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Journal of Innovation in Applied Natural Science CV Media Inti Teknologi Ruko B, RT 05 RW 01 Jalan Pinang Mas, Bentiring Permai, Muara Bangkahulu, Kota Bengkulu Indonesia. 38229
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Journal of Innovation in Applied Natural Science
Published by CV Media Inti Teknologi
ISSN : -     EISSN : 31104150     DOI : https://doi.org/10.58723/jinas.v2i1.153
Core Subject : Science, Education, Agriculture, Social, Engineering,
Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Energy Environmental Science Immunology & microbiology Materials Science & Nanotechnology Mathematics Physics
Journal of Integrated Natural Sciences (JINAS) is an academic peer-reviewed journal that publishes high-quality research in the field of natural sciences, encompassing both fundamental and applied scientific studies. The journal aims to provide a scholarly platform for researchers, academics, and practitioners to disseminate innovative findings, theoretical advancements, and practical applications that contribute to the development of scientific knowledge and technological progress. JINAS welcomes original research articles, review papers, and scientific reports that demonstrate methodological rigor and interdisciplinary relevance. The scope of JINAS covers a broad range of topics within the natural sciences, including Biological and Environmental Sciences, Chemical and Material Sciences, Physical Sciences, and Mathematical Sciences. Through these areas, the journal encourages studies that explore natural phenomena, develop scientific models and analytical approaches, and apply scientific principles to address real-world challenges. By promoting interdisciplinary collaboration and scientific exchange, JINAS seeks to support the advancement of natural science research and its contribution to sustainable development and innovation.
Arjuna Subject : Umum - Umum
Articles 10 Documents
 1 
Performance Analysis of Bio-batteries from Organic Waste for Alternative Electric Energy Nata Raharjo, M. Arya; Arifia, Amanda Fajar; Herlina, Kartini
Journal of Innovation in Applied Natural Science Vol. 1 No. 1 (2025): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v1i1.16

Abstract

Background of study: Biobatteries are an innovative form of renewable energy technology that utilize organic materials to produce electricity through electrochemical reactions. Organic waste such as banana and pineapple peels contains natural electrolytes, making them potential sustainable and eco-friendly energy sources.Aims and scope of paper: This study aims to evaluate the performance of simple biobatteries using banana and pineapple peels as electrolyte materials. The research focuses on measuring voltage and current generation over seven days and assessing the stability and durability of each type of organic waste.Methods: Biobatteries were assembled using zinc (Zn) electrodes as the anode and carbon rods as the cathode. The peels were ground into a paste and used as the electrolyte. Daily measurements of voltage and current were taken for seven consecutive days to analyze performance trends.Result: Test results showed that both types of biobatteries were capable of producing sufficient voltage and current to power simple electronic devices such as small LEDs, wall clocks, and basic household appliances. However, biobattery performance decreased over time due to water evaporation, degradation of active compounds, and environmental influences such as temperature and humidity. Overall, banana peels performed more consistently than pineapple peels.Conclusion: This research demonstrates that organic waste can serve as a viable material for renewable energy generation. Biobatteries made from fruit peels not only help reduce waste but also have potential for educational use and community energy initiatives.
Innovative Cultivation Strategies for Echinochloa Colona in Marginal Lands as a Sustainable Livestock Feed Resource Amalyadi, Rezki
Journal of Innovation in Applied Natural Science Vol. 1 No. 1 (2025): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v1i1.35

Abstract

Background of Study: The growing global demand for high-quality livestock forage is increasingly constrained by land scarcity and climate variability. Marginal lands such as saline soils, degraded peatlands, and arid regions remain underutilized, yet hold promise for sustainable forage production without competing with prime agricultural land.Aims and Scope of Paper: this review aims to evaluate the potential of Echinochloa colona, a fast-growing and stress-tolerant wild grass, as a sustainable forage crop for cultivation on marginal lands, focusing on its agronomic performance, nutritional value, and contributions to livestock feed system sustainability.Methods: a narrative literature review was conducted using Scopus and Google Scholar, focusing on peer-reviewed articles published between 2004 and 2025, with 59 articles selected through a systematic screening process.Results: the findings show that E. colona thrives under adverse conditions, produces high biomass, and offers notable protein content, dietary fiber, and essential micronutrients that support livestock productivity. Agronomic enhancements such as minimum tillage, drip irrigation, biofertilizer use, and polyculture with legumes significantly improve its yield and quality. However, issues such as herbicide resistance, inadequate seed systems, limited farmer awareness, and lack of policy and market support remain barriers to adoption.Conclusion: integrating E. colona into marginal land-based livestock systems presents an opportunity to enhance feed security, combat land degradation, and foster climate-resilient agriculture through adaptive management, technological innovation, and supportive institutional frameworks.
Comparison of Electrical Properties and Endurance of Papaya Peel and Cassava Peel-Based Bio-Batteries as Potential Alternative Energy Sources Heriansyah, Heriansyah; Rahmadani, Novia Gena; Rahman, Refpo; Ramandani, Adityas Agung
Journal of Innovation in Applied Natural Science Vol. 1 No. 1 (2025): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v1i1.48

