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Proceeding International Applied Business and Engineering Conference
Published by ABEC: Konsorsium Politeknik Se-Sumatra
ISSN : -     EISSN : 27984664     DOI : -
Core Subject : Religion, Economy, Humanities, Science, Education, Agriculture, Social, Engineering,
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other
Proceedings of the Sumatra Polytechnic conference, scope: electrical engineering, mechanical engineering, computer engineering, civil engineering, social sciences, business administration, accounting, English, agriculture, tourism
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 79 Documents
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Aggregator Backend API With KrakenD Fikri Muhaffizh Imani
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

Implementation of API Gateway to secure and expose backend API as an endpoint that can be accessed by the client is ideal step in developing an integrated system. The client makes a request through an endpoint exposed by API Gateway to get the data needed to display a web page, but the server load will increase if the page requires data from several endpoints that require multiple requests to be made to the server. Vertical scaling can be applied to increase server resources in order to handle these requests, but this solution costs a lot of money. This research was conducted to overcome the problem of multiple requests by clients without having to do vertical scaling by implementing KrakenD as an aggregator backend API to combine several backend API into one and expose the combined results back into a new endpoint. Based on the results of the study, aggregation on several API backends was able to reduce 75% of the request load to the server. This solution can become novel consideration in building an information system that requires data from several different backend API.
Fruit Recognition and Weight Scale Estimation Based on Visual Sensing Budi Sugandi; Ria Wahyu; Sindi Apriliana; Fitri Ramadani Putri
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

This paper aims to develop a system to recognize fruit and estimate its weight scale based on visual sensing. The images of fruit are captured by camera and processed by image processing to be recognized and estimated their weight. The fruit recognition is performed based on average of RGB histogram. The RGB histogram of each fruit is calculated and saved as training data. To evaluate the recognition process, the testing data is compared with training data. The weight scale estmation is performed by calculating the height dan width of the detected fruit image. The regression equation is used to determine the weight of the fruit. The experiment was performed to 8 types of fuit with 10 samples data of each. The experiment results show the effectivenes of the algorithm to recognize and estimate the weight of fuit with average error 9.38 % of recognition and 4.85% of weight estimation.
Student Calling Machine When After School by Whatsapp Text Message Syaiful Amri; Syahrizal; Khairudin Syah; Azizul
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

Crowds still have the potential to occur during the implementation of 100 percent face-to-face learning. School residents, especially students, still find it difficult to keep their distance from each other and that happens especially when it's time to go home from school. To overcome this condition, schools are moving quickly to find solutions. For example, the education unit made an alternative to prevent crowds. Namely providing a special waiting area for students, chairs lined up in the school hallway. The children sat while waiting for their parents to come pick them up. As soon as the parents arrive, the student is called over the loudspeaker, and so on. However, this method is not effective enough to reduce the crowd. Because at the time of calling the students who were picked up, the officer (teacher picket) was overwhelmed to recognize the parents or guardians of the students who were picking up the call by loudspeaker, due to the large number of students there could also be a change in the person who picked up the previous day.
Simulation of Batang Agam River Capabilities as Effect of LandUse Changes Dalrino; Hartati; Suhendrik Hanwar; Ilham Eka Putra
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

Batang Agam River is one of the rivers in West Sumatra Province that crosses Bukittinggi City, Agam Regency, Payakumbuh City and Limapuluh Kota Regency. The river is ± 60 Kilometers length with headwaters in Bukittinggi city and empties into Batang Sinamar in Limapuluh Kota Regency. With growth development of Bukit Tinggi, so that existing lands such as rice fields and other fields have changed functions into built-up land such as housing, offices, trade and so on. This resulted an increasement of surface runoff coefficient (coefficient C) and flow rate, which resulted in frequent flooding of Batang agam. These will induced flood, for example on 10 December 2018 flood which inundating SDN 18 Koto Tangah in Jorong Uba and 9 February 2020 flood which inundated 6 Hectare of rice fields in Kamang Hilia. To find out the magnitude of changes in land use and flood discharge that occurred in the Batang Agam watershed, a comparison of land use in 2011 with 2019 and flood discharge that occurred in 2011 with 2019. After calculating the results of the flood discharge calculation, the flood discharge was simulated using HEC-RAS software with a 5-year return period to get the overflowing water level and the area of the puddle. From the calculation results obtained an increase in the runoff coefficient value from 0.35 to 0.467, this resulted in a significant increase in flood discharge in each return period and the modeling carried out obtained the results of the maximum flood height reaching 3.13 m from the riverbed, this height is close to the flood height observed in the field, which is as high as 3.03 m.
Design of Tartibtar System In Pmmk Unit Department of Maritime Nur Rahmani; Zulyani; Handro Okta Prianus
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

