Article Per Year (5 Year)
p-Index From 2021 - 2026
4.232
P-Index
This Author published in this journals
All Journal UG Journal Gontor AGROTECH Science Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Agrosains: Jurnal Penelitian Agronomi Jurnal Biologi Tropis JURNAL PERTANIAN PRESISI (JOURNAL OF PRECISION AGRICULTURE) JURTEKSI Jurnal Ilmiah Sinus Jurnal Pembelajaran dan Biologi Nukleus Jurnal Bakti Masyarakat Indonesia Jurnal Teknik Informatika (JUTIF) Akar (Aspirasi Karya Anak Rimba) : Jurnal Ilmiah Hutan & Kehutanan Agroradix : Jurnal Ilmu Pertanian International Journal on Food, Agriculture and Natural Resources (IJFANRES) Jurnal Pengabdian Kepada Masyarakat Darma Saskara ETHOS: Jurnal Penelitian dan Pengabdian kepada Masyarakat Jurnal Pengabdian Masyarakat SAPANGAMBEI MANOKTOK HITEI
Paranita Asnur
Universitas Gunadarma
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Social Sciences Other

Published : 24 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 24 Documents
Search

 1   2   3 
The Influence of Shade on the Growth and Production of Butterfly Pea Plants (Clitoria ternatea) Asnur, Paranita; Kalsum, Ummu; Kanny, Putri Irene; Yuliani, Siska
International Journal on Food, Agriculture and Natural Resources VOL 5, NO 2 (2024): IJ-FANRES
Publisher : Food, Agriculture and Natural Resources - NETWORKS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46676/ij-fanres.v5i2.327

Abstract

Butterfly pea (Clitoria ternatea L.) is a medicinal plant known for its anthocyanin pigment content, which imparts a blue color to its flowers. This study aimed to evaluate the influence of shading on butterfly pea flower growth and production. The research design utilized a randomized complete block design (RCBD) for shading treatments. We replicated each treatment level four times, resulting in 20 experimental units, each containing four plants, for a total population of 80 plants. We conducted the experiment at the Experimental Garden of Gunadarma University Campus F7, implementing shade nets at different intensity levels (55%, 65%, 75%, and 85%), along with a control treatment without shading. We made observations on various plant growth parameters such as leaf count, plant length, days to first flower appearance, flower count, fresh weight, and dry weight. The results indicated that shading significantly influenced butterfly pea plants' growth. Plants without shading tended to exhibit better growth in several parameters, such as increased leaf count, higher plant length, and earlier days to first flower appearance. These findings underscore the importance of sunlight in supporting the growth and production of butterfly pea plants. Therefore, careful consideration of shade management is essential in agricultural practices to ensure optimal growth and maximum yield from butterfly pea plants.
Assistance in Urban Farming for the Cultivation of Chili Peppers in a Greenhouse Based on Internet of Things Systems Aisyah; Asnur, Paranita
ETHOS: Jurnal Penelitian dan Pengabdian kepada Masyarakat Vol. 13 No. 1 (2025): (Januari, 2025) Ethos: Jurnal Penelitian Dan Pengabdian Kepada Masyarakat (Sai
Publisher : UPT Publikasi Ilmiah UNISBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/ethos.v13i1.4856

Abstract

Urban farming has become an innovative solution to address landlimitations in urban areas while also enhancing local food security. This article discusses the cultivation of large chili peppers (Capsicum annuum L.) in the Greenhouse of Ulul Ilmi Islamic Boarding School, East Jakarta, which implements Internet of Things (IoT) technology in its Smart Farming system. This program aims to enhance the efficiency and productivity of chili cultivation through guidance and the implementation of advanced technologies, such as automated irrigation systems, greenhouse temperature monitoring, and maintenance practices like fertilization. The assistance results show that the implementation of IoT can improve the efficiency of water, fertilizer, and energy usage, as well as optimize the growth of red chili plants. This technology enables accurate monitoring and more responsive crop management in response to changes in environmental conditions, allowing chili plants to grow healthier and more productively. We expect this development to serve as a model for replication in various other urban locations, thereby supporting sustainable agriculture and enhancing food security in urban environments.
The Application of Liquid Organic Fertilizer Increasing the Productivity of Pakchoy Plants (Brassica rapa L.) in Soil with Low Nutrient Content Isnainy, Dyon Rahman; Asnur, Paranita; Istiqlal, Muhammad Ridha Alfarabi; Kalsum, Ummu
Jurnal Biologi Tropis Vol. 25 No. 2 (2025): April-Juni
Publisher : Biology Education Study Program, Faculty of Teacher Training and Education, University of Mataram, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbt.v25i2.8972

