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All Journal Jurnal Fisika Unand Prosiding National Conference for Community Service Project Jurnal Sains dan Teknologi SENTRI: Jurnal Riset Ilmiah Lontar Physics Today Journal of Multiscale Materials Informatics
Dian Arif Rachman
Institut Teknologi dan Sains Nahdlatul Ulama Pekalongan
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Veterinary

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PEMANFAATAN LPG SEBAGAI BAHAN BAKAR ALTERNATIF MESIN GENSET PADA KELOMPOK TANI SRI MUMPUNI, DESA DUWET KABUPATEN PEKALONGAN Dian Arif Rachman; Heri Kiswanto
National Conference for Community Service Project (NaCosPro) Vol 2 No 1 (2020): The 2nd National Conference of Community Service Project 2020 (Accepted Papers)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/nacospro.v2i1.1166

Abstract

The human need for food is increasing every day. During the Covid-19 pandemic, disruption of food production is an important matter that must be addressed immediately. One problem that is often faced by farmers as food producers in Indonesia is the problem of drought during the prolonged dry season so that it is threatened with crop failure. Farmers really need this generator modification training because it can reduce the operational costs of rice field irrigation. It is hoped that this service activity can provide new knowledge and help farmers overcome rice fields dryness by using a generator set with LPG fuel.
Pengaruh Jarak Elektroda dan Waktu Terhadap Kandungan COD dan TSS Menggunakan Metode Filtrasi-Elektrokoagulasi pada Pengolahan Limbah Batik Elvinda Bendra Agustina; Abdul Hakim Prima Yuniarto; Dian Arif Rachman; Alif Tiana Dewi
Lontar Physics Today Vol 1, No 1 (2022): Februari 2022
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/lpt.v1i1.10669

Abstract

Produksi batik menghasilkan limbah cair yang memiliki dampak negatif terhadap lingkungan karena bahan kimia hasil pengolahan.  Metode filtrasi-elektrokoagulasi dirasa efektif untuk menurunkan kandungan COD dan TSS pada limbah cair batik sehingga layak buang. Telah dilakukan pengolahan limbah batik menggunakan metode filtrasi-elektrokoagulasi dengan variasi jarak elektroda (2, 4, dan 6) cm dan waktu kontak (60, 90, 120 dan 150) menit. Digunakan elektroda alumunium (Al-Al) dengan ketebalan 0,1 cm dan volume limbah 2500 ml. Hasil penelitian menunjukkan efisiensi penurunan COD dan TSS tertinggi pada variasi jarak 2 cm dengan waktu kontak 150 menit. Efisiensi penurunan COD sebesar 95% sedangkan efisiensi penurunan TSS sebesar 94%. Hasil tersebut menunjukkan bahwa semakin dekat jarak antar elektroda dan semakin lama waktu kontak maka semakin tinggi penurunan kandungan COD dan TSS.Keywords: Filtrasi-elektrokoagulasi, Limbah batik, COD, TSS
Desain Sistem Smart Feeder Ayam Berbasis Internet of Things (IoT) Guna Mencegah Keterlambatan Pemberian Pakan Elvinda Bendra Agustina; Dian Arif Rachman; Recha Nofillah; Lia Ikhlasia Fitri
Jurnal Fisika Unand Vol 13 No 2 (2024)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.13.2.297-302.2024

Abstract

Pemberian pakan ayam secara manual menjadikan pemberian pakan ayam kurang efektif dan efisien. Pengembangan sistem pemberi pakan ayam cerdas berbasis Internet ofThings (IoT) telah dilakukan. Penelitian ini bertujuan untuk mengembangkan desain sistem smart feeder ayam berbasis IoT guna mencegah keterlambatan pemberian pakan. Memungkinkan alat bekerja dengan melakukan kontrol feeder berdasarkan pengaturan waktu, monitoring hopper secara otomatis yang diintegrasikan dengan IoT. Setiap device dihubungkan dengan internet sehingga dapat dipantau dari jarak jauh. Metode yang digunakan adalah perancangan dan telah dilakukan uji dan pengambilan data. Hasil uji aplikasi Blynk menunjukkan ketepatan pengaturan yang telah diberikan dengan kondisi real. Fungsi sistem alat sudah sesuai dengan desain sistem yang direncanakan. Rata-rata persentase error yang terjadi 14% secara keseluruhan tetapi mengecil sampai rata-rata 3% pada berat pakan diatas 5 kg dikarenakan semakin besar volume hopper maka jarak antara sensor ke pakan semakin dekat sehingga nilai error semakin rendah. Pengujian NTP menunjukkan nilai akurasi dan kepresisian 100%. Uji kecepatan rotasi menunjukkan rata-rata kecepatan rotasi hopper yaitu 445,4 rpm sehingga hopper berotasi sesuai dengan perkiraan. Uji volume distribusi pakan sudah sesuai karna pakan 1 diletakkan paling dekat dengan hopper sehingga volume pakan akan terisi paling banyak di bandingkan dengan tempat pakan lainnya
System Design Of Printer Machine Using Image Classification Method Based On Iot To Optimize Production Output Yusril Ihza Tachriri; Elvinda Bendra Agustina; Dian Arif Rachman; Atika Windra Sari; Muhammad Rofiqul A’la; Muhammad Lutfhi Al Hisyam; Muhammad Irfan
SENTRI: Jurnal Riset Ilmiah Vol. 5 No. 3 (2026): SENTRI : Jurnal Riset Ilmiah, Maret 2026
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v5i3.5986

