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Journal of Multidisciplinary Sustainability Asean
Published by Yayasan Adra Karima Hubbi
ISSN : 30482461     EISSN : 30481708     DOI : 10.70177/multidisciplinary
Core Subject : Science, Education,
Computer Science & IT Education Languange, Linguistic, Communication & Media Library & Information Science Other
Journal of Multidisciplinary Sustainability Asean is an international peer-reviewed journal dedicated to facilitating the exchange of results of high-quality research in all aspects of all areas of knowledge. The scope of the Journal of Multidisciplinary Sustainability Asean is not only in the form of study, research, or development but also book review. This journal publishes articles from all areas, including agricultural sciences, health sciences, biological sciences, engineering, and other exact sciences, as well as social and human sciences, which should contribute to scientific knowledge. Types of papers accepted: Review Articles, Mini-Reviews, and Research Articles with Questionnaires Application. As our commitment to advancing science and technology, the Journal of Multidisciplinary Sustainability Asean follows an open-access policy that allows published articles to be freely available online without any subscription. Submitted papers must be written in English for the initial review stage by editors and further review by at least two international reviewers.
Arjuna Subject : Umum - Umum
Articles 5 Documents
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Search results for , issue "Vol. 2 No. 3 (2025)" : 5 Documents clear
Design of Shrimp Skin-Based Nano-Biodegradable Material for Eco-Friendly Food Packaging Juwairiah, Juwairiah; Pong, Ming
Journal of Multidisciplinary Sustainability Asean Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v2i3.2250

Abstract

Background. The problem of plastic waste from food packaging continues to increase and poses a serious threat to the environment. The development of biodegradable-based eco-friendly packaging materials is one of the solutions that is getting more and more attention, especially those that come from organic waste such as shrimp skins that are rich in chitin. Purpose. This research aims to design a nano-biodegradable material based on shrimp skin that can be used as environmentally friendly food packaging, by evaluating its mechanical strength, water resistance, biodegradability ability, and application effectiveness in real conditions. Method. The research uses laboratory experiment methods with a quantitative approach. The shrimp skin is extracted into chitosan, then modified into a nanoform using the ionic gelation technique. Performance tests include tensile strength analysis, water contact tests, biodegradation tests, as well as application case studies on fresh fruit packaging. Results. The developed material shows high mechanical strength, good water resistance, and decomposes perfectly in a humid soil environment in less than 30 days. Direct application to the fruit shows effectiveness in maintaining freshness and preventing microbial contamination. Conclusion. The design of nano-biodegradable material from shrimp skin has the potential to be an alternative solution to plastic in food packaging, with ecological benefits and added value from the use of marine organic waste.
AI-Assisted Early Detection of Crop Disease Using Hyperspectral Imaging and Deep Learning in Smallholder Farms Azhar Nampira, Ardi; Mariam, Siti
Journal of Multidisciplinary Sustainability Asean Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v2i3.2305

Abstract

Background. Crop disease is a major threat to smallholder farmers who lack access to timely diagnostic tools. Traditional detection methods rely on visual inspection and often occur too late to prevent significant yield losses. Early detection using hyperspectral imaging and artificial intelligence presents a transformative solution for precision agriculture in resource-limited settings. Purpose. This study aims to develop and evaluate an AI-assisted early detection system for crop diseases using hyperspectral imaging and deep learning, tailored for application in smallholder farms. Method. A convolutional neural network (CNN) model was trained on hyperspectral data collected from five farm sites, with ground-truth annotations by agricultural experts. The model’s performance was evaluated using standard classification metrics, including accuracy, precision, recall, and F1-score. A case study was also conducted to assess real-world applicability. Results. The model achieved an average detection accuracy of 94.2% across all locations, with F1-score reaching 0.92 when using hyperspectral features. Confusion matrix analysis indicated high true positive and true negative rates, confirming reliability. In a field case, early diagnosis enabled targeted intervention and improved yield by 22% compared to prior seasons. Conclusion. The integration of hyperspectral imaging and deep learning offers a practical and scalable solution for early disease detection in smallholder farms. The system demonstrates high accuracy, adaptability, and operational feasibility in real-world conditions. Future work should focus on expanding crop and disease types, user interface development, and integration with mobile and IoT-based platforms.
Community-Based Coral Reef Conservation In The Kepulauan Seribu Prihadi, Donny Juliandri; Gupta, Meera; Patel, Priya
Journal of Multidisciplinary Sustainability Asean Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v2i3.2593

