Fuzzy-Based Screening System for Determination of Enhanced Oil Recovery (EOR) Method in Reservoir

The petroleum industry is developing technology to increase oil recovery in reservoirs. One of the technologies used is Enhanced Oil Recovery (EOR). Selecting an EOR method for a specific reservoir condition is one of the most challenging tasks for a reservoir engineer. This study tries to build a fuzzy logic-based screening system to determine the EOR method. It created the system intending to be able to assist in selecting and determining the appropriate EOR method used in the field. There are nine input criteria used to screen the EOR criteria, namely: API Gravity, Oil Saturation, Formation Type, Net Thickness, Viscosity, Permeability, Temperature, Porosity, Depth criteria. The output criteria generated from the calculation of the EOR screening criteria are 14 outputs, namely: CO2 MF Miscible Flooding, CO2 IMMF Immiscible Flooding, HC MF Miscible Flooding, HC IMMF Immiscible Flooding, N2 MF Miscible Flooding, N2 IMMF Immiscible Flooding, WAG MF Miscible Flooding , HC+WAG IMMF Immiscible Flooding, Polymer, ASP, Combustion, Steam, Hot Water, Microbial. In this system, 512 rules are generated to produce 14 different outputs of the EOR method, with Mamdani's Fuzzy Inference reasoning. This fuzzy-based screening system has an accuracy rate of 80.95%, so this system is suitable to be used to assist reservoir engineers in determining the appropriate EOR method to be used according to the conditions in the reservoir. The sensitivity level of the system only reaches 53.1%, while the specificity level reaches 94%.

Analysis of Information Technology (IT) Goods Sales Patterns Using the FP-Growth Algorithm

Determination of sales patterns is very important in marketing. Sales pattern serves to conduct an effective analysis in improving marketing. Sales analysis aims to explore new knowledge that can help design effective strategies by utilizing sales transaction data. This study processes sales data for 12 transaction days containing 47 items using the Fp-Growth algorithm. The results of this study are items with a minimum value of support > 0.10 and confidence 0.60 and will be compared with testing data using RapidMiner to test whether the results are valid so that the test results can help in designing sales strategies.

Multiple Linear Regression and Deep Learning in Body Temperature Detection and Mask Detection

In this new normal era, many activities began to operate again, such as offices, malls, etc. This creates a potential mass crowd. The public must follow health protocols as recommended by the government, including wearing masks and checking the temperature to anticipate the spread of the coronavirus. This study tested a tool that included image processing and artificial intelligence to help implement health protocols as recommended by the government. This tool connects Raspberry PI, Thermal Camera (amg8833), Pi Camera, an ultrasonic sensor with Multiple Linear Regression and Deep Learning algorithms. The purpose of this tool is to detect body temperature and detect the use of masks. The system will check on the pi camera frame whether the person is wearing a mask or not. The system is trained using the Deep Learning method to detect the use of masks. The system will check the temperature of the human body and the distance between humans and the tool. Temperature and distance data are entered in multiple linear regression formulas to get more accurate results. The processed results of the system will be displayed on the monitor screen if detected using a mask and the normal temperature will be green and if it is not detected it will be red and give a warning sound. The data is sent to the server and displayed via the web. We found that this tool succeeded in detecting body temperature within a distance of 1 to 3 meters with an accuracy of 99.49%, detecting people using masks with an accuracy of 94.71%, and detecting people not wearing masks with an accuracy of 97.7%.

New Student Drug Tests at College Using Principal Component Analysis Method

Drugs are substances or illegal drugs that can endanger human life. Someone who consumes it in an inappropriate way will become dependent and even result in death. The physical characteristics of people who use drugs vary, but the more obvious characteristics are on the faces of drug users such as red eyes, stiff facial muscles, dark spots, pupils susceptible to light, sunken face shape, and dullness. The lack of physical characteristics of drug users due to similarities with other diseases makes it difficult for people to recognize them initially. However, for users whose face data has been tracked by the National Narcotics Agency, the facial data is stored in the dataset. This research was conducted with the aim of building a system that can detect and recognize prospective students whether they have ever been included in drug users recorded in the National Narcotics Agency dataset or not as one of the requirements for new student admissions to universities. The system built using the Principal Component Analysis method to process and extract images of the physical characteristics of drug users through the facial image data of drug users stored in the dataset. If the detected face has similarities with the characteristics in the dataset, it is necessary to suspect that the detected face is a drug user. The results of this study are the system is able to detect the faces of drug users using the Principal Component Analysis method with an accuracy of 90% and it is hoped that with this research the system can be one solution in helping universities as an identification effort to minimize drug use so that it can be an additional identification tool which strengthens someone detected using drugs.

Cloud-Based NAS (Network Attached Storage) Analysis as an Infrastructure as A Service (IAAS) Using Open Source NAS4FREE and Owncloud

At this time, computer systems and networks are an essential part of human life. The number can see this of computer users in the office or on campus, and at school. This need has reached a relatively large number. To access data, many computer users in the network continue to increase, impacting the selection of servers, and large data storage media is necessary. Currently, the storage media that is often used to store data still uses physical media such as hard disks, flash disks that are virus-prone and easy to lose. Another problem also arises when physical storage has a relatively high price compared to cloud storage that can be accessed anywhere when needed.

