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All Journal KAPAL Jurnal Ilmu Pengetahuan dan Teknologi Kelautan Briliant: Jurnal Riset dan Konseptual Indonesian Journal of Energy Journal of Marine-Earth Science and Technology
Mohammad, Luthfansyah
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Education Energy

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The necessity of implementing AI for enhancing safety in the Indonesian passenger shipping fleet Rahadi, Shinta J.A.; Prasetyo, Dimas Fajar; Hakim, Muhammad Luqman; Sari, Dian Purnama; Virliani, Putri; Rahadi, Cakra W.K.; Rina, Rina; Yulfani, R. D.; Mohammad, Luthfansyah; Kurnianingtyas, Diva
Kapal: Jurnal Ilmu Pengetahuan dan Teknologi Kelautan Vol 21, No 1 (2024): February
Publisher : Department of Naval Architecture - Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/kapal.v21i1.58868

Abstract

The shipping industry, grappling with escalating challenges, increasingly adopts Artificial Intelligence (AI) to enhance efficiency, safety, and environmental impact. Experts endorse ship automation and AI implementation for safety, navigation, and operational efficiency in ferry networks. This paper underscores AIS technology's role in maritime safety and environmental protection, emphasizing AI's potential in navigation and knowledge gap bridging. Indonesia, with its numerous islands and significant population, faces complex challenges in ensuring safe maritime transportation. Collaborative efforts among the government, industry, and stakeholders are vital for enhancing safety standards across the archipelago. Despite regulations, Indonesia contends with a high ferry accident rate, prompting the need for preventive measures. The study reviews AI's application in preventing sea accidents, recognizing its contributions and potential effectiveness in maritime safety. Acknowledging challenges like data quality and cybersecurity, the paper emphasizes the necessity of AI development for passenger ship safety. It concludes by highlighting significant research efforts, endorsing AI's promising role in reshaping the industry for improved efficiency and safety. Further exploration of AI applications, particularly in passenger ship safety, is recommended to meet evolving challenges in the maritime sector.
Performance Enhancement of Solar Panels Using Adaptive Velocity-Particle Swarm Optimization (AVPSO) Algorithm for Charging Station as an Effort for Energy Security Mohammad, Luthfansyah; Asy’ari, Muhammad K.; Izdiharrudin, Mokhammad F.; Suyanto
Indonesian Journal of Energy Vol. 3 No. 2 (2020): Indonesian Journal of Energy
Publisher : Purnomo Yusgiantoro Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33116/ije.v3i2.91

Abstract

The growth of public awareness of the environment is directly proportional to the development of the use of electric cars. Electric cars operate by consuming electrical energy from battery storage, which must be recharged periodically at the charging station. Solar panels are one source of energy that is environmentally friendly and has the potential to be applied to charging stations. The use of solar panels causes the charging station to no longer depend on conventional electricity networks, which the majority of it still use fossil fuel power plants. Solar panels have a problem that is not optimal electrical power output so that it has the potential to affect the charging parameters of the battery charging station. Adaptive Velocity-Particle Swarm Optimization (AV-PSO) is an artificial intelligence type MPPT optimization algorithm that can solve the problem of solar panel power optimization. This study also uses the Coulomb Counting method as a battery capacity estimator. The results showed that the average sensor accuracy is more than 91% with a DC-DC SEPIC converter which has an efficiency of 69.54%. In general, the proposed charging station system has been proven capable to enhance the energy security by optimizing the output power of solar panels up to 22.30% more than using conventional systems.
DESIGN AND CONSTRUCTION OF A SAVONIUS TYPE L WIND TURBINE PROTOTYPE WITH OPEN VARIATIONS AS AN ELECTRIC ENERGY ALTERNATIVE FOR LIGHTING IN LIFT NET NORTH SEMARANG Naseem, Iqbal; Yusim, Adi Kurniawan; Windyandari, Aulia; Ridwan, Mohd; Mohammad, Luthfansyah
Journal of Marine-Earth Science and Technology Vol. 5 No. 2 (2024): September
Publisher : Marine & Earth Science and Technology Research Center, DRPM, ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27745449.v5i2.1805

