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All Journal ARMATUR : Artikel Teknik Mesin dan Manufaktur Go-Integratif : Jurnal Teknik Sistem dan Industri Jurnal Gerakan Mengabdi untuk Negeri
Hidayat, Alif Nur
Unknown Affiliation
Aerospace Engineering Humanities Automotive Engineering Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Mechanical Engineering Public Health Social Sciences Other

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Pemodelan Prediksi Temperatur Freezer Menggunakan Pendekatan Machine Learning Berbasis Framework TensorFlow Davi, Ahmad; Sidiq, Farkhan Jatmiko; Arrizal, Muhammad Aziz; Wibowo, Fahrizal Agil; Gunawan, Taopik Sendy; Aisyah, Andini Nur; Hidayat, Alif Nur
Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 5 No 02 (2024): Go-Integratif : Jurnal Teknik Sistem dan Industri
Publisher : Engineering Faculty at Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35261/gijtsi.v5i02.12524

Abstract

Temperature control in freezers is crucial to maintaining product quality and safety, particularly in the food and pharmaceutical industries. Uncontrolled temperature fluctuations can lead to product damage, increased waste, and reduced quality. Machine learning technology offers an effective solution for predicting and controlling temperature, enabling more accurate monitoring and rapid responses to changing conditions. This study aims to develop a machine learning model using the TensorFlow framework to predict freezer temperatures. Temperature data were collected from sensors installed inside the freezer and used to train and test several machine learning architectures, including Long Short-Term Memory (LSTM) and 1D Convolutional (Conv1D) networks. Model development leveraged TensorFlow's advanced features, enabling efficient model creation, training, and testing. The results show that the Conv1D model with a data composition of 90% training, 5% validation, and 5% testing achieved the best predictions, with a test RMSE of 0.02085°C and a test MAPE of 0.33522%. This predictive model has the potential to be used as an early warning system to prevent product damage. This research is expected to significantly contribute to the development of more efficient temperature monitoring and control systems in freezers, with potential applications across industries such as food and pharmaceuticals. The findings also reinforce the substantial potential of machine learning in environmental prediction and monitoring.
Pelatihan Pembuatan Hantaran Sebagai Upaya Pemberdayaan Warga Desa Triwarno Dalam Meningkatkan Keterampilan dan Kreativitas Sidi, Zahra; Agesta, Risa; Dewanti, Anisa Prilia; Rahma, Femi Clarissa; Hidayat, Alif Nur; Wahyuningsih, Rani; Subhi, Ilham Aditia; Chandra, Ranita Helvy; Surakhman, Vicky Agustin; Ihsan, Hanan Muhammad
Jurnal Gerakan Mengabdi untuk Negeri Vol. 4 No. 1 (2026)
Publisher : Universitas Muhammadiyah Purworejo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37729/gemari.v4i1.7440

Abstract

Tradisi seserahan dalam masyarakat Jawa memiliki makna simbolis yang kuat, namun keterampilan masyarakat desa dalam mengemas dan menghias hantaran masih terbatas sehingga hasil karya cenderung sederhana dan kurang bernilai estetika. Tujuan kegiatan pengabdian ini untuk meningkatkan keterampilan teknis dan kreativitas ibu-ibu PKK desa Triwarno sekaligus memperkenalkan strategi pemasaran digital untuk mendukung pengembangan ekonomi kreatif berbasis budaya lokal. Metode pelaksanaan kegiatan meliputi tahap persiapan, demonstrasi teknik dasar pembuatan hantaran, praktik berkelompok dengan pendampingan mahasiswa KKN, serta monitoring dan evaluasi. Mitra kegiatan adalah ibu-ibu PKK desa Triwarno yang berjumlah sekitar 40 orang. Hasil kegiatan menunjukkan adanya peningkatan signifikan: keterampilan teknis peserta meningkat dari skor 50%, sedangkan kreativitas meningkat dari 27% dari peserta yang mampu menghasilkan variasi bentuk hantaran dengan dekorasi kreatif. Pelatihan berbasis praktik langsung dan pendampingan kelompok kecil efektif dalam meningkatkan keterampilan dan kreativitas ibu-ibu PKK. Integrasi dengan pelatihan marketplace digital memperkuat aspek pemberdayaan ekonomi, sehingga tradisi seserahan tidak hanya dilestarikan tetapi juga dapat dikembangkan menjadi peluang usaha. Rekomendasi dari kegiatan ini adalah perlunya pelatihan lanjutan, pendampingan usaha, serta dukungan kelembagaan agar keterampilan yang diperoleh dapat berkelanjutan dan memberikan kontribusi nyata terhadap kesejahteraan masyarakat desa.
Analisis Hidrodinamika dan Karakteristik Pressure Drop pada Fotobioreaktor Flat-Panel Sistem Closed-Loop Menggunakan Computational Fluid Dynamics hidayat, alif nur; Sena , Boni; Siswadi; Agustin , Aisyah; Aprellya, Putri; Herlambang, Pratikara
ARMATUR : Artikel Teknik Mesin & Manufaktur Vol. 7 No. 2 (2026): Jurnal Armatur (in Progress)
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/armatur.v7i2.11250

Abstract

Hydrodynamic performance plays a crucial role in determining flow distribution and hydraulic losses inside flat-panel photobioreaktor systems. This study aims to investigate the flow characteristics and pressure drop behavior of a closed-loop flat-panel photobioreaktor using a Computational Fluid Dynamics (CFD) approach. A three-dimensional steady and incompressible laminar model was employed with water as the working fluid. Inlet velocities of 0.01 m/s, 0.03 m/s, 0.05 m/s, and 0.1 m/s were applied to evaluate their influence on velocity distribution, streamline patterns, and pressure drop. A grid independence study was conducted using three mesh densities, and the final mesh with an element size of 0.015 m showed less than 1% variation in pressure drop, confirming mesh-independent results. The simulation results indicate that increasing inlet velocity significantly increases pressure drop and maximum velocity within the reaktor due to flow acceleration near the inlet region. Streamline analysis reveals the formation of recirculation zones in the lower section of panel.
Co-Authors Agesta, Risa Agustin , Aisyah Aisyah, Andini Nur Aprellya, Putri Arrizal, Muhammad Aziz Chandra, Ranita Helvy Davi, Ahmad Dewanti, Anisa Prilia Gunawan, Taopik Sendy Herlambang, Pratikara Ihsan, Hanan Muhammad Rahma, Femi Clarissa Sena , Boni Sidi, Zahra Sidiq, Farkhan Jatmiko Siswadi Subhi, Ilham Aditia Surakhman, Vicky Agustin Wahyuningsih, Rani Wibowo, Fahrizal Agil