Abstract

Background of study: Bio-batteries represent an attractive energy solution utilizing organic substances to generate electrical energy. Organic waste materials, such as fruit peels, contain electrolytic compounds harnessed for bioelectricity generation. Cassava and papaya peels, rich in natural acids and carbohydrates, offer potential as low-cost, eco-friendly materials for bio-battery development. Aims and scope of paper: This study investigates the electrical performance and endurance of biobatteries made from cassava peel and papaya peel subjected to varying fermentation durations (0, 2, and 4 days).Methods: The study employed an experimental comparative approach using 1.5 V battery casings filled with fermented cassava and papaya peel pastes. Electrical parameters (voltage, current, and power) were measured using a digital multimeter. Additionally, endurance was tested by using the biobatteries to power a 1.2 W LED until discharge.Result: Cassava peel-based biobatteries showed higher electrical output than those based on papaya peel, especially after 4 days of fermentation. The cassava battery reached a peak voltage of 1.6 V and power of 0.107 mW, while papaya reached 1.57 V and 0.105 mW. Cassava peel biobatteries also demonstrated longer endurance, operating up to 27 hours compared to 21 hours for papaya.Conclusion: Fermentation enhances the electrical properties of fruit peel biobatteries, with 4 days as the optimal duration. Cassava peel is more effective than papaya peel due to its higher content of fermentable substrates and organic acids. This study supports the feasibility of using fermented fruit waste as sustainable bio-battery material and suggests further optimization for practical applications.
Beyond the Canopy: Resolving Topographic and Acoustic Complexities with Machine Learning for Karst Avifauna Monitoring Fitryan, Anggyta; Abdurrahman, Ahmad Faruq; Nuryani; Prihanto, Surya; Al Fath, Yusril; Aprilia, Ayu; Junaidi; Surtono, Arif
Journal of Innovation in Applied Natural Science Vol. 1 No. 1 (2025): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v1i1.52

Abstract

Background of study: Tropical karst landscapes harbor exceptional avian biodiversity but pose unique monitoring challenges due to complex topography, cave reverberation, and humidity-driven sound distortion. Conventional ecoacoustic methods fail in these environments, with indices showing weak correlations (r=0.20-0.43) for avian diversity due to insect masking and abiotic interference. Over 83% of karst-endemic birds lack standardized monitoring protocols despite escalating extinction risks.Aims and scope of paper: This review aims to: (1) quantify limitations of current ecoacoustic methods in karst ecosystems, (2) develop a machine learning-enhanced framework addressing topographic and reverberation effects, and (3) establish conservation-ready protocols for endangered karst avifauna. The study synthesizes evidence from 29 studies across hardware innovation, signal processing, and policy applications.Methods: We systematically analyzed 29 studies on acoustic monitoring in karst ecosystems, focusing on machine learning innovations, topographic adaptations, and conservation applications.Result: Topography drives 47% of soundscape variation, surpassing vegetation effects. Machine learning (CNNs/MFCCs) boosts detection accuracy by 22-80% in reverberant caves. Hybrid protocols enable 25-m resolution habitat mapping and precise disturbance monitoring, overcoming tropical "latitude paradox" limitations.Conclusion: This review establishes the first karst-adapted ecoacoustic framework, integrating machine learning with topographic variables to transform monitoring from biodiversity proxy to precision tool. Critical next steps include developing species-specific call libraries, wind-reverberation filters, and policy integration of acoustic baselines for IUCN assessments. The proposed protocols address urgent conservation needs for Earth's most threatened avian sanctuaries.
Replacing Fat with Soy Milk and Lecithin: Impact on the Quality of Steamed Sponge Cake Putri, Larasita Aulia; Hidayat, Lukman; Anis, Ulfah; Islam, Md Zahidul; Rezvani, Mohammad Qais; Emumejaye, Kugbere
Journal of Innovation in Applied Natural Science Vol. 1 No. 1 (2025): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v1i1.55