Flood Vulnerability Analysis using Weighted Overlay

Several areas in Bengkulu City are affected by floods every year; one of the worst is the Sungai Serut sub-district. The existence of a river that stretches along Sungai Serut also plays a role in floods over the Bengkulu area. Furthermore, this study to see the priority area over this district is still limited. Mapping flood areas is one way to provide information, especially for decision-makers in flood control using geographic information systems. Our research aims to map flood vulnerability areas based on land height, slope, and river buffer by weighting these criteria. This thematic map is the result of overlaying several maps according to the flood vulnerability criteria. The results of this study indicate that Sungai Serut is an area with "Very Vulnerable" and "Vulnerable" levels of flood vulnerability. The story of flood vulnerability is dominated by gently sloping contours, with land elevation levels mostly below 20 m above sea level. In addition, the thing that exacerbates the potential for flood vulnerability is the existence of the river that runs along the Sungai Serut sub-district.

Implementation of Agglomerative Hierarchical Clustering Based on The Classification of Food Ingredients Content of Nutritional Substances

Health is something very precious. Maintaining health can be done in many ways, one of them by keeping your diet. The correct diet will keep your immune system so that it can avoid various diseases. The proper diet will also put the body in a balanced nutrition state, which all need to be nourished. Nutrient requirements include calories, protein, fat, carbohydrates, calcium, phosphorus, iron, vitamin A, vitamin B, and vitamin C with a mass of 100 grams each. To facilitate the search for nutrients needed, then build a system that can categorize food based on its nutritional status and calculate the average value of nutrients in agglomerative hierarchical clustering using average linkage. Calculation of intermediate linkage methods produces data that has some similarities to the data sought nutrients that can be seen from its index, so precise data are in each group.

Optimization of Educational Mobile Game Design 'Ayo Wisata ke Riau' based on User's Perspective

Educational Mobile Game ‘Ayo Wisata ke Riau’ is a mobile-based educational game application that was developed in 2017 on the Android platform. The quality requirements used in this game development have been adjusted for the available Educational Mobile Games. Even though it went well, there were many complaints from users during the direct implementation survey. This becomes material for re-evaluation, whether the game is ready to be disseminated to the public. Based on this occurence, a gap analysis was carried out to see the feasibility and the need for improvements to the game application that had been built. Based on the results of the gap analysis that has been carried out, it is indicated that there is a need for significant improvements in the areas of performance and user satisfaction. So that in this study, a design reengineering was carried out that was focused on improving the two things that were considered crucial, so that the results of the design and implementation that had been improved could provide better performance and user satisfaction scores than previous developments.

High Availability Server Using Raspberry Pi 4 Cluster and Docker Swarm

In the Industrial 4.0 era, almost all activities and transactions are carried out via the internet, which basically uses web technology. For this reason, it is absolutely necessary to have a high-performance web server infrastructure capable of serving all the activities and transactions required by users without any constraints. This research aims to design a high-performance (high availability) web server infrastructure with low cost (low cost) and energy efficiency. low power) using Cluster Computing technology on the Raspberry Pi Single Board Computing and Docker Container technology. The cluster system is built using five raspberry Pi type 4B modules as cluster nodes, and the Web server system is built using docker container virtualization technology. Meanwhile, cluster management uses Docker Swarm technology. Performance testing (Quality of Service) of the cluster system is done by simulating a number of loads (requests) and measuring the response of the system based on the parameters of Throughput and Delay (latency). The test results show that the Raspberry Pi Cluster system using Docker Swarm can be used to build a High Availability Server system that is able to handle very high requests that reach Throughput = 161,812,298 requests / sec with an Error rate = 0%.

Embedded Control System of DC Motor Using Microcontroller Arduino and PID Algorithm

The development of technology has a positive effect on the trade sector, creating smartphones that can be utilized in all activities combined with the internet network. Activity that is currently growing is a mobile trader in the city of Pekanbaru. This development caused much competition, for example, in the Pekanbaru city area, especially in Sialangmunggu village. Traders around is difficult to find consumers because consumers do not have precise location and time information. Therefore, researchers aim to design and build applications by utilizing the functions of google maps and GPS (Global Positioning System) where the Algorithm to be applied is the A* algorithm whose function is to find the nearest location between buyers to mobile merchants, to accommodate data from mobile merchants where buyers can know the nearest position of the traveling merchant. Process analysis will be divided into running analysis that discusses the workings of the process of mobile traders and buyers in the field. Then the proposed system analysis of the analysis will be made by the author to maximize the process on the current analysis. By making analysis and design, the author will know the needs needed in the creation of the system. The result of using method A* is applied to displaying the merchant's route with the user, and the result can provide the fastest route to get to the trader. The use of method A* is also done to find the trader whose location is closest to the user's location, and the result can display the nearest trader.