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Topik penelitian adalah pokok dari rencana riset terkait dengan pembicaraan dalam penulisan artikel ilmiah atau penelitian, oleh karena itu sebelum peneliti melakukan penelitian, penting untuk menentukan topik apa yang akan diangkat.

Pilihan Topik Penelitian

Ade Irawan, Ph.D., Gunawan Witjaksono, Ph.D.,IPM (UTP), M. Zulkifli UTP), Muhammad Yopan (UTP), Dr. Eng. Wahyu Kunto Wibowo (EE), and Ariana Yunita, M.I.T, MBA

Utilization of Advanced Wireless Communication on Decision Making Strategy to Improve Safety Performance and Productivity in Oil and Gas Industries.

Global oil demand is at an all-time high for industries, transportation, technology, and is forecasted to increase by more than a third by 2035. Approximate 95 million b/d of oil the world now consumes, up from 86 million b/d in 2008 and an 11% rise even amid the worst economic times since the 1930s. With this surge in energy demand, the oil and gas (O&G) industry is required to improve production efficiencies and strong safety culture, i.e. health, safety and the environment remain non-negotiable imperatives.

One offshore platform costs billions of dollars. Any small hazard and an improper decision result a huge monetary loss, human life, resources to a company. Hence, the safety behavior, human performance, and production aspects have been a top priority in the O&G industry. This industry has undertaken extensive actions to enhance process safety and human performance and strictly implement proper decision and emergency control measures. With significant oil price decline recently, O&G companies have responded by utilizing digital transformation technologies to gain better insights, drive operational efficiencies, production improvement and ensure survival.
01 January 2018
Rahmat Septian Wijanarko (EE) and Meredita Susanty

Smart Digital-Wallet Based Application for Self-Service Station Improvement

Pertamina provides self-service station in order to reduce number of employee and reduce customer queue time in a gas station. The self-service gasoline station has two types of payment method: gazcard and barcode-receipt. Gazcard is a smart card which can only be used for gasoline purchasing at Pertamina gas station. The other method, requires customer to buy/get a barcode receipt from the attendant. Both Gazcard and barcode must be scanned before at a fuel dispenser before customer refueling. Although barcode receipt method is not fully self-service, it can still reduce the number of attendant in a gasoline station.

Pre-paid method is considered impractical for customer who needs full tank refueling. On the other hand, Pertamina accept debit/credit card as a post-paid payment method. Although post-paid is more practical than pre-paid one, an attendant at each dispenser is still needed to make sure customer pays the correct amount of bill. This research proposes a novel payment method for self-service station by using digital-wallet, a smartphone based application, which overcome inflexibility payment method in the existing self-service station. Digital wallet provide flexibility, customer can choose pre-paid or post-paid. Both methods use barcode. In a pre-paid method, barcode displayed in smartphone screen determine the volume of purchased gasoline after digital wallet is charged while in a prepaid method it identify the customer data to charged their digital wallet after refueling.
01 January 2017
Muhamad Koyimatu, Ade Irawan, Ariana Yunita, dan Herminarto Nugroho (EE)

Deep Learning Based Computer Vision for Improving Safety in Oil and Gas Industry

The recent oil price collapse has triggered a wave of cost reduction in Oil and Gas (O&G) companies. As one of the most sensitive and dangerous industries, the infrastructure in O&G companies requires regular monitoring and maintenance to avoid accidents that can lead to environmental problems which result in increased operational costs. Digital technologies are recognized as adding value to O&G companies by helping not only reduce costs, but also increase workforce productivity. Modern O&G companies utilize digital technologies for obtaining information about ongoing operations to gain operational efficiencies, production improvement, and safety performance. As a result, modern rigs often have a number of video-based sensors actively monitoring the exploration and production process. However, most of the video-based monitoring activities have traditionally relied on manual methods as such increase the operational cost.

Computer vision (CV) technologies facilitate advanced video interpretation that allows achieving continuous, robust, and accurate assessment of many different phenomena through real-time and pre-existing video data. Recent advances of CV combined with deep learning (DLCV) can lead to significantly improved performance of monitoring process for improving safety and productivity performances. The main challenge is devising the technology while adhering to the constraints of operational cost and data processing latency.
01 January 2018
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