Abstract

Background of study: Steamed sponge cake is a type of cake that uses eggs as the primary raw material for foam formation, emulsification, and coagulation. Soybean flour, a plant-based protein source, has the potential to replace the functional roles of eggs in steamed sponge preparation. The addition of an emulsifier is also required to maintain the final product quality.Aims and scope of paper: This study aimed to analyze the effects of soy milk substitution, lecithin addition, and their interaction on the physical, chemical, and organoleptic characteristics of steamed sponge cake.Methods: The experiment was conducted using a factorial Completely Randomized Design with two factors: the egg-to-soy milk ratio (100:0, 75:25, and 50:50) and the level of soy lecithin addition (2% and 4%). Data were analyzed using two-way ANOVA at a 5% significance level, followed by Duncan’s Multiple Range Test (DMRT) to determine significant differences among treatments.Result: Soy milk significantly affected moisture content, volume, hardness, cohesiveness, springiness, chewiness, gumminess, resilience, protein content, and fat content. Lecithin addition significantly affected moisture content, volume, specific volume, hardness, springiness, chewiness, gumminess, resilience, and protein content. The interaction between soy milk substitution and lecithin addition significantly influenced specific volume, hardness, springiness, gumminess, and resilience.Conclusion: Soy milk substitution and lecithin addition, individually and in combination, significantly influenced multiple physical and chemical properties of steamed sponge cake. These findings demonstrate the potential for partial replacement of eggs with soy milk, combined with soy lecithin, to produce high-quality steamed sponge cake with possible cost benefits.
Physicochemical Quality of Coffee Soap Based on Variations in Soap Manufacturing Methods and Roasting Type Wulandari, Sri; Yuwita, Fitri; Anis, Ulfa
Journal of Innovation in Applied Natural Science Vol. 2 No. 1 (2026): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v2i1.143

Abstract

Background: The demand for natural, environmentally friendly, and sustainable cosmetic products continues to increase along with growing consumer awareness of the negative impacts of synthetic chemicals. Coffee is one of the natural ingredients with potential application in soap formulation, as it contains bioactive compounds beneficial for skin health. Aims: This study aimed to analyze and compare the physicochemical quality of coffee soap based on variations in manufacturing methods (cold process and hot process) and type of coffee roasting (light, medium, and dark). Methods: The research was conducted at the Laboratory of Mathematics and Natural Sciences, University of Bengkulu, and the Laboratory of the Faculty of Agricultural Technology, Gadjah Mada University, using a two-factor Completely Randomized Design (CRD). The quality parameters observed were moisture content, pH, free fatty acids, free alkali and caffeine. Data were analyzed using Two-Way ANOVA. Result: soap making method and the type of coffee roasting had a significant effect on the quality of water content, pH, free fatty acids, and caffeine with a significance value (p<0.05), but had no significant effect on the quality of free alkali (p>0.05) that is 0.136. Conclusion: The combination of the cold process and medium roasting level is recommended as it provides the best balance between the physical and chemical quality of coffee soap. This study contributes to the development of coffee soap as a high-quality and competitive natural cosmetic product
Physicochemical Characteristics of Nata De Banana Produced From Ambon Banana Peels (Musa paradisiaca L.) Cultivated in The Highlands and Lowlands of Bengkulu Province, Indonesia Jumiarni, Dewi; Hulandari, Getteri; Ansori, Irwandi
Journal of Innovation in Applied Natural Science Vol. 2 No. 1 (2026): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v2i1.144

Abstract

Background: Banana peel waste from Ambon bananas contains essential nutrients that support the growth of Acetobacter xylinum in nata production. Differences in cultivation environments, such as highland and lowland areas, may influence the composition of banana peels and subsequently affect the characteristics of nata de banana produced. Aims: This study aimed to analyze the differences in characteristics of nata de banana produced from Ambon banana peels cultivated in highland and lowland areas, focusing on physical properties and sensory acceptance. Methods: An experimental design was used with banana peels from highland and lowland areas as the differentiating variables. Data on nata characteristics were analyzed statistically using an independent sample t-test with SPSS version 23. Result: The results showed significant differences in thickness and weight of nata de banana between the two sources. Nata produced from highland banana peel extract had greater thickness and weight. Organoleptic tests also indicated that nata from highland peels was more preferred in terms of color, texture, taste, and aroma. Conclusion: Ambon banana peels from highland areas demonstrate higher potential as raw material for nata production, offering an effective approach to utilizing local natural resources and improving the management of banana peel waste.
Renewable Energy Systems of Smart Grids and DL scheme Sathio, Anwar Ali; Hingora, Tehreem; Raja Vavekanand; Ali, Sameer
Journal of Innovation in Applied Natural Science Vol. 2 No. 1 (2026): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v2i1.153

