scholarly journals Data Mining Untuk Mengetahui Tingkat Loyalitas Konsumen Terhadap Merek Kendaraan Bermotor dan Pola Kecelakaan Lalulintas di DIY

2011 ◽  
Vol 5 (3) ◽  
pp. 1
Author(s):  
Agus Sasmito Ariwibowo ◽  
Edi Winarko
Keyword(s):  
Data Mining ◽  
Brand Loyalty ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Police Department ◽  
Mining Method ◽  
Data Traffic ◽  
Rule Based ◽  
Accident Data ◽  
Using Data

Abstract— The data of vehicle sales and traffic accident can be processed into information that is important for vehicle dealers and the Police Department. Those important information researched are the level of consumer loyalty to the vehicle brands and to predict the vehicle’s brands that will be purchased by a consumer. The study also tries to analyze the traffic accident data to find out is there any link between the occurrence of an accident to a certain brand of vehicle.                This research implementing data mining method called ‘rule based classification’ to establish the sales of vehicles rules by which can be used to classify consumer into group level of brand loyalty and also estimate the brand of the next vehicle’s brand that will be purchased by the consumer. This research will process the data traffic accident by using data mining techniques called Apriori Method. Apriori Method is used to identify a pattern of accidents based on brand, type of vehicles, and the vehicle’s color. The results are used to estimate whether there is any correlation between the occurrences of a traffic accident to a particular brand.                The result can help companies or vehicle dealers to obtain information about the level of the consumer’s brand loyalty to the dealer’s brand and to predict the brand that the consumer would be buy for the next vehicle. The result can also help the Police Department to find out whether there is any correlation between the occurrence of traffic accidents to the brand, type and the color of vehicle. Keywords— rule based classification, apriori, brand loyalty, traffic accident.

scholarly journals K-Means Clustering untuk Data Kecelakaan Lalu Lintas Jalan Raya di Kecamatan Pelaihari

2018 ◽  
Vol 5 (5) ◽  
pp. 613 ◽  
Author(s):  
Winda Aprianti ◽  
Jaka Permadi
Keyword(s):  
Data Mining ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Distance Measure ◽  
Data Traffic ◽  
First Aid Training ◽  
Accident Data ◽  
Special Concern ◽  
Clustering Data ◽  
Minor Injuries

<p>Kecelakaan lalu lintas di jalan raya masih menjadi penyumbang tingginya angka kematian di Indonesia, sehingga menjadi perhatian khusus bagi kepolisian di negara ini. Termasuk Kepolisian Resor (Polres) Tanah Laut, yang telah membuktikan perhatian tersebut dengan membentuk komunitas korban kecelakaan lalu lintas dan Pelatihan Pertolongan Pertama Gawat Darurat (PPGD). Tahapan awal pencegahan kecelakaan lalu lintas adalah dengan mengetahui faktor-faktor penyebab kecelakaan lalu lintas yang diperoleh melalui analisa data kecelakaan. Analisa tersebut dapat dilakukan dengan data mining, yaitu <em>K-Means Clustering.</em> <em>K-Means Clustering</em> mengelompokkan data menjadi beberapa <em>cluster</em> sesuai karakteristik data tersebut. Data kecelakaan lalu lintas dibagi menjadi 2 dataset, yakni dataset 1 dan dataset 2. Hasil <em>cluster </em>penerapan <em>K-means clustering </em>terhadap dataset 1 dan dataset 2 kemudian dilakukan pengujian <em>silhoutte coefficient </em>untuk mencari hasil <em>cluster </em>dengan kualitas terbaik<em>. </em>Pengujian <em>silhoutte coefficient</em> secara berurutan menghasilkan <em>distance measure </em>paling optimal yakni <em>clustering </em>dengan 4 <em>cluster</em> untuk dataset 1 dan <em>clustering </em>dengan 2 <em>cluster</em> untuk dataset 2. Selain memperoleh <em>cluster </em>dengan kualitas terbaik, penganalisaan data juga menghasilkan beberapa informasi kecelakaan lalu lintas yang sering terjadi, yakni faktor penyebab dan korban kecelakaan adalah pengemudi, umur korban adalah 9 sampai 28 tahun, dan keadaan korban kecelakaan adalah luka ringan.</p><p> </p><p class="Judul2"><strong><em>Abstract</em></strong></p><p><em>Traffic accidents on the highway are still contribute to the high mortality rate in Indonesia, which are becoming a special concern for the police. Including the Police of Tanah Laut Resort where prove themselves by established The Community of Traffic Accident Victims and Emergency First Aid Training. The first prevention of traffic accidents is knowing the factors causing traffic accidents which is obtained through the analysis of traffic accident’s data. It can be done through data mining, i.e. K-Means Clustering, which is clustering data into clusters according to characteristics of the data. Traffic accident data is divided into two datasets, namely dataset 1 and dataset 2. After obtaining the cluster results, the next step is to calculate silhoutte coefficient which is used to find the best quality cluster result. The result of testing silhoutte coefficient are clustering with 4 clusters for dataset 1 and clustering with 2 clusters for dataset 2. Analyzing data in this research also produces some information on traffic accidents that often occur, namely the causes and victims of accidents are drivers, the age of the victims is between 9 and 28 years old, and the circumstance of the accidents victims are minor injuries.</em></p>

