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All Journal CEMARA Forum Agribisnis Agro Ekonomi Aceh Anthropological Journal
Maharani, Mutiara Ria Despita
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Economics, Econometrics & Finance Social Sciences Other

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ANALISIS POSISI DAN TINGKAT KETERGANTUNGAN IMPOR BAWANG PUTIH INDONESIA DI PASAR INTERNASIONAL Maharani, Mutiara Ria Despita; Wulandari, Savira Putri; Aryawan, Febry; Nipu, Dian Karolin
JURNAL PERTANIAN CEMARA Vol 21 No 2 (2024): JURNAL PERTANIAN CEMARA (CENDEKIAWAN MADURA)
Publisher : Fakultas Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24929/fp.v21i2.3874

Abstract

Total permintaan bawang putih domestik tidak selaras dengan produksi bawang putih nasional sehingga berpengaruh terhadap peningkatan volume impor bawang putih. Penelitian ini memakai metode deskriptif kuantitatif untuk menganalisis posisi serta tingkat ketergantungan Indonesia terhadap impor bawang putih di pasar internasional. Analisis data menggunakan ISP (Indeks Spesialisasi Perdagangan), IDR (Import Dependency Ratio) dan DKI (Derajat Keterbukaan Impor) periode tahun 2019 hingga 2023. Hasil penelitian menunjukkan posisi perdagangan bawang putih Indonesia ditunjukkan dengan nilai ISP rata-rata sebesar -0,9 persen. Nilai ini mengindikasikan daya saing bawang putih Indonesia rendah dan cenderung sebagai negara pengimpor. Tingkat ketergantungan impor bawang putih Indonesia tercermin dalam nilai rata-rata IDR sebesar 90,64 persen, sementara nilai rata-rata DKI mencapai 3,18 persen
Ritual Larung Sesaji: Studi Etnografi Komunikasi pada Masyarakat Nelayan Kecamatan Puger Kabupaten Jember Maharani, Mutiara Ria Despita; Puspitasari, Phinky; Pramudia, Krisna Budi
Aceh Anthropological Journal Vol. 8 No. 2 (2024)
Publisher : Department of Anthropology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/aaj.v8i2.16459

Abstract

Larung Sesaji is a ritual communication that gives rise to social interactions between individuals and individuals, individuals and society, and individuals and the creator. This article aims to describe in depth the ethnography of Larung Sesaji ritual communication in the fishing community of Puger District, Jember Regency. This research uses qualitative research methods with an ethnographic approach. The data collection techniques are observation, interviews, and document study. The research results show that Larung Sesaji is considered a way to communicate by expressing gratitude to God Almighty. This tradition is seen by the fishing community as sacred which has religious values and togetherness among the fishing community as well as an effort to seek safety from various disasters.Abstrak: Larung Sesaji merupakan komunikasi ritual yang memunculkan interaksi sosial baik interaksi antar individu dengan individu, individu dengan masyarakat, dan individu dengan sang pencipta. Artikel ini bertujuan mendeskripsikan secara mendalam etnografi komunikasi ritual Larung Sesaji pada masyarakat nelayan Kecamatan Puger Kabupaten Jember. Penelitian ini menggunakan metode penelitian kualitatif dengan pendekatan etnografi. Teknik pengumpulan data menggunakan observasi, wawancara dan studi dokumen. Hasil penelitian menunjukkan bahwa Larung Sesaji dianggap sebagai cara untuk berkomunikasi dengan mengungkapkan rasa syukur kepada Tuhan Yang Maha Esa. Tradisi ini dipandang oleh masyarakat nelayan sebagai keramat yang memiliki nilai keagamaan dan kebersamaan antar masyarakat nelayan serta upaya meminta keselamatan terhadap berbagai bencana. 
PEMANFAATAN ARTIFICIAL INTELLIGENCE DALAM MANAJEMEN RANTAI PASOK PRODUK PERTANIAN TINJAUAN LITERATUR SISTEMATIK Maharani, Mutiara Ria Despita; Hifziah, Hilyatul; Muflikh, Yanti Nuraeni; Suprehatin; Rahadiarta, I Komang Pradnyananda S.
Forum Agribisnis Vol. 15 No. 2 (2025): FA Vol `15 No 2 September 2025
Publisher : Magister Science of Agribusiness, Department of Agribusiness, FEM-IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/fagb.15.2.227-242

Abstract

The agricultural product supply chain frequently faces challenges, including fluctuations in demand, climate change, and the perishable nature of products, which can result in inefficiencies and losses. These issues require technology to optimize supply chain performance, one of which is through the use of Artificial Intelligence (AI). This study aims to identify the types of AI commonly used, their applications across various stages of the supply chain, their role in enhancing efficiency, and the challenges associated with their implementation. The method used is a Systematic Literature Review (SLR) based on 21 scientific articles from 2015 to 2025 sourced from the Scopus database. Articles were selected based on criteria including journals and proceedings, open access, and relevance to AI applications in agricultural product supply chains. The research results indicate that machine learning and deep learning are the most widely used types of AI, particularly for crop yield prediction, plant disease detection, product quality classification, and logistics management. AI has been applied across various stages of the supply chain, from cultivation, processing, to distribution. AI has proven to enhance efficiency, real-time monitoring, and decision-making. However, its implementation still faces challenges such as limited quality data, inadequate infrastructure, high implementation costs, and low human resource capacity. Therefore, the utilization of AI in the agricultural product supply chain requires collaboration between the government, academia, industry, and farmers. On the other hand, regulations and policies supporting AI adoption also need further review to ensure this technology can be widely and sustainably implemented.
Predictive Trends of Major Food Prices in Indonesia: A Deep Learning Approach to Time Series Forecasting Yafi, Muhammad Ali; Maharani, Mutiara Ria Despita; Nabilla, Nur Afra; Adyanti, Amanda Sekar
Agro Ekonomi Vol 36 (2025): ARTICLE IN PRESS
Publisher : Department of Agricultural Socio-Economics Faculty of Agriculture Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ae.104454

Abstract

Price uncertainty in food commodities will have an impact on people's food consumption. Prediction of future prices is necessary to serve as a policy reference in overcoming price fluctuations. The purpose of the study is to predict the price of major agricultural food in Indonesia in 2023-2029. The research uses time series data from 1990-2022 with price variables of corn, onion red chilli, beef, and chicken. The analytical tool used to answer the research objectives is the Autoregressive Integrated Moving Average (ARIMA) model. The results of the analysis obtained the best model for predicting price forecasts, namely ARIMA on corn commodities (1,1,0), shallots (2,1,0), red chillies (1,1,0), beef (0,1,1), and chicken meat (1,1,1). The results of the prediction of the price of Indonesia's food needs in 2023-2029 as a whole tend to increase.
Co-Authors Adyanti, Amanda Sekar Aryawan, Febry Hifziah, Hilyatul Nabilla, Nur Afra Nipu, Dian Karolin Pramudia, Krisna Budi Puspitasari, Phinky Rahadiarta, I Komang Pradnyananda S. Suprehatin Wulandari, Savira Putri YAFI, MUHAMMAD ALI Yanti Nuraeni Muflikh