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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) IMTechno: Journal of Industrial Management and Technology
Adly, Sulthan
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Computer Science & IT Industrial & Manufacturing Engineering

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Digitalisasi Layanan Publik Melalui Platform Terintegrasi Berbasis Laravel Rahmawati, Mari; Supriyatna, Adi; Adly, Sulthan; Suryani, Rani; Saridawati, Saridawati; Sabariah, Etika; Indrarti, Wahyu
IMTechno: Journal of Industrial Management and Technology Vol. 7 No. 1 (2026): Vol. 7 No. 1 (2026): Januari 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/imtechno.v7i1.11488

Abstract

Abstrak - Pelaporan infrastruktur di tingkat desa, masih banyak dilakukan secara manual, sehingga menimbulkan berbagai kendala seperti keterlambatan penanganan, kehilangan data, dan minimnya transparansi antara warga dan pihak desa. Untuk mengatasi permasalahan tersebut, penelitian ini bertujuan merancang sistem pelaporan infrastruktur desa berbasis web Laravel yang mempermudah masyarakat dalam melaporkan kerusakan fasilitas umum secara mandiri dan terstruktur. Sistem ini dikembangkan menggunakan metode Rapid Application Development (RAD) yang memungkinkan proses pengembangan dilakukan secara cepat melalui tahapan iteratif dan keterlibatan langsung pengguna. Hasil pengembangan menunjukan bahwa sistem dapat berfungsi dengan baik sesuai kebutuhan tiga peran utama: warga, admin desa, dan kepala desa. Sistem ini juga dilengkapi dengan fitur validasi laporan, unggah bukti foto, serta rekap data dalam format PDF. Penerapan metode RAD terbukti mampu meningkatkan efisiensi waktu pengembangan dan menghasilkan sistem yang adaptif terhadap kebutuhan pengguna. Secara umum, sistem ini memberikan manfaat berupa peningkatan transparansi, partisipasi masyarakat, serta akuntabilitas dalam pengelolaan infrastruktur desa. Kata Kunci: Infrastruktur, RAD, Laravel
OPTIMIZING CAYENNE PEPPER PRICE FORECASTING USING HYBRID SARIMAX-LSTM MODEL FOR FOOD SECURITY Supriyatna, Adi; Rahmawati, Mari; Rabbani, Burhanudin; Wenang, Asta; Adly, Sulthan
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 4 (2026): JITK Issue May 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i4.7917

Abstract

The price volatility of cayenne pepper in traditional markets significantly impacts household purchasing power and regional inflation. While traditional statistical models can capture seasonal patterns, they often fail to model complex non-linear fluctuations driven by external factors such as weather anomalies and national holidays. To address these limitations, this study proposes a hybrid SARIMAX-LSTM model. The Seasonal AutoRegressive Integrated Moving Average with eXogenous variables (SARIMAX) component is utilized to model linear structures, seasonality, and the influence of exogenous variables (temperature, rainfall, and holidays), whereas the Long Short-Term Memory (LSTM) component specifically models the remaining non-linear patterns within the residuals. Daily data comprising chili prices, weather metrics, and holiday schedules were employed to train and test the model using Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) as performance metrics. Experimental results demonstrate that the proposed hybrid model significantly outperforms the single SARIMAX baseline model, reducing the RMSE by 26.7% (from 11.09 to 8.13) and MAPE by 28.6% (from 23.45% to 16.74%). This approach not only provides a more accurate and robust decision-support tool for price stability but also contributes to the advancement of artificial intelligence-based hybrid methods in the domain of food security.
Co-Authors Adi Supriyatna Etika Sabariah Mari Rahmawati Rabbani, Burhanudin Saridawati Suryani, Rani Wahyu Indrarti Wenang, Asta