Abstract

Organic farming plays a very important role in maintaining environmental balance because it can reduce the use of harmful synthetic chemicals. This LOF is considered capable of enhancing soil fertility and supporting plant growth, while simultaneously reducing waste from the aquaculture sector. This study aims to evaluate the effect of liquid organic fertilizer (LOF) from catfish pond wastewater on the productivity of pakcoy (Brassica rapa L.) plants grown in soil with low nutrient content. The research was conducted in the experimental field of Universitas Gunadarma, East Jakarta, using 18 combinations of POC treatments with various concentrations and five varieties of pakcoy. Data were analyzed using the F-test to determine the overall treatment effect, followed by the Duncan Multiple Range Test (DMRT) at a 5% significance level to compare between treatments. The research results show that the application of POC from catfish pond wastewater has a positive effect on the growth of pakcoy compared to the control. A POC concentration of 0.75 ml/L yielded the best results in most parameters, including plant height, number of leaves, as well as leaf length and width. Although not all treatment combinations yielded significant results, the use of POC generally shows great potential in increasing the productivity of pakcoy plants. POC from catfish pond wastewater is not only effective as an organic fertilizer but also supports sustainable agriculture by reducing the negative impact of aquaculture waste on the environment. This research recommends POC as an environmentally friendly fertilizer alternative to improve agricultural yields, especially in areas with low nutrient content, through gradual soil quality improvement.
Pengembangan Aplikasi Berbasis Website untuk Deteksi Hama pada Daun Sawi Menggunakan Metode Deep Learning NASNetMobile dan Model Sequential Pratiwi, Swelandiah Endah; Kholish, Iqbal Nur; Pernadi, Dody; Asnur, Paranita
Jurnal Ilmiah SINUS Vol 23, No 2 (2025): Vol. 23 No. 2, Juli 2025
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v23i2.992

Abstract

Green mustard (Brassica rapa var. parachinensis) is one of the important horticultural commodities in Indonesia with high economic value, but its production has declined due to leaf pest attacks such as armyworms, Plutella larvae, and aphids. Manual pest detection, which is time-consuming and prone to errors, poses a major challenge in effective early control. This research aims to develop a pest detection system on mustard greens leaves based on a website using the NASNetMobile deep learning model and sequential architecture, to provide a practical, accurate, and easily accessible solution for farmers. The research method includes the collection of 1000 images of mustard greens from the Kaggle dataset, preprocessing with augmentation and normalization, development of a CNN model with two architectures (NASNetMobile and sequential), evaluation of model performance, and implementation of a Flask-based prototype for web-based testing. The training results show that the best architecture (NASNetMobile + sequential) achieved a validation accuracy of 94% and a validation loss of 0.1160 in 14 seconds of training. Further testing using 50 new images showed an overall detection accuracy of 96%, with 100% accuracy on pest-infected leaves and 92% on pest-free leaves. The conclusion of this research indicates that the web-based detection system using the NASNetMobile and sequential models is effective in supporting pest management on green mustard plants. This system provides easy access, quick response, and high accuracy, although further development with a more diverse dataset and field testing are needed to improve reliability in real conditions across various agricultural environments.
KAJIAN POTENSI DAN STRATEGI IMPLEMENTASI AGROFORESTRI DI SEMPADAN SUNGAI PESANGGRAHAN Asnur, Paranita; Aisyah, Aisyah; Wiseno, Elbi; Gunarto, Thomas Yuni; Suryanto, Doddy Ari
Jurnal Bakti Masyarakat Indonesia Vol. 8 No. 1 (2025): Jurnal Bakti Masyarakat Indonesia
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jbmi.v8i1.34457