Abstract

The micro, small, and medium enterprises (MSMEs) industry plays a crucial role in supporting the Indonesian economy, yet faces challenges in production efficiency and cost management. This study presents the design and development of an IoT-based automated screen-printing system that integrates edge-based image classification using a CNN model with microcontroller-driven print actuation, specifically tailored for MSME-scale garment production. The system employs an ESP32/Raspberry Pi as the edge device, enabling local inference without cloud dependency, and utilizes MQTT protocol for IoT connectivity. Quantitative evaluation across 50 test cycles demonstrated a 96% printer success rate, a 60% reduction in production time from 45 to 18 minutes per 10 shirts, a 90% reduction in labor from 10 operators to 1, and an approximately 50% reduction in per-unit production cost from Rp65,000–80,000 to Rp30,000–40,000 per shirt. IoT connectivity testing over 48 continuous hours recorded an average MQTT latency of 120 ms and a system uptime of 98.5%, confirming the reliability of the communication layer for sustained production operations. Grounded in Industry 5.0 principles, this research advances human-machine collaboration in small-scale manufacturing contexts. The proposed system offers a cost-effective, remotely controlled, and semi-autonomous production solution, representing a novel contribution to the field of IoT-based garment manufacturing in Indonesia.
Ensemble Learning Model in Predicting Corrosion Inhibition Capability of Pyridazine Compounds Dian Arif Rachman; Muhamad Akrom
Journal of Multiscale Materials Informatics Vol. 1 No. 1 (2024): April
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jimat.v1i1.10502

Abstract

Empirical studies of possible compound corrosion inhibitors require a lot of money, time, and resources. Therefore, we used a machine learning (ML) paradigm based on quantitative structure-property relationship (QSPR) models to evaluate ensemble algorithms as predictors of corrosion inhibition efficiency (CIE) values. Our investigation reveals that the gradient boosting (GB) regressor model outperforms other ensemble-based models. This advantage is evaluated objectively using the metrics root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). In summary, our research provides a new perspective on how well machine learning algorithms in particular ensembles work to identify organic molecules such as pyridazine that have the potential to prevent corrosion on the surfaces of metals such as iron and its alloys.
Variational Quantum Circuits Design Principles, Applications, and Challenges Toward Practical: A Review Dian Arif Rachman; Muhamad Akrom
Journal of Multiscale Materials Informatics Vol. 2 No. 2 (2025): Oktober
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jimat.v2i2.14935

Abstract

Variational Quantum Circuits (VQCs) have emerged as a cornerstone of hybrid quantum–classical algorithms designed to harness the computational potential of near-term quantum devices. By combining parameterized quantum gates with classical optimization, VQCs provide a flexible framework for tackling machine learning, chemistry, and optimization problems intractable for classical methods. This review comprehensively overviews VQC design principles, ansatz structures, optimization strategies, and real-world applications. Furthermore, we discuss fundamental challenges such as barren plateaus, the expressibility–trainability trade-off, and current noisy intermediate-scale quantum (NISQ) hardware limitations. Finally, we highlight emerging directions that could enable scalable, noise-resilient, and physically interpretable variational quantum models for future quantum computing applications
Rancang Bangun Smart Feeder Terintegrasi Monitoring Kualitas Air Bertenaga Surya Berbasis IoT pada Budidaya Perikanan Elvinda Bendra Agustina; Dian Arif Rachman; Yusril Ihza Tachriri; Jessika Artamevira; Khusfiatul Kholisah
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 6 (2025): Desember 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i6.6658

Abstract

This study presents the design and implementation of a smart feeder system integrated with real-time water quality monitoring powered by a solar photovoltaic system and based on the Internet of Things (IoT). The system automatically dispenses fish feed and monitors key water quality parameters such as pH, temperature, and Total Dissolved Solids (TDS). The ESP32 microcontroller was used as the main controller, integrated with multiple sensors and an MQTT-based monitoring application. The entire system is powered by a 30 Wp solar panel and a 12 V battery, enabling autonomous operation in remote areas without grid access. Experimental results show that motor rotation speed significantly affects feed distribution. The optimal feeding performance was achieved at medium motor speed with a feed distance of 8 m, ensuring uniform feed dispersion and low energy consumption (±14.4 W). Water quality parameters remained within the ideal range for freshwater aquaculture: pH 6.6–6.9, temperature 27.5–28.8 °C, and TDS 380–450 ppm. The photovoltaic system generated around 90–110 Wh/day, meeting the system’s daily energy demand (±45 Wh/day). This integrated IoT–solar solution demonstrates high efficiency and sustainability, suitable for rural aquaculture applications.
Co-Authors Abdul Hakim Prima Yuniarto Alif Tiana Dewi Atika Windra Sari Elvinda Bendra Agustina Elvinda Bendra Agustina Heri Kiswanto Jessika Artamevira Khusfiatul Kholisah Lia Ikhlasia Fitri Muhamad Akrom Muhammad Irfan Muhammad Lutfhi Al Hisyam Muhammad Rofiqul A’la Recha Nofillah Yusril Ihza Tachriri Yusril Ihza Tachriri