Number Of Vehicles In Indonesia Research Articles

Implementation of Traffic Monitoring Technology Using Smart Surveillance in Intelligent Transportation System

Currently transportation is very attached to human life, almost every family and even every adult human being has a vehicle as a means of transportation. Based on this, a conclusion can be drawn that population growth will trigger an increase in the number of vehicles in Indonesia. The implementation of Traffic Monitoring Using Smart Surveillance in the Intelligent Transportation System is research on information and communication technology in the transportation system in order to increase mobility, reduce congestion resulting from the buildup of vehicles in one lane, and be taken into consideration by road users before crossing a road section. This system uses the Background Subtraction method, and object detection. This system was created by utilizing OpenCV and Python programming language. This research obtained an accuracy of 93.1% on camera A and 93.5% on camera B in calculating passing vehicles in the test using simulations monitored via cameras in real time.

Optimizing Driving Completeness Prediction Models: A Comparative Study of YOLOv7 and Naïve Bayes at Institut Teknologi Sumatera

The number of vehicles in Indonesia is increasing every year. The number of motor vehicle accidents in 2022 will be more than 100,000. It is hoped that several regulations regarding motorbike rider equipment will increase awareness of rider safety. By utilizing image recognition technology developed with artificial intelligence, it is possible to create digital image processing models or images that are fast and accurate for detecting driving equipment. The object detection model developed uses a dataset in the form of images of motorists who want to enter ITERA through the main gate. The object detection model will also be integrated with the classification model to create a program that can detect motorbike rider equipment, such as mirrors, helmets, not wearing a helmet, shoes, not wearing shoes, open clothes, and closed clothes. After detecting motorized rider equipment in the classification area, the results will be transferred to a classification model to determine the level of safety for motorized riders, either insufficient or sufficient safety. The test results show that the optimal object detection model was found at an epoch value of 70 with a batch-size of 16, producing a mAP value of 0.8914. The optimal classification model uses the naive Bayes method which has been trained with a dataset of 62 data and achieves an accuracy of 94%.

Sistem Tracking dan Counting Kendaraan Berbasis YOLO untuk Pemetaan Slot Parkir Kendaraan

The growth in the number of vehicles in Indonesia has always increased from year to year. Based on data from the Central Statistics Agency, it shows that from 2018 to 2020 there has been an increase of around 5.62% (2018-2019) and 1.89% (2019-2020). This condition causes the condition of parking lots in every public facility to always be a concern considering the lack of availability of parking spaces accompanied by an increase in the number of vehicles. This causes, in some places, especially for areas such as malls, the parking area is always filled with vehicles. Finally, it caused several visitors to experience difficulties in parking the vehicle. In this study, developing an automatic parking system by detecting, tracking and counting vehicles in real time. The proposed detection system is based on YOLO and to carry out vehicle calculations using calculations by checking vehicles that have crossed a predetermined center line. The system performance results show that the detection results show performance with an accuracy percentage of 85% and the results of counting or object calculations with an accuracy of 77.55%.

Analysis of MyPertamina Application User Satisfaction Using End User Computing Satisfaction Method

The MyPertamina application is an application that functions as a cashless payment system, where this application can make it easier for users to make BBM payments. This study aims to determine the level of user satisfaction and the factors that influence their satisfaction with the MyPertamina application using the End User Computing Satisfaction (EUCS) approach. Since 2017 this application has been running, until now it is known that the number of existing MyPertamina users is still relatively low and far from the maximum potential of the vehicle population in Indonesia. Where MyPertamina users currently are approximately 5 million users, while the number of vehicles in Indonesia itself is currently 144 million units of vehicles. This causes the target user has not been achieved in accordance with what is expected by PT. Pertamina. It can be concluded that of the 5 hypotheses tested, 1 of them was rejected. So the factors that canaffect MyPertamina user satisfaction in terms of Content, Accuracy, Ease of Use, and Timeliness. Meanwhile, the format variable has no effect on MyPertamina user satisfaction.