The cadets of the Maritime Department of the State Polytechnic of Bengkalis as prospective shipping professional officers who are expected to have personality competencies that need to have good physical and mental conditions, so that all cadets are obliged to obey and comply the rules of maritime cadets. Currently the recording of cadet indiscipline points is still done manually by recording cadets' violation points and monitoring cadet data note in the violation book, therefore supervisors and PMMK members are often confused in finding cadets' personal and historical data, in addition to personal data reports and activity reports. cadets that should besubmitted to Academic advisors andcadets' families are often reported late because it takes a long time. To assist the performance of the cadet moral and discipline building unit in handling problematic students, therefore we need an application that functions as an information system and decision support system that aims to facilitate the performance of PMMK in order to document data, monitor, and provide appropriate further action. The purpose of this research is to design a computerized system in the Tatibtar application for checking application that can accommodate information and present quickly, precisely, and accurately about the state of the cadet point record. This application is implemented properly and correctly and is expected to minimize the human error factor. Make it easy to control input and output data in presenting information about the credit status of cadet points so that it can be done quickly and can be accessed by cadets, parents, and campus parties in the maritime department. The application is a decision support system can assist related parties in the results of the implementation of the task of supervision and enforcement of student discipline quickly and precisely.
Early Detection and Tracking of Distant Incoming Traffic using Improved Detection on Road Vanishing Point Reference for Adaptive Traffic Light Signaling Yoanda Alim Syahbana; Yokota Yasunari
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

Real-time monitoring is essential and influences the decision-making process of adaptive traffic light systems. During temporary road closures, only one side of the lane can be accessed, increasing the need to recognize and track oncoming vehicles. Therefore, it is crucial to detect oncoming vehicles that are far away as early as possible, as waiting for an oncoming vehicle near a traffic light may delay the signal, leading to sudden braking or an accident. The purpose of this study was to improve traffic detection and tracking, even when the traffic is still far from the traffic lights. Vanishing point as detection reference is estimated, and Region of Interest (RoI) is calculated. An evaluation is performed based on how quickly the proposed method detects oncoming traffic compared to the R-CNN method. The results show that the proposed method requires an average of 17.75 frames to detect the target vehicle, while R-CNN requires an average of 63.36 frames to detect the target vehicle. The results show that the accuracy of the proposed method depends on the number of pixel orientations when estimating the vanishing point and how accurately the RoI is defined. Therefore, the proposed method reliably supports the safety and reliability of adaptive traffic light systems.
Electric vehicle power monitoring system based on IoT sensing architecture Jia-Syuan Lin; Zi-Fang Tsai; Zhi-Hao Wang; Hendrick
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

At present, most of the vehicles in life are mainly based on gasoline and diesel, and with the gradual advancement of vehicle technology, but also accelerating global warming, countries have launched a variety of green energy to reduce the harm to the earth. Many vehicles have been developed into hybrid vehicles, and a large number of pure electric vehicles have been launched in recent years. On the other hand, many countries have begun to plan carbon footprint and carbon allowance management, and the emission of greenhouse gases or the use of green energy will be more regulated in the future. Therefore, this research will take the electric stacker as the test target, measure the values of current and voltage, input the measured values into the program to calculate the carbon emissions produced during operation, and obtain the carbon emissions emitted by driving electric vehicles that are significantly smaller than the carbon emissions emitted by driving gasoline and diesel vehicles.
Driving Physiological State Monitoring Based on IoT Sensing Architecture Yi-Ching Kuo; Yu-lian Yu; Zhi-Hao Wang; Hendrick
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

In clinical practice, alcoholic beverages will have imaging effects on the autonomic nervous system. Common reactions of the human body after absorbing alcohol include unsteady walking, rapid heartbeat, and reddening of the face. In this case, humans are usually unable to fully rely on self-consciousness to manipulate the body, and consciousness tends to become blurred. In recent years, the incidents of drinking and driving have emerged in an endless stream. Although there are laws and regulations, they cannot effectively prevent and control drunk driving. Therefore, this study intends to develop an alcohol lock that can monitor the physiological state of driving. The architecture proposed in this study uses the pulse oximeter to obtain the PPG signal and then analyzes the autonomic nervous system and uses the MQ-3 alcohol sensor to detect the air alcohol content in the cockpit. The two signals are sensed by ESP32 and sent to the base station outside the car by LoRa through the IoT architecture. Finally, the driving physiological information will be sent to the server for centralized display
A comparison between Super Vector Regression, Random Forest Regressor, LSTM, and GRU in Forecasting Bitcoin Price Rifando Panggabean; Yohana Dewi Lulu Widyasari
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

High bitcoin user volume results in high market volatility, and indicators commonly used in stock and forex transactions have low accuracy in handling bitcoin's highly volatile market. The present study aims to find out the most optimal machine learning algorithm for Bitcoin transactions by examining four algorithms: Super vector regression(SVR),Random Forest Regressor(RF),Long short-term memory(LSTM), and Gated Recurrent Unit (GRU), examined using four tests, namely Root Mean Square Error (RMSE), Mean Square Error (MSE) , Mean Absolute Error (MAE) and R-Squared(R2). The test was performed using Bitcoin data between 2014 and 2022. The test result showed that LSTM+GRU algorithm exhibited the highest accuracy, indicated by a R-squared of 94%.

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