Abstract

This study investigates wind speed, wind turbine design to be implemented on fixed lift net in the waters of North Semarang in fishing with the help of lights. The research was carried out by designing and making a prototype of a Savonius type L wind turbine with a blade diameter of 400 mm and a height of 400 mm which was carried out directly on the beach for 10 hours and tested with a blue light to produce fish catches on the fixed lift net. The results of the use of blue lights were obtained from seven types of catfish, anchovies, Rebon fish, Selar fish, Cucut fish, mullet and layur fish with a total catch of 125.16 kg. The results obtained from processing wind turbine data are that the generator power at a wind speed of 1.3 m/s is 0.896 W, the highest power at a speed of 4.9 m/s is 5.214 W and the total generator power for 10 hours is 389.9 W. The energy produced is sufficient to light a 30-W lamp for 12 hours of use which will later be stored in a 12V 38 Ah capacity battery because the battery capacity used is 35.2 Ah with a battery efficiency of 85%.
Evaluasi Hasil Kinerja Tekno-Ekonomi Pembangkit Listrik Tenaga Surya (PLTS) Pada Bangunan Perguruan Tinggi di Indonesia Mohammad, Luthfansyah; Istiqomah, Aulia; Tahier, Ahmad Ridlo Hanifudin; Syamputra, Dhani Nur Indra; Roodhiyah, Lisa’ Yihaa
BRILIANT: Jurnal Riset dan Konseptual Vol 8 No 2 (2023): Volume 8 Nomor 2, Mei 2023
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/briliant.v8i2.1360

Abstract

Dimulainya kegiatan sekolah normal dan universitas membuat sektor pendidikan mengalami peningkatan konsumsi listrik dibandingkan tahun-tahun sebelumnya sebelum merebaknya pandemi. Sayangnya, peningkatan konsumsi listrik berbanding lurus dengan peningkatan emisi yang besar. Oleh karena itu, diperlukan penggunaan teknologi energi terbarukan yang ramah lingkungan yang dapat langsung diterapkan di bidang pendidikan. Studi ini berfokus pada evaluasi kinerja sistem panel surya yang telah terpasang di Gedung Dekanat Universitas Diponegoro, Indonesia. Dua metode digabungkan dalam melakukan analisis; Simulasi perangkat lunak PVsyst Versi 7.0, dan penilaian langsung. Hasil asesmen lapangan menunjukkan bahwa sistem yang terpasang mampu menghasilkan energi sebesar 37.068 MWh per tahun dan hanya memiliki selisih sebesar 3.372 MWh saat disimulasikan. Terdapat kerugian sebesar 2,02% dari nilai produksi ideal yang disebabkan oleh beberapa faktor klimatologis dan teknis. Secara umum dengan target penghematan energi sebesar 16,6%, sistem yang dibangun berhasil mencapai 16,51%. Analisis kelayakan ekonomi menunjukkan bahwa nilai Levelized Cost of Electricity adalah Rp. 1.153,93 per kWh, nilai Payback Period 9,4 tahun, Net Present Value sekitar Rp. 364.331.588,4, dan Return of Investment sebesar 102,1%. Akhirnya, berdasarkan penilaian evaluasi, dapat diputuskan bahwa secara teknis sistem dapat bekerja dengan lancar sesuai target yang ditentukan, memiliki proyeksi ekonomi yang menguntungkan, dan memiliki potensi nilai investasi yang positif
RANCANG BANGUN SISTEM AUTOMATED GUIDED VEHICLE (AGV) MENGGUNAKAN AGV LINE FOLLOWER BERBASIS FUZZY LOGIC CONTROL SEBAGAI PENENTU RUTE DAN BERAT BARANG Mohammad, Luthfansyah; Aulia Istiqomah; Ardani, Hanif Satrya
BRILIANT: Jurnal Riset dan Konseptual Vol 10 No 4 (2025): Volume 10 Nomor 4, November 2025
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/briliant.v10i4.2221

Abstract

The Automated Guided Vehicle (AGV) is a robotic innovation designed to assist in the process of delivering goods in the logistics sector of a factory. The stability of an AGV's movement has a direct impact on the safety of the goods it transports. This research aims to overcome this problem by designing and implementing an AGV mapping control system using a Fuzzy Inference System. The Load cell sensor is used as system input to measure the weight of the load carried by the AGV. The data from this sensor is then processed by the Fuzzy Inference System to produce information about the load value carried by the AGV. The research results showed that the AGV could determine the destination post when goods were placed in the load cell sensor. When the AGV was running, it went to the destination post according to the weight of the goods, and an accuracy of 100% and an error level of 5% were obtained from testing the load cell sensor.
Co-Authors Ardani, Hanif Satrya Asy’ari, Muhammad K. Aulia Istiqomah Aulia Windyandari Dian Purnamasari Istiqomah, Aulia Izdiharrudin, Mokhammad F. Kurnianingtyas, Diva Mohd Ridwan Muhammad Luqman Hakim, Muhammad Luqman Naseem, Iqbal Prasetyo, Dimas Fajar Rahadi, Cakra W.K. Rahadi, Shinta J.A. Rina Rina Roodhiyah, Lisa’ Yihaa Suyanto Syamputra, Dhani Nur Indra Tahier, Ahmad Ridlo Hanifudin Virliani, Putri Yulfani, R. D. Yusim, Adi Kurniawan