Vehicle Accident Detection Monitoring System with Web Server and Telegram

Every year the number of vehicles in Indonesia is increasing; this is also directly proportional to the accidents that occur. With the increasing number of victims of vehicle accidents, serious handling is needed. The average number of accident victims who die in Indonesia is three people every hour due to road accidents. Therefore, serious and fast post-accident handling is needed to reduce the number of fatalities due to accidents. The tool's purpose is to maximize post-accident handling, so research is carried out to make an internet-based vehicle accident information tool. The tool that is made can detect the accident's location to speed up post-accident handling using the internet with the latest location information sent and photos of the driver's last condition after the accident. The research method used in this research is Research and Development (R&D) in designing internet-based vehicle accident information tools as a communication medium for sending data, telegram, social media applications, and web servers are used as vehicle monitoring simulations. The accident information system is designed to use a vibration sensor as a trigger and an accelerometer sensor to detect the degree of vehicle tilt. Tests were carried out on tools made and applied directly to vehicles by changing the slope of the vehicle as an accident simulation. The information tool can send the location and photos of the driver's current condition after the accident simulation is detected to telegram and the web server.

Reformulasi Strategi Pemasaran Bengkel Otomotif Mengunakan Metode SWOT Dan QSPM

The rised in number of four-wheeled vehicles in Indonesia has a positive impact on elevating business opportunities for otomotive repair services. This type of business is reside in all over region with service level vary from conventional services to advance services. Hari Jaya Teknik is a medium-sized service enterprise which focus on otomotive repairements in Gresik city. The business is experiencing with decreasing customers’ demand caused by conventional business promotion techniques and a number of business competition around bussiness location. This study aims to reformulate a marketing strategy to maintain the existence of a business that has been built for more than twenty years. SWOT and QSPM are the approaches used in this study. The research method begins by identifying internal and external factors obtained from six expert respondents, followed by the calculation of the SWOT and QSPM matrix. The results of this study found eight factors as primary consideration in order to redevelop marketing strategy. The highest factor namely strategy to both maintain and enhance the quality of service. These factors followed by calculating reasonable service costs in order to maintainbussiness reputation as well as customer loyalty. The reformulation of the eight strategies is also expected to be able to bring in new customers in the workshop in order to sustaining bussiness existence.

The Correlation of Subjective Fatigue, Negligence, Knowledge of Safety Riding and Length of Work on Traffic Accidents of Online Motorcycle Taxis in Sidoarjo

Introduction: The number of vehicles in Indonesia has increased every year. The number of two-wheeled vehicles in 2016 was 105.150.082 units and increased to 111.988.863 in 2017 and 120.101.047 in 2018. Unfortunately, along with the increase in motorized vehicle users, the rate of traffic accidents that occurred also increased. One of the causes of the high number of traffic accidents in Indonesia is a large number of jobs in the transportation sector, such as online motorcycle taxis. This study aims to identify the factors that cause traffic accidents, including those caused by fatigue, negligence, knowledge of safety riding, and length of work for online motorcycle taxi drivers. Methods: This study is an analytic observational study with a cross-sectional design. The study population consisted of 110 online motorcycle taxi riders who are members of the Sidoarjo-Porong Online Driver Association Basecamp. Sampling was done by using the total sampling technique. The variables studied included subjective fatigue, negligence, knowledge of safety riding, length of work, and two-wheeled online motorcycle taxi traffic accidents. Data analysis was performed using Cramer’s V Correlation Coefficient or Phi Correlation Coefficient. Results: The results showed a significant correlation between subjective fatigue and the incidence of accidents as indicated by a value of r = 0.289. Furthermore, it was found that a weak correlation between negligence and the incidence of accidents with a value of r = 0.211. No correlation was found between knowledge of safe riding and the incidence of accidents marked with a value of r = -0.169. Meanwhile, there is only a weak correlation between the length of work and the incidence of accidents with a value of r = 0.214. Conclusion: Subjective fatigue, neglect, length of work has a correlation with two-wheeled online motorcycle taxi traffic accidents. There is no correlation between knowledge of safety riding with two-wheeled online motorcycle taxi traffic accidents.

