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Meningkatkan Produktivitas Budidaya Hidroponik di Lahan Terbatas Menggunakan Metode PDCA Elsa Amanda Putri; Olif Aulia; Nabila Dwi Isa Melandari; Jessica Mayddy Amanda; Amanda Dian Rahmawati
Hidroponik : Jurnal Ilmu Pertanian Dan Teknologi Dalam Ilmu Tanaman Vol. 1 No. 2 (2024): July: Hidroponik: Jurnal Ilmu Pertanian Dan Teknologi Dalam Ilmu Tanaman
Publisher : Asosiasi Riset Ilmu Tanaman Dan Hewan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/hidroponik.v1i2.82

Abstract

17 August 1945, University Surabaya has expanded its limited green space and educated students and the community about plant development without planting material, or it is referred to as contemporary farming by using the rooftop area on the third level of the Engineering Building (Q) for hydroponic plant cultivation. Using the PDCA (Plan, Do, Check, Action) method, one may improve the productivity of plants in hydroponic farming. The NFT (Nutrient Film Technique) system, which consists of three pipes stacked in parallel places, is used in the design of the hydroponic growing system. Rockwool, flannel cloth, plastic cups, nutrients, and a pH or TDS (Total Dissolved Solid) measuring device are among the equipment and supplies utilized. Choosing plants that can be used on small amounts of land are.    
System Dynamics Simulation of Semi-Organic Fertilizer and Pest Management Scenarios to Enhance Sustainable Food Security in Bungur Village Amanda Dian Rahmawati; Murnawan, Hery
Indonesian Journal of Engineering and Technology (INAJET) Vol. 8 No. 1 (2025): September 2025
Publisher : Fakultas Teknik Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/inajet.v8n1.p25-32

Abstract

This study investigates agricultural sustainability and food security in Bungur Village, Nganjuk Regency, East Java, by addressing critical challenges such as an aging farming population, heavy reliance on chemical fertilizers, and recurring pest infestations. To identify key determinants, Structural Equation Modelling–Partial Least Squares (SEM–PLS) was employed, while system dynamics modeling using STELLA software was applied to simulate three alternative intervention scenarios. The simulation results demonstrate that the adoption of semi-organic fertilizers increases profit by approximately 1% (Rp106.4 million), the use of environmentally friendly pest management enhances profit by 12% (Rp117.8 million), and the combined application of both strategies yields the highest improvement, with a 16% increase (Rp122.3 million) compared to the baseline condition (Rp105.6 million per hectare annually). Model reliability was confirmed through validation tests using mean comparison error (≤5%) and variance explained (≤30%). These findings highlight that integrated interventions are effective in improving productivity, profitability, and sustainability, while also providing incentives to encourage greater youth participation in agriculture. Nonetheless, the scope of this study is limited to Bungur Village and focuses exclusively on rice, shallots, and corn, without accounting for farmer-level heterogeneity. Future studies are recommended to extend the model to wider geographical contexts and incorporate factors such as climate variability and market fluctuations.
Penerapan K-Means Clustering Untuk Strategi Promosi Untuk Meningkatkan Jumlah Perolehan Mahasiswa Baru Herlina, Herlina; Siti Mundari; Elsa Amanda Putri; Amanda Dian Rahmawati
JOURNAL OF INDUSTRIAL AND MANUFACTURE ENGINEERING Vol. 8 No. 1 (2024): EDISI MEI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jime.v8i1.10928

Abstract

Tiap tahun di sebuah program studi pasti ada mahasiswa baru yang masuk yang berasal dari berbagai wilayah. Penelitian ini bertujuan menganalisis data mahasiswa di prodi Teknik Industri Untag Surabaya berdasarkan sebaran asal SMA, program peminatan saat menempuh studi di SMA, jenis kelamin, jarak kedekatan rumah tempat tinggal dengan kampus, dan jenis pekerjaan orang tua. Data yang diperoleh akan diolah menggunakan algoritma K-Means Clustering. Data-data yang memiliki kesamaan karakteristik akan dikelompokkan menjadi satu klaster, sedangkan data dengan karakteristik yang berbeda akan dikelompokkan dalam klaster yang lainnya. Klaster yang terbentuk akan dibagi tiga yaitu tinggi, sedang dan rendah. Dari klaster yang tinggi akan dianalisis potensi terbesar yang dapat digunakan sebagai strategi marketing untuk meningkatkan jumlah mahasiswa baru di periode mendatang. Dari hasil pengolahan data menggunakan Rapidminer, diperoleh hasil cluster 0 terdiri dari 75 data, cluster 1 sebanyak 31 data, cluster 2 sebanyak 55 data. Dari hasil clustering, atribut yang membedakan cluster secara signifikan adalah jarak tempat tinggal ke kampus. Dari cluster yang tertinggi diperoleh data rata-rata jarak tempat tinggal mahasiswa ke kampus adalah 4,6 km dengan jangkauan antara 0,1 km sampai 10 km. Promosi dapat lebih ditingkatkan pada daerah-daerah dengan jangkauan jarak yang lebih jauh agar menambah perolehan jumlah mahasiswa baru.