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All Journal Habitat AGRARIS: Journal of Agribusiness and Rural Development Research JMM (Jurnal Masyarakat Mandiri) JAST : Jurnal Aplikasi Sains dan Teknologi
Destyana Ellingga Pratiwi
Department Of Agricultural Socio-Economics, Faculty Of Agriculture, Universitas Brawijaya, Jl. Veteran Kota Malang 65145, Indonesia
Agriculture, Biological Sciences & Forestry Economics, Econometrics & Finance Education Engineering Environmental Science Social Sciences Other

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Risk Mitigation Strategies in Semi-Organic Rice Supply Chains: Lesson Learned from the Involved Actors Agustina Shinta Hartati Wahyuningtyas; Novi Haryati; Destyana Ellingga Pratiwi; Luisa Maliny Situmeang
AGRARIS: Journal of Agribusiness and Rural Development Research Vol 7, No 2: July-December 2021
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.263 KB) | DOI: 10.18196/agraris.v7i2.10126

Abstract

Rice is the main consumption food for Indonesians. The demand for food increased from 114.6 kg per capita in 2016 to 124.89 kg in 2017. However, rice farmers and supply chain actors in rice agribusiness have experienced high challenges, such as production, transportation, price, product quality, and the environment. This research aimed to understand actors involved in the supply chain, their perception of occurring risks, and evaluation and risk mitigation in the supply chain. This was a quantitative descriptive study done purposively in Watugede Village, Singosari Sub-District, Malang Regency. Non-probability sampling was taken to gather primary data. The respondent of this research was 16 involved actors, from on-farm actors to consumers. The data were analyzed using the Fuzzy analytical hierarchy process (FAHP) to provide descriptive risk mitigation strategies. The results show that six involved actors are suppliers, farmers, grinders, traders, and buyers. Each actor faces different risks, and thus, the recommended mitigation strategies are adjusted to their risks. Sharing information, optimizing the level of supply availability, measuring supply chain performance, and building more coordination with the government are the best strategies to mitigate risks.
PEMBERDAYAAN PEREMPUAN SEBAGAI AGEN PENGGERAK DALAM PENGOLAHAN SAMPAH DAPUR MENJADI ECO ENZYME Agustina Shinta Hartati Wahyuningtyas; Anisa Aprilia; Tri Ardyati; Kiki Fibrianto; Fahriyah Fahriyah; Riyanti Isaskar; Arie Srihardyastutie; Destyana Ellingga Pratiwi; Vi’in Ayu Pertiwi; Yusri Fajar
JMM (Jurnal Masyarakat Mandiri) Vol 7, No 1 (2023): Februari
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v7i1.12000

Abstract

Abstrak: Peningkatan jumlah penduduk mengakibatkan adanya peningkatan produksi sampah, utamanya limbah organik rumah tangga yang dapat menimbulkan dampak buruk bagi lingkungan maupun kesehatan masyarakat jika tidak diimbangi dengan pengelolaan sampah yang tepat. Tujuan kegiatan pengabdian ini adalah untuk mengembangkan pengetahuan, kesadaran, dan kebiasaan baik terutama bagi kaum perempuan agar mampu mengolah sampah atau limbah rumah tangga menjadi eco enzyme. Metode pengabdian meliputi persiapan, sosialisasi, dan pelatihan. Mitra dari kegiatan ini adalah kelompok ibu-ibu PKK RW VII Kelurahan Lesanpuro, Kecamatan Kedungkandang, Kota Malang dengan jumlah peserta yang terlibat sebanyak 86 20 orang. Hasil dari kegiatan tersebut, yaitu peserta dapat membuat dan melestarikan eco enzyme yang didukung dengan hasil evaluasi di mana peserta memiliki peningkatan pemahaman terkait pengolahan sampah dari aspek pengetahuan, kebiasaan, dan kepedulian.Abstract: The growth of population causes the increase of waste production, especially household waste which can cause a negative impact for environment and health if it isn't used the right waste’s management. The community service aims to increase the knowledge, awareness, and good habits to manage household waste into eco enzymes. The first method of this service is preparation, and then followed by socialization. And also training. The partners are the women of RW VII, who are the member of PKK group in the Kelurahan Lesanpuro of Kecamatan Kedungkandang, Kota Malang. There are 86 women involved. The result of the activity shows that participants can make and preserve eco enzymes, which is supported by the evaluation result. It shows that the participants understanding about organic waste management have increased based on the aspects of knowledges, habits, and care. 
Pelatihan Smart Multi-Culture Farming Berbasis Teknologi Cloud-AI untuk Pemantauan Objek Budidaya dengan Tenaga Surya sebagai Eco-Green Energy Masyarakat Indonesia Nurudin Santoso; Imam Cholissodin; Arief Andy Soebroto; Nurul Hidayat; Sutrisno Sutrisno; Destyana Ellingga Pratiwi; Vivien Fathuroya
JAST : Jurnal Aplikasi Sains dan Teknologi Vol 6, No 2 (2022): EDISI DESEMBER 2022
Publisher : Universitas Tribhuwana Tunggadewi Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33366/jast.v6i2.4015