Abstract

The Pesanggrahan River riparian zone holds significant potential for development as an agroforestry area that supports environmental conservation and ecology-based agrotourism. However, the area faces several challenges, including the absence of clearly defined boundaries, environmental degradation caused by human activities, and a lack of appropriate plant species recommendations for sustainable development. This Community Service Program (PkM) aims to assess the existing conditions of the area, conduct boundary mapping, and provide recommendations for agricultural and forestry plant species that support both ecological conservation and economic value for local communities. The methods used in this program include site surveys to identify vegetation conditions, soil characteristics, and environmental issues; territorial mapping using drones and manual boundary marking; and interviews with local communities and stakeholders to understand their perceptions and needs regarding agroforestry and agrotourism. The results indicate that the area has already been planted with various forest trees and fruit-bearing plants, such as acacia, durian, jackfruit, avocado, and banana, as well as agricultural crops like cassava and vegetables. Additionally, boundary mapping was conducted twice to determine the designated working area for a more structured implementation of agroforestry. Based on the findings, it is recommended to implement an agroforestry system by planting forest trees and perennial fruit crops along the riverbanks to reduce erosion and strengthen the riparian ecosystem. The implementation of agroforestry is expected not only to contribute to environmental conservation but also to create economic opportunities through agrotourism and community empowerment. The success of this program requires further coordination between local governments, academics, and communities to ensure the sustainable management of the Pesanggrahan River riparian zone.
RESPON BEBERAPA VARIETAS BATANG ATAS DAN WARNA SUNGKUP PADA SAMBUNG PUCUK TANAMAN JERUK Khansa Sulthanah Rumi; Fitri Yulianti; Muhammad Ridha Alfarabi Istiqlal; Paranita Asnur
AGRORADIX : Jurnal Ilmu Pertanian Vol 8 No 1 (2024): Desember 2024
Publisher : Agroteknologi Fakultas Pertanian Universitas Islam Darul 'Ulum (UNISDA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/agroteknologi.v8i1.7724

Abstract

Citrus plants are a horticultural that is in great demand in various countries and has potential in the future, but still experiences problems in seedling propagation. Efforts to overcome this problem are grafting propagation. This study aims to determine the response of grafting results to the treatment of differences in scion varieties and cover colors and to determine the best grafting results between treatment combinations. The study was conducted in April-May 2022 in the Agrotechnology open land, Campus F7 Gunadarma University. The study was conducted with a randomized complete group design (rcbd) (4x4) with 3 replications. The first factor is the difference in scion varieties (nipis, limo, pamelo, and sunkist), the second factor is the cover color (red, yellow, blue and transparent). The results showed that the success of grafting based on the highest scion variety was obtained in the limo and pamelo varieties of oranges, while for cover colors it was obtained in transparent and yellow colors, the treatment of scion varieties had a significant effect on the variables of scion height, scion diameter, number of shoots and number of leaves. Meanwhile, the color treatment of the cover had a significant effect on the variables of plant height and upper stem height.
INTUITIVE UI DESIGN FOR MANGROVE TREE DETECTION APP Asnur, Paranita; Agushinta R, Dewi; Fitrianingsih, Fitrianingsih; Ngakasah, Siti Aliyah
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 12 No. 1 (2025): Desember 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v12i1.4362

