjukkan terbentuknya koperasi digital SIRATIH dengan anggota awal pelaku UMKM desa sebagai wadah distribusi dan transaksi kolektif, peluncuran tiga produk wellness baru (lilin aromaterapi, body butter, dan lulur) yang memperluas portofolio UMKM, serta implementasi prototipe IoT smart watering yang mampu mengurangi penggunaan air hingga sekitar 20% pada lahan uji coba. Selain itu, booklet promosi wisata Jendela Doplang diterbitkan untuk memperkuat citra desa sebagai destinasi wisata berbasis wellness. Program ini membuktikan bahwa integrasi kelembagaan digital, inovasi produk, dan penerapan teknologi tepat guna mampu memperkuat daya saing UMKM sekaligus mendorong keberlanjutan ekonomi lokal. Implikasi lebih luas dari program ini adalah perlunya dukungan lintas sektor untuk mempercepat sertifikasi produk dan replikasi model ke desa lain yang memiliki potensi serupa.
ANALYSIS OF HIGH SCHOOL STUDENTS’ CRITICAL AND COMPUTATIONAL THINKING SKILLS IN THERMOCHEMISTRY Wibowo, Aries Setyo; Patonah, Siti; Novita, Mega
Jurnal Pendidikan Matematika dan IPA Vol. 17 No. 1 (2026): January 2026
Publisher : Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jpmipa.v17i1.104115

Abstract

Critical and computational thinking skills are two essential 21st-century competencies that are highly relevant in chemistry education, particularly in thermochemistry topics that require deep conceptual understanding and scientific reasoning. This study aims to provide an in-depth analysis of the profile of high school students’ critical and computational thinking skills in thermochemistry. A descriptive quantitative method was employed, involving 36 eleventh-grade students from SMAN 1 Kedungwuni. The instruments consisted of diagnostic tests based on Facione’s and Brennan & Resnick’s indicators, classroom observations, semi-structured interviews with teachers and students, and student perception questionnaires. The analysis revealed that students’ critical thinking skills were at a moderate level, with the highest score in interpretation (65.3%) and the lowest in evaluation (58.1%) and explanation (59.4%). Similarly, computational thinking skills were also in the moderate category, with the highest score in decomposition (63.2%) and the lowest in abstraction (57.3%). Observational and interview data indicated that learning was still dominated by conventional lecture methods with limited exploratory activities that promote higher-order thinking. However, students expressed strong motivation toward the use of more interactive learning media, such as websites or Android-based applications. In conclusion, these findings underscore the need for innovative, contextual, and technology-based learning media to enhance students’ critical and computational thinking skills and better align chemistry education with 21st-century learning demand.
Adaptasi Pedagogik Mahasiswa Calon Guru Indonesia dalam Pembelajaran di Sekolah Islam Thailand Selatan Novita, Mega; Priyatno, Wawan; Prasetiyo, Prasetiyo; Hidayat, Nur; Munawar, Muniroh; Maetam, Adul
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 17, No 2 (2026): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v17i2.28098

