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Journal of Smart Agriculture and Environmental Technology
Published by Indonesian Soil Science Society of South Sumatra
ISSN : -     EISSN : 30218802     DOI : https://doi.org/10.60105/josaet
Core Subject : Health, Science, Agriculture, Social,
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Earth & Planetary Sciences Environmental Science Veterinary
The Journal of Smart Agriculture and Environmental Technology (JOSAET) is an international, interdisciplinary publication committed to addressing current issues in agriculture and environmental sciences. Our mission is to promote sustainable and safe food production practices for the future without causing environmental harm. JOSAET covers a broad range of topics, including soil, water, and plant management, pest control, and plant cultivation. We aim to anticipate environmental changes and contribute to the development of resilient agricultural practices. Published three times a year, in April, August, and December, JOSAET maintains rigorous standards through a high-quality peer-review process. We welcome manuscripts showcasing interdisciplinary expertise in areas such as: Enhancing crop production efficiency with new technologies to support agricultural sustainability, covering topics like crop management, pest control, environmental impact, input efficiency, new variety development, and socio-economic assessment. Fostering soil and water management strategies, such as the use of organic inputs, anticipation of soil pollution, soil health, and soil fertility inputs for sustainability. Exploring technology applications in various fields including soil science, agronomy, horticulture, plantation, forestry, aquaculture, husbandry farming, bioremediation, and application of machine learning and artificial intelligence in soil science, agriculture, and environment. We also welcome contributions discussing other environmental technologies aimed at improving our environment. JOSAET publishes original papers, short communications, and reviews concerning smart agriculture and environmental technology. We are particularly interested in research that promotes agricultural practices preserving the environment, enhancing crop production and income, mitigating global warming effects, and building food security in the face of climate change. Our vision is to be a leading voice in the discourse on sustainable agriculture and environmental management, facilitating innovation and knowledge exchange for a sustainable and resilient future.
Arjuna Subject : Ilmu Pertanian dan Biologi (Semua) - Agronomi dan Ilmu Tanaman
Articles 7 Documents
 1 
Search results for , issue "Vol. 4 No. 1 (2026): April 2026" : 7 Documents clear
Analysis of Tea Plant (Camellia Sinensis) Farming in the PTPN 7 Regional 1 Gunung Dempo Pagar Alam, South Sumatra, Indonesia supli rahim
Journal of Smart Agriculture and Environmental Technology Vol. 4 No. 1 (2026): April 2026
Publisher : Indonesian Soil Science Society of South Sumatra in Collaboration With Soil Science Department, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60105/josaet.2026.4.1.41-45

Abstract

The low selling price of tea in the country by PTPN 7 Regional 1 Gunung Dempo Pagar Alam is currently causing the selling price of tea plant shoots to be increasingly cheaper as indicated by the decreasing number of farming revenues and the low farming income received by the state-owned company. The aim of this research is to describe the farming performance carried out by PTPN 7. Apart from that, the main aim of this research is to analyze the value of tea farming starting from the value of farming revenues, farming costs and farming income. The research results show that that tea farming is still feasible and profitable to continue to be developed. This is evidenced by the B/C ratio value which exceeds 1, which indicates that each unit cost incurred still generates profit. In addition, the R/C ratio value in all PTPN 7 plantation divisions ranges from, which means that for every IDR 1 of total farming costs incurred, the company earns revenue of Rp 1,24. Thus, tea farming at the research location still makes a positive contribution to the company’s income and has good sustainability prospects.
Effect of Potassium Sulfate (K2SO4) and Chicken Manure Application on Productivity, Morphology, Physiology, and Antioxidant Activity of Shallots in Floating Cultivation chindy charin marlisa; Susilawati Susilawati; Irmawati Irmawati
Journal of Smart Agriculture and Environmental Technology Vol. 4 No. 1 (2026): April 2026
Publisher : Indonesian Soil Science Society of South Sumatra in Collaboration With Soil Science Department, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60105/josaet.2026.4.1.19-27