Abstract

Background. The coral reef ecosystems of Kepulauan Seribu National Park, crucial for marine biodiversity and local livelihoods, face severe anthropogenic pressures from coastal development and tourism. Community-Based Conservation (CBC) has emerged as a vital strategy to counteract this degradation, yet its specific impacts in this high-pressure marine area require rigorous evaluation. Purpose. This research evaluates the ecological efficacy and socioeconomic contributions of established CBC programs in Kepulauan Seribu. The study investigates the key factors influencing successful community participation and the resulting impacts on coral reef health. Methods. A mixed-methods approach was employed, integrating quantitative ecological surveys with qualitative socioeconomic analysis. Ecological data were collected via Line Intercept Transects (LIT) at multiple CBC-managed sites and non-CBC (control) sites. Socioeconomic data were gathered through semi-structured interviews (n=120) with community members, program managers, and local stakeholders. Results. The findings indicate that CBC-managed reefs exhibited significantly higher live coral cover and greater reef fish biomass compared to control sites. Socioeconomic analysis revealed enhanced community stewardship, supplementary income streams, and increased environmental awareness. However, institutional challenges, particularly funding instability and policy conflicts with tourism development, were identified as persistent obstacles. Conclusion. Community-based conservation demonstrates tangible success in mitigating reef degradation in Kepulauan Seribu. This study concludes that while CBC is effective, its long-term sustainability hinges on strengthening institutional support, resolving resource-use conflicts, and ensuring equitable benefit sharing for participating communities.
Local Literature’s Role In Raising Environmental Awareness: An Ecocritical Study Of Indonesian Texts Abdurahman, Abdurahman; Saputra, Dedi Gunawan; Fitri, Silva
Journal of Multidisciplinary Sustainability Asean Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v2i3.2604

Abstract

Background: Indonesia faces acute environmental crises, including deforestation and marine pollution, which are often disconnected from public discourse. While policy-based solutions are widely discussed, the potential of local literature as a vehicle for shaping ecological consciousness and fostering environmental ethics remains significantly underexplored in academic research. Purpose: This research aims to analyze the specific ecocritical strategies employed in contemporary Indonesian literary texts and to evaluate their effectiveness in raising environmental awareness and critiquing anthropocentric paradigms. Methods: An ecocritical textual analysis was employed as the primary research method. The study analyzed a purposive selection of prominent Indonesian novels and short stories published post-2000 that explicitly engage with themes of ecological degradation, local wisdom (kearifan lokal), and human-nature relationships. Results: The analysis reveals that these texts utilize distinct narrative techniques such as adopting non-human perspectives, invoking indigenous ecological knowledge, and portraying visceral environmental disasters to cultivate empathy. These strategies effectively translate complex ecological data into relatable affective experiences, challenging developmentalist narratives. Conclusion: Contemporary Indonesian literature functions as a vital and potent medium for environmental advocacy. By grounding ecological crises in local cultural contexts, these texts bypass defensive skepticism and successfully foster a critical environmental awareness that policy-making and scientific data alone often fail to achieve.
A Bioinformatics Analysis Of Circulating Microrna Signatures As Novel Biomarkers For Predicting Chemotherapy Response Muttaqin, T. Amirul; Allen, Esther; Salazar, Beatriz
Journal of Multidisciplinary Sustainability Asean Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v2i3.2663

Abstract

Background. Chemotherapy response is highly variable, leading to ineffective treatment and toxicity. Reliable, non-invasive biomarkers to predict response a priori are urgently needed. Circulating microRNAs (miRNAs) are stable liquid biopsy candidates, but previous studies often lack robust validation. Purpose. This study aimed to identify and validate a novel, non-invasive circulating miRNA signature to accurately predict chemotherapy response using a large-scale bioinformatic approach. Method. A comprehensive in silico study was conducted. We aggregated and harmonized 948 patient samples from five public datasets (GEO, TCGA). A machine learning pipeline (LASSO + Random Forest) was applied to a Training Set (n=664) to discover a predictive signature. The signature was then validated in an Internal Testing Set (n=284) and a separate External Validation Cohort (n=120). Results. We aggregated and harmonized 948 patient samples from five public datasets (GEO, TCGA). A machine learning pipeline (LASSO + Random Forest) was applied to a Training Set (n=664) to discover a predictive signature. The signature was then validated in an Internal Testing Set (n=284) and a separate External Validation Cohort (n=120). We identified and validated a 7-miRNA circulating signature (c-miRSig). The model demonstrated high accuracy in both the internal (AUC 0.89) and external (AUC 0.86) validation sets. Conclusion. The signature was also a powerful prognostic tool, significantly stratifying patients for progression-free survival (p < 0.001). Functional analysis linked the signature to key chemoresistance pathways (PI3K-Akt, ABC transporters). The c-miRSig is a robust, non-invasive biomarker with dual predictive and prognostic power. This computationally validated signature provides a strong foundation for a clinically viable test to personalize chemotherapy, sparing non-responders from toxic, ineffective treatment.

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