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All Journal Jurnal Teknologi Industri Pertanian JITMI (Jurnal Ilmiah Teknik dan Manajemen Industri) MEANS (Media Informasi Analisa dan Sistem) International Journal of Engineering, Science and Information Technology
Putranto, Kartiko Eko
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Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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The Role of Artificial Intelligence in Improving the Efficiency of the Company's Supply Chain Husein, Muh; Rajagukguk, Jenni Ria; Putranto, Kartiko Eko
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.596

Abstract

The development of technology, especially in the era of Industry 4.0, has significantly impacted various sectors, including supply chain management. Artificial Intelligence (AI), one of the leading technologies in Industry 4.0, has excellent potential to improve the efficiency and effectiveness of the supply chain. This study aims to identify the relationship between AI and the concept of supply chain management and analyze the practice of using AI to improve supply chain efficiency at PT. Pelita Media Nusantara. Using a descriptive-analytical method, this study examines various relevant literature and data. The results of the study indicate that the application of AI at PT. Pelita Media Nusantara has increased the supply chain's visibility, accuracy, and responsiveness. Implementing big data analytics, IoT sensors, and AI-based predictive systems allows companies to optimize procurement, production, and distribution processes. This case study also reveals that complex technology integration and the need for skilled human resources are the main challenges in implementing AI. This study provides important insights for academics and practitioners in developing more effective and efficient AI-based supply chain management strategies.
Energy Efficiency Analysis of LED, CFL, and Incandescent Bulbs with Smart Energy Management (SEM) Technology Supriyono, Lawrence Adi; Fitrianto, Yuli; Setiawan, Dwi; Putranto, Kartiko Eko; Aldila, Amalia Shifa
MEANS (Media Informasi Analisa dan Sistem) Volume 9 Nomor 2
Publisher : LPPM UNIKA Santo Thomas Medan

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Abstract

This study focuses on the comparative energy efficiency analysis of LED, CFL, and incandescent bulbs to assess the potential savings offered by LED technology. With growing global concerns about energy consumption and carbon reduction, it is essential to eval_uate lighting options based on energy efficiency. Incandescent bulbs, though widely used, are inefficient as they emit more energy as heat than light. Compact Fluorescent Lamps (CFLs) are more energy-efficient but have a shorter lifespan compared to LEDs, making them less environmentally friendly. In this research, the real-time power consumption of each bulb type is measured using ACS712 and ZMPT101B sensors, connected to an Arduino Uno R3 microcontroller. The ACS712 sensor is used to monitor electrical current, while the ZMPT101B sensor detects voltage, enabling accurate energy consumption calculations. All bulbs are tested under identical conditions, providing clear, comparative data on their energy efficiencies. The analysis demonstrates that LED bulbs not only offer lower energy consumption but also result in long-term environmental and economic benefits. These findings suggest significant savings in electricity costs, supporting the shift towards energy-efficient LED lighting.
The Impact of Aurora Supercomputer in Scientific Area and the Development Analysis Okafor, Ngozi Lilian; Gunawan, Stella Putri; Zhafirah, Rafdah; Sujatmiko, Devlin Wen; Aldila, Amalia Shifa; Scantya, Miranti Andhita; Supriyono, Lawrence Adi; Putranto, Kartiko Eko
MEANS (Media Informasi Analisa dan Sistem) Volume 10 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

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Abstract

Supercomputers are crucial in solving complex scientific and industrial computing due to its tremendous computational power in enabling large- scale simulations, scientific research, and advancement in various scientific fields. This study is conducted on Aurora supercomputer, a powerful exa-scale supercomputer designed for intricate computing tasks, such as climate modeling, intense simulations, and AI and machine learning. By making use of the literature review approach, we analyze the capabilities and impact of Aurora on the scientific environment. Our research suggests that Aurora is capable of significantly enhancing performance on processing data, surpassing supercomputers such as Frontier and Fugaku. Furthermore, we discuss Aurora's impact on driving groundbreaking research across multiple scientific domains and its real-world applications such as drug discovery driven by AI and machine learning. The result highlights that Aurora marked a remarkable milestone in revolutionizing computational research and further research can show the true power of the Aurora supercomputer
Optimalisasi Pola Operasi Tanpa Penambahan Alat Untuk Meningkatkan Produksi Pada Industri Kertas Ependi, Ujang Rahmat; Putranto, Kartiko Eko
JITMI (Jurnal Ilmiah Teknik dan Manajemen Industri) Vol. 7 No. 1 (2024): JITMI
Publisher : Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jitmi.v7i1.y2024.p66-80