Abstract

Shallot is one of the vegetable commodities that has long been intensively cultivated by farmers. In addition, shallots are also a short-lived and commercial vegetable commodity. This study aims to evaluate the application of chicken manure and potassium sulfate (K2SO4) fertilizer on the growth and yield of shallot plants (Allium ascalonicum L.) cultivated in a floating manner. This research was conducted in Terawas Village, STL ULU Terawas District, South Sumatra. From May to July 2024. This research method Factorial Randomize Block Design (RAKF), consisting of 2 factors, namely the first factor of chicken manure consisting of 4 levels, and the second factor is sulfur fertilizer from K2SO4 consisting of 4 levels. With 3 block, in each block it was 3 planted plants. 3 treatment groups and 3 replications each replication consists of 16 plant units, resulting in a total of 144 plants used in this study. This treatment is the first factor: P0 = control (without chicken manure), P1 = 1 kg/polybag chicken manure, P2 = 2 kg/polybag chicken manure, P3 = 3 kg/polybag chicken manure. Second factor: S0 = control (without potassium sulfate fertilizer (K2SO4), S1 = potassium sulfate fertilizer (K2SO4) 100 kg/ha, S2 = potassium sulfate fertilizer (K2SO4) 200 kg/ha, S3 = potassium sulfate fertilizer (K2SO4) 300 kg/ha. Parameters observed included plant height, number of leaves, number of tillers, wet stover weight, tuber diameter, fresh tuber weight, wind-dried tuber weight, root length, tuber length, tuber number, tuber volume, hectare-1 production, chlorophyll analysis and flavonoid content. Dosing potassium sulfate fertilizer (K2SO4) with an optimal dose of 142.5 kg/ha on the variable of estimated production per/ha, 174 kg/ha on the variable of tuber weight, 210 kg/ha on the variable of tuber volume, 154 kg/ha on the variable of wind dry weight, 214.45 kg/ha on the variable of antioxidant activity (flavonoids).
Optimization of Compost Mixing Efficiency and Airflow Through Innovative Gate Design in a Dual-Chamber Brick Tank System Ari Saputra; Supli Effendi Rahim; Gusmiatun
Journal of Smart Agriculture and Environmental Technology Vol. 4 No. 1 (2026): April 2026
Publisher : Indonesian Soil Science Society of South Sumatra in Collaboration With Soil Science Department, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60105/josaet.2026.4.1.28-36

Abstract

The development of innovative composting systems based on appropriate technology is crucial in addressing the pressing environmental issue of organic waste management in Indonesia. This study aims to develop and test a two chamber composting system with innovative airflow gates to enhance the efficiency of organic waste processing. The system was tested using a completely randomized design with four different treatments: innovative system, standard machine, manual method, and natural method, each with three replications. The results showed that the innovative system with airflow gates achieved the fastest composting time of 20 days, with a stable pH range of 6.9-7 and optimal moisture content of 34-36%. The system also produced compost with high nutrient content, including organic carbon, phosphorus, and potassium. Additionally, the system reduced labor requirements by 93% compared to conventional methods. Soil analysis revealed that the use of compost from the innovative system significantly improved soil quality and reduced chemical fertilizer requirements by 25-50%. These findings demonstrate that the composting system with airflow gates is superior in producing high-quality compost consistently. This system also offers a sustainable solution for organic waste management in Indonesia. This innovation has great potential for widespread adoption as an effective and efficient solution for organic waste management. Further development of this system can make a significant contribution to environmental conservation efforts and agricultural productivity enhancement in Indonesia.
Characterization Of Plant Growth Promoting Rhizobacteria (PGPR) From Bamboo A Napoleon; Agus Hermawan; Muh Bambang Prayitno
Journal of Smart Agriculture and Environmental Technology Vol. 4 No. 1 (2026): April 2026
Publisher : Indonesian Soil Science Society of South Sumatra in Collaboration With Soil Science Department, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60105/josaet.2026.4.1.46-51

Abstract

PGPR (Plant Growth Promoting Rhizobacteria) are root bacteria that trigger plant growth by colonizing a thin soil layer of about 1 mm-2 mm. PGPR can be derived from golden bamboo (Bambusa vulgaris) roots, bamboo roots contain hormones such as auxin, cytokinin and gibberillin which can stimulate root growth and plant development. This study aims to identify the morphological characteristics of PGPR bacteria from bamboo rhizosphere. This research was conducted in June-July 2023 in the experimental garden of ATC (Agrotech Training Center) owned by the Faculty of Agriculture, Sriwijaya University. This study used a simple experimental method to identify the morphological characteristics of bacteria in general. This method is carried out by conducting experiments, namely taking bamboo rhizosphere material and identifying the isolates obtained and then concluding from the experiments that have been carried out by proving the results obtained in accordance with existing research. In this study, there were 5 bacterial isolates successfully grown on Nutrient Agar (NA) media with different colony morphologies. Bacterial morphology found in giant colony isolates of PGPR solution from bamboo rhizosphere has a shape (Irregular and Circular); elevation (flat); edge (Lobate and Undulate); Color (Transparent, Milk White to Yellowish; and cell shape (Streptococcus and Palisade). The results of the identification of bacterial species indicated that the PGPR solution from the bamboo rhizosphere belonged to the Pseudomonas fluorescens and Bacillus polymixa species.
The Effect of Applying Bilimbi Juice (Averrhoa Bilimbi L.) as an Acidifier in Drinking Water on the Quality of Native Chicken Meat Meisji Liana Sari; Sofia Sandi; Eli Sahara; Arfan Abrar
Journal of Smart Agriculture and Environmental Technology Vol. 4 No. 1 (2026): April 2026
Publisher : Indonesian Soil Science Society of South Sumatra in Collaboration With Soil Science Department, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60105/josaet.2026.4.1.37-40