Abstract

Abstract: The rapid degradation of mangrove ecosystems threatens coastal biodiversity, shoreline stability, and carbon sequestration capacity, particularly in areas experiencing intense human activity. However, community-based participatory mangrove monitoring remains limited due to the lack of accessible and user-friendly digital tools. This study aims to design an intuitive mobile application for mangrove tree detection and participatory ecological monitoring using a User-Centered Design (UCD) approach. The research was conducted iteratively through user needs analysis, prototype development, and usability evaluation involving local governments, conservation practitioners, and non-expert users. The proposed application integrates machine learning for automated mangrove recognition with geospatial visualization and real-time feedback to support field-based monitoring. Usability evaluation using the System Usability Scale (SUS) yielded an overall score of 82.3, categorized as excellent usability, indicating high user satisfaction and intuitive interaction. The results demonstrate that integrating UCD and machine learning enhances usability, user engagement, and the accuracy of mangrove documentation under real field conditions. Overall, this study presents a field-ready, user-centered mobile solution that bridges usability engineering and participatory mangrove monitoring as a replicable model for inclusive ecological application development. Keywords: Carbon sequestration; mangrove monitoring; mobile application; user-centered design; usability evaluation Abstrak: Degradasi ekosistem mangrove yang semakin cepat mengancam keanekaragaman hayati pesisir, stabilitas garis pantai, dan kapasitas sekuestrasi karbon, terutama di wilayah dengan aktivitas manusia yang intens. Namun, pemantauan mangrove secara partisipatif berbasis komunitas masih terbatas akibat kurangnya perangkat digital yang mudah diakses dan ramah pengguna. Penelitian ini bertujuan merancang aplikasi mobile yang intuitif untuk deteksi pohon mangrove dan pemantauan ekologi partisipatif dengan menggunakan pendekatan User-Centered Design (UCD). Penelitian dilakukan secara iteratif melalui analisis kebutuhan pengguna, pengembangan prototipe, dan evaluasi kegunaan dengan melibatkan pemerintah daerah, praktisi konservasi, serta pengguna non-ahli. Aplikasi yang diusulkan mengintegrasikan pembelajaran mesin untuk pengenalan mangrove secara otomatis dengan visualisasi geospasial dan umpan balik waktu nyata guna mendukung pemantauan di lapangan. Evaluasi kegunaan menggunakan System Usability Scale (SUS) menghasilkan skor keseluruhan sebesar 82,3 yang termasuk dalam kategori kegunaan sangat baik, menunjukkan tingkat kepuasan pengguna yang tinggi dan interaksi yang intuitif. Hasil penelitian menunjukkan bahwa integrasi UCD dan pembelajaran mesin meningkatkan kegunaan, keterlibatan pengguna, serta akurasi dokumentasi mangrove dalam kondisi lapangan. Secara keseluruhan, penelitian ini menyajikan solusi mobile berbasis UCD yang siap digunakan di lapangan dan menjembatani rekayasa kegunaan dengan pemantauan mangrove partisipatif sebagai model replikatif bagi pengembangan aplikasi ekologi yang inklusif. Kata kunci: Carbon sequestration; mangrove monitoring; mobile application; user-centered design; usability evaluation
Effects of Biofertilizer Application and Organic Matter Incubation on Soil Chemical Properties Aisyah; Paranita Asnur; Fitrianingsih; Risnawati
Jurnal Penelitian Pendidikan IPA Vol 11 No 11 (2025): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i11.13342

Abstract

Soil organic matter is essential for maintaining soil fertility and supporting sustainable agricultural production. However, raw organic matter does not directly enhance soil chemical properties without a sufficient decomposition period. This study evaluated the effects of organic matter incubation and biofertilizer concentrations on soil chemical characteristics. The experiment was conducted from June to August 2024 in the Greenhouse Laboratory of Gunadarma Technopark University, Jamali Village, West Java, using a completely randomized factorial design. Treatments consisted of four biofertilizer concentrations (0, 10, 15, and 20 mL/L) and five incubation periods of cow manure (0, 1, 2, 3, and 4 weeks), each replicated four times, resulting in 80 experimental units. The results showed a significant interaction between incubation duration and biofertilizer concentration on soil pH, organic carbon, total nitrogen, C/N ratio, available phosphorus (P₂O₅), and available potassium (K₂O). The four-week incubation combined with 10–20 mL/L of biofertilizer produced the most notable improvements, increasing pH to neutral levels, raising organic carbon and nitrogen contents, achieving an optimal C/N ratio, and enhancing P availability, although K remained low. These findings indicate that combining biofertilizer application with an adequate incubation period effectively improves soil fertility and offers a viable strategy for long-term soil management and agricultural productivity.
PENDAMPINGAN PENGEMBANGAN SISTEM PERTANIAN ORGANIK BERKELANJUTAN DI THE LEARNING FARM Paranita Asnur; Aisyah Aisyah; Veronika Widi Prabawasari; Dimyati Dimyati; X Furuhito; Bima Haryadi; Azaz Pradana; Budi Santosa
Jurnal Bakti Masyarakat Indonesia Vol. 8 No. 3 (2025): Jurnal Bakti Masyarakat Indonesia
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jbmi.v8i3.35461