Forecasting the Number of Vehicles in Indonesia Using Auto Regressive Integrative Moving Average (ARIMA) Method

The number of vehicles in Indonesia increases significantly from year to year. This has an impact on various aspects such as traffic jams, air pollution, traffic accidents etc. The purpose of this study is to obtain the best model for forecast the number of cars and the number of motorcycles in the next 11 years. For the purpose, ARIMA method was used. Using the historical data of the number of cars and the number of motorcycles from 2001 to 2019, the best model for forecasting the number of cars and the number of motorcycles is ARIMA (1,1,0) and ARIMA (2,1,2), respectively. The models have MAPE of 7.01% and 7.24% for cars and motorcycles, respectively.

Klasifikasi Jenis Kendaraan Menggunakan Metode Extreme Learning Machine

The number of vehicles in Indonesia has increased each year, both two-wheeled and four-wheeled vehicles; this is inversely proportional to the development of road infrastructure in Indonesia, which has not experienced much change or improvement. Supposedly, with the increase in the number of vehicles, road infrastructure must also keep pace so that things such as the accumulation of cars on the road do not occur, traffic accidents and congestion become obstacles to carrying out activities. Therefore, it is necessary to make a system to detect and classify vehicles' types in this study using two types of vehicles, namely cars and motorbikes. According to the Indonesian Central Statistics Agency (BPS), it is the highest number. The classification system uses digital image processing techniques, a science to study how an image is formed, processed, and analyzed by a computer to produce information that humans can understand. The method used in this research is the Extreme Learning Machine (ELM), a part of artificial intelligence in feedforward neural networks, where this method can solve regression and classification problems. The data used in this study are 25 images of cars and motorbikes as training data and 15 photos of cars and motorbikes as test data, respectively. The results obtained from this study are a system for classifying two types of vehicles, namely cars and motorbikes, with an accuracy rate of 86.6%.

MOBERAK (Motor Bebas Bahan Bakar Ramah Lingkungan)

The vehicle is an important requirement for daily activities. The increasing number of vehicles in Indonesia from year to year correlates with the worsening air quality, especially in big cities like Jakarta. Data also shows that 70% of air pollution in Jakarta comes from motorized vehicles that use fossil fuels. One source of energy that can be an alternative solution is electric-powered vehicles because they have advantages, which are not producing pollution. Electric vehicles generally use lithium batteries as a source of electric power. Lithium batteries that have been used up are generally just thrown away without going through the processing so that they will contaminate water and soil. Therefore, we want to make vehicles that are not dependent on fossil fuels, produce no pollution, and can do auto charging electric so they don't rely on PLN electricity. This vehicle can charge independently because it has an electromagnetic coil on the rear wheel that will produce GGL induction from the wheel rotation when the bike is moving. We call this vehicle MOBERAK (Environmentally Friendly Fuel-Free Motorbike).

Car Driver Drowsiness Recognition Android-Based System

The growth of the number of vehicles in Indonesia especially in terrestrial mode is also offset by the increasing number of accidents. One of the main causes of traffic accidents is due to drivers who driving in drowsiness. This condition leads to loss of concentration and even awareness of the driver. The drowsiness recognition system built into android smartphone platforms which owned by almost all walks of life, can help the community and government in providing direct warning especially to motorists while driving in a drowsy state. The method used is the Haar-Cascade Classifier to detect the driver's face and utilize the detectable face size ratio to create ROI in the mouth area. Then the using of the FindContour algorithm to find contours in dark areas when the mouth is open because it evaporates. The size of the contour will be compared to the Mouth ROI size for the drowsy driver's decision. System creation using Android Studio with C ++ and Java programming languages, as well as OpenCV libraries for Haar-Cascade and FindContour. Based on the test to 10 respondents, the accuracy of the system recognizes sleepiness on the driver reached 88.7% during the day.

Design of Parking Control Using Ultrasonic Sensor Based On Fuzzy Logic

The number of vehicles in Indonesia is currently increasing, which is not matched by the availability of parking lots, especially cars. Like in public places, namely, offices, shops, and other public places. However, in Indonesia the use of parking lots is still less organized, such as too close the position of one car to another, the position of the vehicle that is not in line with the slot, this can cause inconvenience in the use of parking lots or both parties. Supervision carried out by the manager of the parking lot is still lacking because it can be caused by the vast parking area and the number of supervised vehicles, so that a parking control system is needed that can help overcome this problem. The control system to be designed uses a proximity sensor to detect the proximity of the vehicle to one another, where the position of the vehicle has been determined, not only to detect proximity, but the number of vehicles that have entered the parking area, so parking users know whether the slot provided is still available or not. To detect distance, fuzzy logic method is applied. Fuzzy methods are applied to read the conditions received by the proximity sensor, and calculate the number of vehicles using infra red and photodiode sensors. If information from the proximity sensor that is processed in the microcontroller by fuzzy logic is detected, the output is in the form of an LED indicator and alarm warning.