Abstract

Maintaining animal gut health by applying an acidifier directly impacts the performance of poultry production. This study aimed to determine the effect of adding Bilimbi (Averrhoa bilimbi L.) juice as acidifier to the drinking water of native chickens on meat quality. One hundred one-day old chickens were divided into a completely randomized design (CRD) with 5 treatments and 4 replications. The treatments were a mixture of drinking water and Bilimbi juice (v/v) as follows; P0 (control), P1 (drinking water + 4% Bilimbi juice), P2 (drinking water + 6% Bilimbi juice), P3 (drinking water + 8% Bilimbi juice), and P4 (drinking water + 10% Bilimbi juice) and applied for 60 days. The observed variables were pH, water-holding capacity, cooking-loss water, tenderness, meat fat and cholesterol. The results showed that applying Bilimbi juice up to 10% had no significant effect (P>0.5) on the pH, water holding capacity, cooking loss water, tenderness, fat and cholesterol of native chicken meat.
An Integrated Platform Innovation in the Sustainable Agribusiness Ecosystem (Case Study: Tani Link as a Knowledge-Based Communication Media) Maura Crescentiana Ninik Sri Rejeki; Adrianus Yoga Pranata; Alexander Beny Pramudyanto
Journal of Smart Agriculture and Environmental Technology Vol. 4 No. 1 (2026): April 2026
Publisher : Indonesian Soil Science Society of South Sumatra in Collaboration With Soil Science Department, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60105/josaet.2026.4.1.7-18

Abstract

The research aims to analyze the Tani Link platform as a communication media innovation that contributes to a sustainable agribusiness ecosystem. Additionally, it explores how science communication, such as communication media innovation, can strengthen sustainable agribusiness practices. The approach employed in this study was a case study by analyzing the concept and implementation of the Tani Link platform of the digital ecosystem in sustainable agribusiness. Primary data collection was conducted through interviews with three informants, such as the Director of Tani Link, the Tani Link Information Technology Manager, and the beneficiaries of the Tanilink TV broadcast. In addition, the collection of secondary data was performed through document studies on the Tani Link integrated platform (application, website, and YouTube channel @TanilinkTV). The results of the study indicate that Tani Link was an integrated and knowledge-based platform for building a sustainable agribusiness ecosystem  transparently, comprehensively, and democratically. Additionally, the research provided empirical insights into the integration of communication media, technology, and  information systems to support sustainable agribusiness, economically, socially, and environmentally.
Machine Learning-Driven Smart Aquaculture Technology for Climate-Resilient Water Quality Monitoring Moses Abiodun; Babatunde Adesina; S. Adebukola Onashoga; Kehinde Eniola; Kehinde Adeniyi; Babatomiwa Idris Rasheed
Journal of Smart Agriculture and Environmental Technology Vol. 4 No. 1 (2026): April 2026
Publisher : Indonesian Soil Science Society of South Sumatra in Collaboration With Soil Science Department, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60105/josaet.2026.4.1.1-6

Abstract

The aquaculture sector is among the fastest-growing food production industries, playing a critical role in global food security by supplying high-quality protein to millions.  However, climate change has introduced severe challenges, disrupting production through altered temperature regimes, unpredictable rainfall, and deteriorating water quality. Key parameters such as pH, dissolved oxygen (DO), and salinity have shown significant fluctuations, which are directly affecting fish health, growth rates, reproduction, and overall pond productivity. To address these challenges, this study  proposes an integrated IoT and machine learning (ML) framework designed for real-time water quality monitoring and adaptive management in aquaculture systems. The primary objective is to enhance climate resilience by enabling data-driven decision-making for optimal fish health and production efficiency. A comprehensive dataset was sourced from reputable offline and online repositories, and then partitioned into training (90%) and testing (10%) subsets. Water quality was classified into two categories: “good” and “bad” based on critical thresholds for aquaculture sustainability. Four supervised machine learning algorithms were evaluated for classification performance, including Random Forest (RF) with an accuracy of 100%, demonstrating superior predictive capability, and Logistic Regression (LR) with an accuracy of 57%, indicating moderate performance, Support Vector Machine (SVM) yielded an accuracy of 62%, suitable for certain nonlinear patterns, and Naive Bayes (NB) attained 89% accuracy, offering a balance between speed and reliability. This research paves the way for next-generation smart aquaculture systems, bridging the gap between environmental monitoring and AI-based decision support.

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