Abstract

Working in multicultural agriculture is exhausting and has several bad risks for farmers in rural and urban areas. The risks start from the considerable time required in cultivation, especially when maintaining the growth and development of plants and other cultivation objects, the large number of costs required in the use of irrigation for fuel purchases, and the risk of carrying out specific processes using high voltage electricity which is very dangerous for farmers. Based on these problems, an automated technology approach that can work to help farmers is necessitated. In this community service, two partners are involved, i.e., a group of farmers who are also workers in Kampung Kauman RW/RT III/03 as the primary partner and a group of farmers who are also workers at the plantation in Poncokusumo Malang as the supporting partner. Both partners used solar electricity for irrigation and other uses through the Cloud-AI approach obtained from the results of multi-disciplinary research several years earlier at the Filkom UB Intelligent Computing Laboratory. Cloud-AI can work adaptively according to weather conditions from a Web App from application programming interface (API) data to provide recommendations for predicting the length of time for irrigation in observing cultivation objects which later can be modified for other particular purposes. The activity's primary results are providing training and assistance with intelligent multi-culture farming installation tools for hydroponics, solar panels, and pumps for irrigation: cloud-AI-based agricultural training modules and educational videos with excellent responses from the partners.ABSTRAKProses pengerjaan bidang pertanian multi-culture sangat menguras banyak tenaga dan memiliki beberapa resiko kurang baik bagi petani, baik di pedesaan maupun perkotaan. Mulai dari waktu yang cukup banyak dibutuhkan dalam pembudidayaan terutama saat pemeliharaan tumbuh kembangnya tanaman maupun objek budidaya lainnya, lalu banyaknya biaya yang dibutuhkan dalam penggunaan irigasi untuk pembelian bahan bakar serta resiko ketika melakukan proses tertentu menggunakan listrik tegangan tinggi yang sangat membahayakan petani. Berdasarkan permasalahan tersebut dibutuhkan pendekatan teknologi otomasi yang dapat bekerja membantu petani. Dalam pengabdian ini melibatkan Dua Mitra, yaitu di kelompok petani yang sekaligus pekerja Kampung Kauman RW/RT III/03 dan pada Perkebunan di Poncokusumo Malang yang memanfaatkan listrik tenaga surya untuk irigasi dan kegunaan lainnya serta pendekatan Cloud-AI yang dapat bekerja secara adaptif baik luring maupun daring untuk mengendalikan kelistrikan, prediksi untuk pengambilan keputusan dalam pengamatan objek budidaya dan lainnya. Hasil utama kegiatan berupa pemberian pelatihan, lalu bantuan paket alat instalasi smart multi-culture farming untuk hidroponik, panel surya dan pompa untuk irigasi serta modul pelatihan pertanian berbasis Cloud-AI dan video edukasi dengan respon yang sangat baik dari Mitra.
Comparative Study of SVR, Regression and ANN Water Surface Forecasting for Smart Agriculture Arief Andy Soebroto; Imam Cholissodin; Destyana Ellingga Pratiwi; Guruh Prayogi Willis Putra
HABITAT Vol. 33 No. 1 (2022): April
Publisher : Department of Social Economy, Faculty of Agriculture , University of Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.habitat.2022.033.1.9

Abstract

In the smart agriculture system based on green-based technology of artificial intelligence (AI), flooding can be predicted early by forecasting the water surface and good agricultural irrigation. The process of rising and falling of the water surface in a water basin area can be explained theoretically, but since there are many related variables and the complexity of dependencies between variables, the mathematical model is difficult to construct. Forecasting water surface in the field of irrigation needs too many variable parameters, such as cross-sectional area, depth, volume of rivers and so on. Based on patterns in each period, forecasting can be done using a statistical method and AI. This study uses the support vector regression (SVR) method, regression, multiple linear regression, and algorithm backpropagation, all compared to one another. The results of tests carried out between SVR and multiple linear regression show that SVR is superior. This can be seen from the result of the mean square error (MSE) obtained for each method. SVR 0.03 and for multiple linear regression, 0.05. The result is also supported by the best MSE result in the regression method, which is 0.338, and the best MSE value in artificial neural network (ANN), which is 0.428.
Co-Authors Agustina Shinta Hartati Wahyuningtyas Anisa Aprilia Arie Srihardyastutie Arief Andy Soebroto Fahriyah Fahriyah Guruh Prayogi Willis Putra Imam Cholissodin KIKI FIBRIANTO Luisa Maliny Situmeang Novi Haryati Nurudin Santoso Nurul Hidayat Riyanti Isaskar Sutrisno Sutrisno Tri Ardyati Vivien Fathuroya Vi’in Ayu Pertiwi Yusri Fajar