Appropriate CNN Architecture and Optimizer for Vehicle Type Classification System on the Toll Road

The growth in the number of vehicles in Indonesia causes traffic jam problems, including on the toll roads. Traffic jam problem on the toll roads occurs because the users must stop and make payments in the toll gate. Government built an Automatic Toll Gate Shelter (or Gardu Tol Otomatis/GTO) as an effort to reduce this problem. However, GTO can only be used by certain type of vehicles only. In this study, we developed a system that can classify type of vehicles so that GTO can be used for various types of vehicles that cross the toll road. The developed system will receive vehicle input to be classified. The learning process to do the classification is using the Convolutional Neural Network (CNN). The CNN algorithm is trained first with 2,930 vehicle images divided into 1,794 vehicles type 1 (van, jeep, and pick-up) image, 507 vehicle type 2 images (truck with 2 axle), and 631 vehicle type 3 images (truck with 3 axle). From the experimental results of CNN architecture and various parameters of the architecture, the best accuracy is found on MiniVGGNet architecture which applies Adadelta optimization function and input image parameter 64x64 and epoch 40. The result obtained from the network has accurate evaluation or out-sample accuracy of 73%.

PEMANFAATAN GEOFENCE UNTUK MENCARI LOKASI BENGKEL TAMBAL BAN TERDEKAT BERBASIS ANDROID

The number of vehicles in Indonesia continues to increase every year. It will also be directly proportional to many people who have problems with their vehicles, such as finding a tire leaking from a nail puncture or other causes. And will also increase the need for tire services. For vehicle users who do not know the area around when experiencing leak tire disaster, then directly proportional to search for the nearest tire repair shop will be difficult. Therefore, in this study developed information media in the form of Android-based applications to map the locations - workshop tire repair shop, as well as search for the nearest tire patch based on the location of the rider by using geofence system, where in this application the user will be notified the nearest workshop with a blink on the animated image tire repairs. From the test results, this application is able to help users search for the nearest tire repair shop along with the distance from the user location. This application is also able to show related information as well as showing the distance and route of the road that will be taken from the location of the user with the location of the intended tire patch by utilizing google maps applications. Applications have been tested by questionnaire method distributed to 30 respondents with 10 questions and the results of the questionnaire calculated using the likert scale get 76,2% results and included in either category

Determinant of Fuel Consumption in Indonesia

Fuel consumption in Indonesia is increasing due to rising incomes, the number of motor vehicles in Indonesia. The purpose of this study was to determine the effect of fuel price policy, motor vehicles (motorcycles), per capita income on the consumption of fuel (Premium). The object of this study is the fuel consumption in the Republic of Indonesia period 1985-2014. The design of this research study with a quantitative approach. Analyzed using Multiple Linear Regression Ordinary Least Square method (OLS). Based on the results of this study concluded that the pricing policies have a significant effect on the consumption of premium, per capita income has positive influence on consumption of premium, the number of motorcycles positive effect on premium consumption, as well as fuel prices, per capita income, and the number of motorcycles simultaneously positive effect on consumption of premium.

Development of institutional funding model of deep discount bond and land lease on a toll road project

Toll road is one of the most important parts of connectivity infrastructure. However, the current length of the existing toll roads is still not sufficient compared to the increasing number of vehicles in Indonesia. Nevertheless, the needs for infrastructure funding including for toll roads are not comparable to the availability of state budget. Innovations in funding schemes were required to meet such needs such as Deep Discount Bond (DDB) and Land Lease (LL). To ensure these schemes are running appropriately, an institutional funding model is needed to organize the stakeholders involved. Therefore, five institutional funding models were developed based on the conditions of the DDB issuer (project or corporate finance), LL executor [State Assets Management Institutions (LMAN) or Special Purpose Company (SPC)], and the number of SPC in the models. In addition, ten institutional success factors were identified. Data was collected using in-depth interviews consisting of three parts and analyzed using the Relative Importance Index to rank the institutional success factors found and using the Multi Criteria Analysis to choose the most effective institutional funding model. The institutional success factors that were found to have great values were those related to Government. At the same time, the most effective funding model is a corporate finance scheme, where LL is executed by LMAN, and a single SPC is used.