Abstract

The mentoring activity for developing a sustainable organic farming system at The Learning Farm (TLF) aims to document potential, identify constraints, and provide strategic recommendations to strengthen organic farming practices. The program was carried out through field surveys, direct observations, interviews, and questionnaires administered to partner farmers to gather information on cultivation practices, knowledge, and their needs. The collected data were analyzed qualitatively and descriptively as the basis for formulating mentoring strategies. Survey results show that each vegetable commodity produces an average of 10–15 kg per harvest, with some reaching up to 40 kg, harvested twice a week or approximately 97 times a year. TLF has implemented organic farming through crop rotation, multiple cropping, and intercropping with perennial plants such as robusta coffee. Fertilization is carried out using solid and liquid organic fertilizers produced independently, while irrigation utilizes river water filtered with water hyacinth. The main challenges include limited capital, nutrient-poor soil conditions, high rainfall, and high labor requirements. Nevertheless, the organic farming sector contributes more than 50% of TLF’s income, surpassing the agritourism sector. The implications of this activity emphasize that organic farming is not only environmentally friendly but also economically significant. Multidisciplinary mentoring is required to strengthen farmers’ capacity, optimize cultivation systems, and support TLF as a center for education and innovation in sustainable agriculture
Cloud Computing-Based U-Net Integration for Post-Landslide Satellite Image Segmentation Pratiwi , Swelandiah Endah; Asnur, Paranita; Fitrianingsih, Fitrianingsih; Senjaya, Remi; Nurdin, Muhammad Sahal
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5617

Abstract

Landslides are geological disasters that cause severe impacts on human life, infrastructure, and ecosystems, highlighting the need for post-disaster mapping methods that are fast, accurate, and scalable. This study aims to develop a post-landslide satellite image segmentation framework based on U-Net integrated with cloud computing to support large-scale and operational disaster mapping. While U-Net has been widely applied for landslide analysis, most existing studies focus on local-scale assessments or susceptibility mapping and lack integration with cloud-based pipelines and multi-source data for post-disaster operations. The novelty of this research lies not in modifying the U-Net architecture, but in integrating multi-source geospatial data, system workflow, and scalable cloud deployment. The proposed framework utilises a global multi-source dataset consisting of RGB imagery, Normalized Difference Vegetation Index (NDVI), slope, and elevation to enhance robustness and generalisation across diverse geomorphological conditions. Experimental results show stable model convergence with a final loss of 0.0357, an F1-score exceeding 0.75, and an AUC-PR of 0.8391. Evaluation on the testing dataset achieves a precision of 0.7692, recall of 0.7519, F1-score of 0.7604, and Intersection over Union of 0.6135. Qualitative analysis demonstrates strong spatial agreement between predicted segmentation and ground truth, with minor deviations mainly along complex slope boundaries. From an Informatics perspective, this study contributes by operationalizing deep learning through cloud computing to enable scalable computation, parallel processing, and system-level deployment, while providing object-level estimates of landslide events and affected areas to support disaster response and risk mitigation.
Co-Authors Aisyah Aisyah Aisyah Aisyah Aisyah Aisyah Aisyah Aisyah Alki Satrio Plapito Amelia Salsabila Andina Dwi Iryanti Angga Putri Ekanova Arti, Inti Mulyo Azaz Pradana Bima Haryadi Budi Santosa Budi Santosa Budi Santosa Cicilia Erly Istia Dewi Agushinta R. Dimyati Dimyati Dini Yartiwulandari Doddy Ari Suryanto Dody Pernadi Dody Pernadi Elbi Wiseno Erna Kustyarini Evan Purnma Ramdan Fitri Yulianti Fitri Yulianti Fitrianingsih Fitrianingsih Fitrianingsih Fitrianingsih Fitrianingsih Haryadi, Bima Hendi Hidayat Hertinsyana, Desy Inti Mulya Arti Inti Mulya Arti Irmawati Wijaya Isnainy, Dyon Rahman Izzani Ulfi Kanny, Putri Irene Khansa Sulthanah Rumi Kholish, Iqbal Nur Laraswati, Rini Manurung, Adinda Nurul Huda Maulana Syarif Hidayatullah Mufid Suryani Mufid Suryani Muhammad Ridha Alfarabi Istiqlal Muhammad Ridha Alfarabi Istiqlal Ngakasah, Siti Aliyah Nicky Handayani Nida Nusaibatul Adawiyah Nur Azifah Nurachmania, Meylida Nurdin, Muhammad Sahal Pratiwi , Swelandiah Endah Ramdan, Evan Purnama Ramdan, Ivan P. Ratih Kurniasih Rehulina Apriyanti Remi Senjaya Ridwan, Ridwan Risa Septiani Riskayanto Riskayanto Risnawati Siska Yuliani, Siska Siti Aisyah Siti Aisyah Stevani Adinda Nurul Huda Sutan Emir Hidayat Swelandiah Endah Pratiwi Thomas Yuni Gunarto Tia Chisca Anggraeni Ummu Kalsum Veronika Widi Prabawasari Veronika Widi Prabawasari Wahyu Prakosa Wahyu Prakosa X Furuhito