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All Journal Media Trend: Berkala Kajian Ekonomi dan Studi Pembangunan Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi)
Al Aziz, Moh. Sofwan Kastir
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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THE OPTIMIZATION STRATEGY OF FISHERY WASTE IN SUMENEP REGENCY AS A VALUE-ADDED PRODUCT BASED ON THE CIRCULAR ECONOMY Arifin, Alvin; Al Aziz, Moh. Sofwan Kastir; Liahmad, Liahmad; Wahyuningtias, Novi; Tsawaba, Naila
Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA) Vol 9 No 3 (2025): Edisi September - Desember 2025
Publisher : LPPM STIE Muhammadiah Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31955/mea.v9i3.6467

Abstract

The fisheries sector in Sumenep Regency plays a vital role in food security and the local economy, but generates substantial waste, including fish heads, bones, viscera, and skins. Most of these residues are discarded into the sea or landfills, creating environmental burdens and economic losses. This study aims to formulate a strategy for optimizing fishery waste based on circular economy principles using a sequential explanatory mixed-methods approach. The quantitative phase employed multiple linear regression to examine the effects of business duration, technology, and average catch on waste utilization. Results indicate that technology significantly influences utilization (p < 0.01), whereas business duration and catch volume are not significant. The qualitative phase, involving in-depth interviews and focus group discussions, reinforced these findings by revealing that limited access to simple processing technologies, weak market linkages, and inadequate regulations remain the main obstacles. Nevertheless, respondents recognized the potential of fish waste to be converted into organic fertilizer, animal feed, fish oil, and collagen. This study concludes that appropriate technology, market access, and regulatory as well as multi-stakeholder collaboration are crucial for implementing a circular economy model in Sumenep’s fisheries sector. The practical implication suggests strengthening community capacity and policy support to advance sustainable fishery waste valorization.
Poverty Analysis in Indonesia Based on AI (Artificial Intelligence) with ARIMA Method Al Aziz, Moh. Sofwan Kastir; Rahman, Hairul; Hidayat, Nurul; Arifin, Fauzi; Ainorrofiqie, Ainorrofiqie
MediaTrend Vol 20, No 2 (2025): OKTOBER
Publisher : Trunojoyo University of Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/mediatrend.v20i2.32521

Abstract

Poverty in Indonesia is a complex and multidimensional problem, because poverty levels can be an indicator of success for the country in terms of both its development and economy. This is an important point for the government to predict or predict poverty so that it can provide a more appropriate alternative. Based on this problem, a method is needed, namely using the forecasting method (Forcasting). In this study, researchers used a model from Box Jenkins, namely the Auto Regressive Moving Average (ARIMA) to predict the future level of poverty in Indonesia. AI (Artificial Intelligence) is not widely used in terms of economy, especially on poverty issues, but AI is one of the alternatives for countries to overcome poverty. Quantitative research in this study uses the ARIMA (Auto Regressive Moving Average) analysis. The poverty dataset used is sourced from the Central Bureau of Statistics (BPS) with test data from 2010 to 2023 to 2029. AI can provide alternative recommendations to deal with poverty in the future and in addition to looking at the forecast (Forcasitng) of poverty levels for the next 5 years. Conclusion: The government can make AI one of the tools to find solutions in the form of alternatives to solve poverty problems. Thus, through AI, it can be considered by the government in providing policies for poverty problems
Co-Authors Ainorrofiqie, Ainorrofiqie Alvin Arifin Fauzi Arifin Liahmad, Liahmad Nurul Hidayat Rahman, Hairul Tsawaba, Naila Wahyuningtias, Novi