PERANCANGAN APLIKASI LOKASI TAMBAL BAN DI PONOROGO BERBASIS ANDROID

The number of vehicles in Indonesia continues to increase every year. This also happened in Ponorogo regency. It will also be directly proportional to the number of people who have problems with their vehicles, such as leaked tire quotes for being nailed or other causes. And will also increase the need for tire services. For motorists who are less aware of the surrounding area when experiencing damage to motorcycle tires, then of course to find a place nearest tire patch will be quite difficult. Therefore in this study developed information media for Android-based applications to map the locations - tire patch locations in Ponorogo, as well as looking for the closest tire patch with the rider. This app is a location-based service (location-based service) to the driver with the nearest patch of the banal location. Based on the results of testing this application can help users find the location of location preservation, tar bambal patch location, tire repair shop list, and tire repair shop list distance. This application can also show each other the location in accordance with the location of google maps applications.

Use of Crumb Rubber as an Additive in Asphalt Concrete Mixture

As the rapidly growing number of vehicles in Indonesia, the waste of tire rubber becomes a major environmental concern. The use of crumb rubber, which is the recycled tire rubber, as an additive in hot mix asphalt mixture is considered as a sustainable construction method. The purpose of this study was to investigate the effect of adding crumb rubber to asphalt mixture using wet process. The laboratory hot mix asphalt design tests were done by Marshall Method procedure. In this study, two different crumb rubber contents (1% and 2% by weight of asphalt mixture) and two different crumb rubber sizes (#40 and #80) were investigated. A comparative study was done among the unmodified and modified asphalt concrete mixtures considering the Marshall Stability value and the volumetric properties. The results showed that crumb rubber is recommended as an additive in asphalt mixture, as all the test results are within the standard requirements. The addition of crumb rubber tended to increase the strength and quality of asphalt mixture. However, it should be more concern about durability of asphalt mixture because of the lower asphalt content in crumb rubber modified asphalt mixture.

Internet of Things (IoT) as Green City Economic Development Smart Transportation System

The number of vehicles in Indonesia based on BPS data in 1987 amounted to 7.98148 million units to 104 118 969 units in 2013. An increase in the number of vehicles by 1304.51% is dominated by a motorcycle which was originally 5,554,305 units to 84,732,652 units. A large number of vehicles adds to problems of traffic regulation on the road. Internet of Things (IoT) can be used as the vehicle detection control device so as to create solutions Green Economic Development City Smart Transportation System that is good in handling motor vehicle. IoT sensor devices produced can identify the vehicles through model of information system connected with the detection system of motor vehicle license plate identification by means of sensors and data are stored in a digital chip which is mounted on any motor vehicle. With the chip of these vehicles will be produced a Green Economic Development City Smart Transportation System for the development of cities, especially in Narotama.

Gasoline and Synthetic Fuel from Plastic Waste

Currently the use of motor gasoline from year to year increase. In 2010 the number of vehicles in Indonesia about 26,706,705 vehicles, in 2011 amounted to 30,769,093 vehicles and 2012 amounted to 38,156,278 vehicles. This resulted in the consumption of petroleum fuels and exhaust emissions in motor vehicles is increasing. To overcome these problems, conducted research on synthetic fuel which is one of the alternative fuel sources. This research was conducted at gasoline engine. Variations in fuel mixture gasoline and synthetic fuel. This research will be able to generate and determine the effect of fuel mixture gasoline-synthetic fuel on levels of exhaust emissions, to determine the effect of fuel mixture gasoline-synthetic fuel for engine performance. Based on the analysis of performance and exhaust emissions test on a gasoline engine, for most engine performance is good and efficient set at first to mix synthetic fuel.