Abstract

From the data analyzed, it is known that the problems being faced by paper production companies, especially PT. XYZ is the amount of production produced during the paper production process in 2019 which has made the company suffer a total loss of 4,876 tons. This thesis aims, firstly to find out how to measure productivity in the latest paper industry, second what are the ways to optimize productivity, third what are the causes of productivity in the paper industry is not optimal, fourth how to determine how to optimize productivity most efficiently.To achieve these objectives, this thesis uses the OEE (Overall Equipment Effectiveness) method in increasing the cutsize sheeter. The cutsize sheeter was chosen in this study because the cutsize sheeter has a lower yield than the predetermined target.The results of the calculation of OEE value on the cutsize sheeter in 365 days are 31.29%) <85% (world standard OEE values). Two variables that cause low OEE values ​​are time efficiency and performance efficiency.The results of the calculation of the OEE Big Losses Value on the cut size sheeter are Reduce Speed ​​Loss of 45.45%, Breakdown Loss of 21.54%. Furthermore, technical analysis with the company efficiency team, using a fishbone diagram to identify the causes of the problem (why), identify the causes of the problem (how). The next step is to apply the Plan - do - check - action method to find the root of the problem and make quality improvements. Result, this thesis suggests 1). Performance, especially low speed, can be overcome by working with the HRD team in conducting training, 2). The problem of high breakdown can be overcome by improving communication between the dept. engineering, 3). For base papers that do not fit the deckle, coordinate with the Dept. Finishing & PPIC
A TERTIARY PERSPECTIVE OF THE SUGARCANE-BASED AGRO-INDUSTRY SUSTAINABILITY ANALYSIS Rohayati; Marimin; Hardjomidjojo, Hartrisari; Fahma, Farah; Putranto, Kartiko Eko
Jurnal Teknologi Industri Pertanian Vol. 34 No. 3 (2024): Jurnal Teknologi Industri Pertanian
Publisher : Department of Agroindustrial Technology, Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24961/j.tek.ind.pert.2024.34.3.286

Abstract

Sustainability has given significant consideration to the development of the agricultural sector, particularly the sugarcane-based agro-industry. Extensive research on sustainability analysis has been explored across different fields, including the sugarcane-based agro-industry. A wide range of primary studies has focused on diverse aspects of sustainability. Various secondary studies, such as systematic reviews and mapping studies, have also been documented. Nonetheless, performing tertiary research in this critical domain remains essential to systematically identify, evaluate, and categorize these secondary studies. This tertiary study utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework for a systematic literature review, focusing on sustainability analysis within the agricultural sector, particularly the sugarcane-based agro-industry. A search protocol was applied for article identification, followed by articles’ screening and selection. Content analysis was conducted using Biblioshiny in RStudio, followed by a descriptive analysis. A total of 27 secondary studies were reviewed to gain deeper insights into the evolution of the research topic productions, as well as key trends. This study also acknowledges its limitations and provides key recommendations for future research in the field, which were considered in the results. Keywords: Biblioshiny, sugarcane-based agro-industry, sustainability analysis, systematic review, tertiary study
Co-Authors Amalia Shifa Aldila Dwi Setiawan Ependi, Ujang Rahmat FARAH FAHMA Gunawan, Stella Putri Hartrisari Hardjomidjojo Husein, Muh Lawrence Adi Supriyono Marimin , Miranti Andhita Scantya Okafor, Ngozi Lilian Rajagukguk, Jenni Ria Rohayati Sujatmiko, Devlin Wen Yuli Fitrianto Zhafirah, Rafdah