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All Journal Exact Paper In Compilation (EPIC) Jurnal Informatika: Jurnal Pengembangan IT
Putri, Nadira Hijriani
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science

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The Optimalisasi Produksi di Sentra Pandai Besi Desa Blumbungan Menggunakan Metode Simplex Solver Putri, Nadira Hijriani
Exact Papers in Compilation (EPiC) Vol 6 No 2 (2024): Mei 2024
Publisher : Lembaga Penelitian Pengabdian Masyarakat Universitas KH. A. Wahab Hasbullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/epic.v6i2.1163

Abstract

Desa Blumbungan terkenal sebagai sentra produksi besi dengan pengrajin handal dan peralatan modern. Penggunaan mesin-mesin canggih ini telah meningkatkan kapasitas produksi dan kualitas produk yang dihasilkan. Namun, proses produksi sering terhambat oleh ketidakpastian pasokan bahan baku, yang dapat mengganggu kelancaran produksi dan menurunkan efisiensi. Penelitian ini bertujuan untuk mengoptimalkan produksi di Sentra Pandai Besi Desa Blumbungan menggunakan metode Simplex Solver Excel. Hasil penelitian menunjukkan bahwa penggunaan metode Simplex Solver Excel dapat memberikan solusi optimal dalam menghadapi kendala bahan baku dan dapat mencapai produksi maksimum 10 produk per hari, meskipun data produk yang dihasilkan dapat berubah tergantung pada kinerja karyawan dan ketersediaan bahan. penelitian ini diharapkan dapat memberikan kontribusi signifikan dalam pengembangan industri pandai besi di desa tersebut, serta menjadi acuan bagi sentra produksi lainnya yang menghadapi masalah serupa.
Prediksi Kebutuhan Beras Di Jawa Timur Menggunakan Metode Gated Recurrent Unit (GRU) Hozairi, Hozairi; Muhsi, Muhsi; Putri, Nadira Hijriani
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8790

Abstract

Food security is a strategic issue that affects economic stability and community welfare, especially in ensuring the availability of rice as a staple food in East Java. Uncertainty in food planning can cause an imbalance between rice production and consumption. Consequently, a precise forecast technique is necessary to aid decision-making. The objective of this research is to forecast or predict rice needs using the Gated Recurrent Unit (GRU) model to support more effective food management. The research methods include Min-Max Scaling normalization, and data division into 80% training and 20% testing. The GRU model has two main layers with 64 and 32 neuron units, The system was trained for 100 epochs with a batch size of 32 using the Adam optimizer and the MSE loss function. The evaluation results show high performance with MAE 0.0103, MSE 0.0001, RMSE 0.0116, and R² 0.9935, indicating low error and good generalization. The Training and Validation Loss graph shows a stable learning model without overfitting. This model can be a reliable prediction tool in food planning. Implementation of the model can help the government maintain the balance of rice supply and optimize agricultural policies.
Co-Authors Hozairi Muhsi, Muhsi