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Ischak, Rabbani
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Agriculture, Biological Sciences & Forestry Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Mechanical Engineering Social Sciences Transportation

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Inovasi kapal bertenaga panel surya sebagai implementasi energi baru terbarukan dalam transportasi laut Palembangan, Semuel; Nursyamsu, Nursyamsu; Irwansyah, Rudi Harun; Peramutya, Alvian Demaz; Santoso, Rahmat; Amirullah, Amirullah; Hidayatuloh, Ade Taopik; Ischak, Rabbani
Journal Marine Inside Vol. 7 No. 1 (2025)
Publisher : Politeknik Pelayaran Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62391/ejmi.v7i1.137

Abstract

Ketergantungan sektor maritim pada bahan bakar fosil telah berkontribusi signifikan terhadap peningkatan emisi karbon, pencemaran lingkungan laut, dan tingginya biaya operasional kapal. Tantangan ini menuntut inovasi energi alternatif yang ramah lingkungan dan berkelanjutan. Penelitian ini bertujuan merancang dan mengimplementasikan prototipe kapal wisata bertenaga surya sebagai sumber energi utama penggerak. Pendekatan penelitian yang digunakan adalah Research and Development (R&D) yang meliputi tahap analisis kebutuhan, perancangan, perakitan, pengujian, dan evaluasi kinerja. Hasil pengujian menunjukkan bahwa kapal berbobot 1,3 ton dapat beroperasi dengan kecepatan rata-rata 3,5–4 knot menggunakan enam panel surya berkapasitas 100 WP dan empat baterai 200 Ah, dengan waktu pengisian penuh sekitar 12 jam pada kondisi penyinaran optimal. Temuan ini mengindikasikan bahwa kapal bertenaga surya berpotensi menjadi alternatif transportasi laut yang efisien, ramah lingkungan, serta mendukung penerapan energi terbarukan di sektor maritim.   The maritime sector's reliance on fossil fuels has significantly contributed to increased carbon emissions, marine environmental pollution, and high vessel operational costs. These challenges necessitate the development of environmentally friendly and sustainable alternative energy solutions. This study aims to design and implement a solar-powered tourist boat prototype as the primary propulsion energy source. The research employed a Research and Development (R&D) approach, encompassing needs analysis, design, assembly, testing, and performance evaluation stages. The test results indicate that a 1.3-ton vessel can operate at an average speed of 3.5–4 knots using six 100 WP solar panels and four 200 Ah batteries, with a full charging time of approximately 12 hours under optimal sunlight conditions. These findings suggest that solar-powered boats have the potential to serve as an efficient and environmentally friendly alternative for maritime transportation while promoting the adoption of renewable energy in the maritime sector.
Komparasi Metode Peramalan Harga Daging Ayam Broiler Di Kabupaten Banyuwangi Menggunakan Jaringan Syaraf Tiruan Backpropagation dan Model Multiplicative Holt-Winters Hasanudin Slamet, Ahmad Haris; Ischak, Rabbani; Wulandari, Sekar Ayu; Brillyantina, Septine
Paradigma Agribisnis Vol 4 No 2 (2022): Paradigma Agribisnis
Publisher : lembaga penelitian universitas swadaya gunung jati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33603/jpa.v4i2.6788

Abstract

ABSTRAKHarga daging ayam broiler di Banyuwangi merepresentasikan data ekonomi yang memiliki fluktuasi musiman dengan variasi tidak konstan dan pola trend. Fluktuasi harga daging ayam broiler menjadi permasalahan dalam tingkat konsumsi daging ayam. Peramalan harga merupakan salah satu cara yang cara yang penting dalam menangani fluktuasi harga. Peneltian ini menggunakan metode jaringan syaraf tiruan backpropagation. Data yang digunakan pada penelitian ini adalah harga daging ayam broiler di Kabupaten Banyuwangi dalam kurun waktu 2014-2017. Hasil uji menggunakan metode jaringan syarat tiruan didapatkan nilai terbaik yaitu 12-10-1 (12 neuron input, 10 neuron hidden layer, 1 neuron output. Nilai n MAPE yang diperoleh sebesar 18,016 %. Selanjutnya, model Multiplicative Holt-Winters dengan tiga komponen parameter penghalusan, dimana komponen irregular-nya akan dihilangkan. Sehingga peramalan periode mendatang hanya dipengaruhi oleh konstanta level (  = 0,9989), komponen trend (  = 0,0056), dan musiman (  = 0,0008), pada periode ke-12 musiman sebelumnya. Akurasi peramalan menunjukkan bahwa model Multiplicative Holt-Winters dapat meminimalkan persentase kesalahan peramalan dengan Mean Absolute Percentage Error (MAPE) sebesar 12,63%, lebih baik dibandingkan Jaringan Syaraf Tiruan Backpropagation. Peramalan harga sangat penting dilakukan baik oleh industri peternakan maupun industri pengolah daging ayam. Peramalan harga yang tepat dapat dijadikan industri peternakan dan industri pengolah daging ayam untuk mengoptimalkan alokasi sumber daya sehingga dapat meningkatkan pendapatan. Kata Kunci: Backpropagation, Peramalan, Multiplicative Holt-Winters
Analyzing the Use of Artificial Intelligence for Optimizing Crewing Management Systems in Indonesian Shipping Companies: A Literature Review Andri Setiawan, Raden Novi; Bintari, Pramudyasari Nur; Ischak, Rabbani; Setiawan, Weli Agus; Octavitri, Yollanda
Journal Of Social Science (JoSS) Vol 4 No 12 (2025): Journal of Social Science
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/djtmp463

Abstract

The shipping industry relies heavily on efficient crewing management to ensure safe vessel operations and compliance with national and international regulations. In Indonesia, crewing management faces persistent challenges, including complex documentation procedures, manual data processing, high administrative workloads, and limited integration between human resource systems and operational platforms. With the rapid expansion of artificial intelligence (AI) technologies, maritime companies increasingly explore AI-based solutions to optimize decision-making, automate routine processes, and enhance overall crew management performance. This study conducts a systematic literature review to analyze the potential, limitations, and implementation models of AI within the context of crewing management systems (CMS). The result shows that AI significantly improves crew scheduling accuracy, reduces administrative workload by up to 40%, enhances regulatory compliance monitoring, and supports predictive analytics for crew performance and turnover. The study concludes that AI-enabled CMS could transform Indonesia’s shipping operations, although challenges remain in terms of digital readiness, data quality, cybersecurity, and regulatory frameworks. Recommendations are provided to support Indonesian shipping companies in adopting AI-driven crewing management solutions
Co-Authors Alvian Demaz Peramutya Amirullah -, Amirullah Andri Setiawan, Raden Novi Hasanudin Slamet, Ahmad Haris Hidayatuloh, Ade Taopik Nursyamsu, Nursyamsu Palembangan, Semuel Pramudyasari Nur Bintari, Pramudyasari Rahmat Santoso, Rahmat Rudi Harun Irwansyah Sekar Ayu Wulandari Septine Brillyantina Setiawan, Weli Agus Yollanda Octavitri