Abstract

Program Praktik Pengalaman Lapangan (PPL) Internasional merupakan salah satu bentuk pengabdian yang bertujuan meningkatkan kompetensi pedagogik mahasiswa calon guru melalui pengalaman mengajar di lingkungan pendidikan multikultural. Pelaksanaan program di sekolah Islam Thailand Selatan menghadapi berbagai tantangan, seperti perbedaan bahasa, budaya belajar, dan karakteristik peserta didik yang menuntut mahasiswa untuk melakukan adaptasi pedagogik. Artikel ini bertujuan mendeskripsikan pelaksanaan program serta mengevaluasi luaran yang dihasilkan terhadap proses pembelajaran di sekolah mitra. Metode yang digunakan berupa observasi, praktik mengajar, pendampingan oleh guru pamong, serta refleksi dan evaluasi selama pelaksanaan program. Hasil kegiatan menunjukkan bahwa program memberikan dampak positif terhadap kualitas pembelajaran, ditunjukkan oleh peningkatan partisipasi peserta didik dari 62% menjadi 88%, keaktifan peserta didik dari 58% menjadi 86%, pemahaman materi dari 60% menjadi 84%, serta penggunaan media pembelajaran dari 40% menjadi 90%. Selain itu, mahasiswa mampu mengembangkan kemampuan adaptasi pedagogik melalui penyesuaian strategi pembelajaran, komunikasi lintas budaya, pengelolaan kelas, dan pemanfaatan media pembelajaran sesuai dengan karakteristik sekolah mitra. Program ini memberikan manfaat bagi mahasiswa maupun sekolah mitra serta berpotensi menjadi model pengembangan kompetensi pedagogik dalam mendukung internasionalisasi pendidikan guru.
CNN Implementation in Progressive Web App for Automatic Garbage Classification using TensorFlow.js Eka Setyabudi; Noora Qotrun Nada; Mega Novita
Jurnal Teknologi Informasi dan Terapan Vol 12 No 2 (2025): December
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v12i2.458

Abstract

The substantial and continuously increasing volume of global waste has become a critical environmental challenge, exacerbating the inherent inefficiency of conventional manual sorting techniques. This research addresses this problem by developing and evaluating an automated waste classification system using Convolutional Neural Networks (CNN), specifically the VGG16 architecture, integrated into a Progressive Web App (PWA) to enhance accessibility and sorting efficiency. Our primary goal is to deliver an intelligent, lightweight, and cross-platform solution capable of performing client-side inference on diverse devices. The VGG16 model was retrained using transfer learning on a validated public dataset of 10,365 images, comprising two classes (organic and inorganic waste). The trained model was converted to a browser-compatible format, TensorFlow.js, and deployed within the PWA framework which utilizes Service Workers for offline capabilities. Despite the significant challenge posed by the VGG16 model's large size, the system successfully performed client-side inference by prioritizing GPU acceleration and achieved 0.94 overall accuracy on the test dataset2. This result, supported by high F1-scores for both waste categories, confirms that deploying high-accuracy CNN models at the edge using PWA and TensorFlow.js is a feasible and promising strategy for practical, technology-based waste management and environmental education.
Co-Authors AA Sudharmawan, AA Amanda, Nathasya Gracya Anggraini, Natasya Dila Putri Aris Tri Jaka Harjanta, Aris Tri Bambang Agus Herlambang, Bambang Desi Purwaningsih Dwi Saputro, Nugroho Eka Setyabudi Febrian Murti Dewanto Febrihastatiwi, Dinda Fenny Roshayanti Ferdy Semuel Rondonuwu Ghani Nurfiana Fadma Sari Hayat, M. Syaipul Hermana, Rifki Hukmi Hukmi, Hukmi Intan Indiati Jubhar Mangimbulude Kusumo, Haryo Latifa, Khoiriya Maetam, Adul Mariyana, Ekanata Desi Sagita Marlina, Dian Maulana, Novan Mawardi, Dimas Putra Muhammad Syaipul Hayat Muniroh Munawar Noora Qotrun Nada Noora Qotrun Nada, Noora Qotrun Nugroho Dwi Saputro Nugroho Dwi Saputro, Nugroho Dwi Nur Hidayat Nur Khoiri Nur Latifah Dwi Mutiara Sari Pramukantoro, Ganet Eko Prasetiyo Prasetiyo Priyanto, Widodo Priyatno, Wawan Puspitasari, Ismi Putri, Cinthiya Ekwinta Renaldy, Ramadhan Rukmi, Pramastuti Adiar Salwa, Faiza Rulla Saputro, Anjar Tiyo Setyoningsih Wibowo Siti Patonah Siwi, Andini Prabandaru Sri Wahyuni Sutomo Sutomo Utami, Tri Wahyu Waliyansyah, Rahmat Robi Wibowo, Aries Setyo