Abstract

Background: Solar energy systems are expanding rapidly, which increases the need for efficient power extraction and accurate power forecasting. Conventional maximum power point tracking methods show reduced performance under varying meteorological conditions, which leads to power losses. Machine learning offers data driven models that adapt to changing environmental patterns and improve system performance. Aim and Scope: The study aims to enhance solar power harvesting and forecasting through machine learning techniques. Multiple predictive models are evaluated to identify reliable approaches for photovoltaic system applications. Methodology: Solar and meteorological datasets were preprocessed through data cleaning, removal of missing values, and extraction of time based features to support time series modeling. Linear regression, random forest, and artificial neural network models were trained and evaluated through mean absolute error, root mean square error, coefficient of determination, and graphical performance analysis to achieve accurate solar power prediction and effective maximum power point tracking. Results: The proposed framework improves solar power collection and contributes to grid stability. Machine learning based models demonstrate fast and accurate maximum power point tracking with consistent power output and improved efficiency. Conclusion: The integration of intelligent control and machine learning techniques enhances the efficiency and reliability of solar energy systems. The proposed approach supports increased power generation, improved grid stability, and stronger sustainability of renewable energy utilization
Application of the Semi-Batch Method in Biodiesel Processing Using Refined Bleached Deodorized Palm Oil (RBDPO) with Variations in Feed Addition and Temperature Faizin, Indra Muhammad; Bimantio, Mohammad Prasanto; Widyowanti, Reni Astuti
Journal of Innovation in Applied Natural Science Vol. 2 No. 1 (2026): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v2i1.154

Abstract

Background: Biodiesel production efficiency is strongly influenced by reaction method, temperature, and reactant feeding strategy. Semi-batch transesterification offers better molar ratio control and reduced methanol waste compared to conventional batch systems. Aims: This study analyzes the effect of feed addition frequency and reaction temperature on biodiesel efficiency and characteristics using Refined Bleached Deodorized Palm Oil (RBDPO) as raw material. Methods: A Complete Block Design with two factors was applied: feed addition frequency (4×, 5×, 6× per period) and reaction temperature (40°C, 50°C, 60°C) with two replications. Biodiesel was produced using semi-batch transesterification with sodium methylate catalyst. Parameters measured included yield, density, pH, water content, glyceride profile, and methyl ester content. Data were analyzed using Duncan’s Multiple Range Test (5%). Result: The best treatment was 5× feed addition, 50°C, producing the highest methyl ester content (67.18%), yield (92.98%), density (877 kg/m³), pH 6.78, and low water content (1,401 ppm). Most quality parameters approached SNI 7182:2015 biodiesel standards. Conclusion: Semi-batch operation improves conversion control but is not yet fully optimal due to reverse reactions. Further optimization of methanol ratio and reaction time is required to suppress monoglyceride and diglyceride reformation.
A Tetrahedral Sensor Array Prototype for Avian Sound Source Localization in Bioacoustics Conservation Fitryan, Anggyta; Wulandari, Mei; Nuryani; Faruq, Ahmad Abdurrahman; Junaidi; Aprilia, Ayu; Prihanto, Surya; Al Fath, Yusril
Journal of Innovation in Applied Natural Science Vol. 2 No. 1 (2026): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v2i1.157

Abstract

Background: Effective wildlife monitoring is crucial for conservation, but traditional methods are often invasive or lack spatial precision. Passive acoustic monitoring offers a non-invasive alternative, yet deriving meaningful spatial data from sound recordings remains a technical challenge, limiting its utility for detailed ecological analysis. Aims: This study aims to design and simulate a proof-of-concept, low-cost acoustic localization system. The goal is to translate Time Difference of Arrival (TDOA) data from a simple tetrahedral microphone array into two-dimensional spatial heatmaps, providing a visual and quantitative tool to map animal vocal activity for enhanced biodiversity assessment. Methods: A cross-shaped, four-sensor array was modeled. A custom MATLAB GUI was developed to simulate TDOA data from multiple sound sources at varied positions. The system processed this data to generate and compare four distinct types of spatial heatmaps: Gaussian Smoothing, Kernel Density Estimation, Grid Counting, and Inverse Distance Weighting Result: The simulation successfully generated all four heatmap types, validating the core data processing pipeline. The system provided estimated source coordinates with a root mean square error (RMSE) of 0.15-0.25 meters in a controlled 6x6m area and output key statistical metrics like cluster density and distribution. Conclusion: The prototype establishes a feasible framework for transforming raw acoustic signals into actionable spatial intelligence. This work provides a foundational step towards developing affordable, automated systems for long-term ecological monitoring, with future integration of machine learning promising direct species identification and behavioral insight.

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