scholarly journals Kematian akibat kecelakaan lalu lintas Kota Tomohon tahun 2012-2014

e-CliniC ◽  
2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Arischa Rompis ◽  
Johannis Mallo ◽  
Djemi Tomuka
Keyword(s):  
Traffic Accident ◽  
Human Error ◽  
Traffic Accidents ◽  
Police Department ◽  
Male Victims ◽  
The Road ◽  
The World ◽  
Environment Factor ◽  
Using Data ◽  
Age Range

Abstract: Traffic accident as a health problem being the most causal factor of injury in the world. Most cases of injuries occur in the age range 15-44 years and are dominated by man with disability proportion and also that of traffic accident around 25%. The most important factor who determine level of accident distribution by human error who contribute 75-80% and also affected by disciplinary factor in driving (80-90%), vehicle factor (4%), the road (3%), and environment factor (1%). This study aimed to obtain some information about the death caused by traffic accident in Tomohon city between the years 2012-2014. This was a descriptive retrospective study using data of Police Department in Tomohon from October to November 2015. The results showed that the peak of deaths due to traffic accidents in Tomohon city (2012-2014) was in 2013 with 50 male victims from 59 victims aged 15-24 years. Most of the victims were motorcycle drivers.Keywords: death, traffic accidentAbstrak: Kecelakaan lalu lintas merupakan masalah kesehatan yang menjadi penyebab terbanyak terjadinya cedera di seluruh dunia. Kasus cedera terbanyak terjadi pada rentang usia 15 - 44 tahun yang didominasi kaum pria dengan proporsi disabilitas dan kematian karena kecelakaan sekitar 25%. Faktor yang dianggap menentukan tingginya jumlah kecelakaan dan keparahan korban kecelakaan yaitu faktor manusia yang memberikan kontribusi 75-80% yang juga dipengaruhi oleh faktor kedisiplinan dalam berkendara (80-90%), faktor kendaraan (4%), faktor jalan (3%) , dan faktor lingkungan (1%). Penelitian ini bertujuan untuk mengetahui informasi mengenai kematian akibat kecelakaan lalu lintas di kota Tomohon tahun 2012 – 2014. Metode penelitian yang digunakan adalah metode deskriptif retrospektif yang dilakukan di bagian lalu lintas POLRESTA TOMOHON pada bulan Oktober – November 2015. Hasil yang diperoleh dari penelitian ini menggambarkan kematian akibat kecelakaan lalu lintas di kota Tomohon 2012 – 2014 mengalami puncak kenaikan pada tahun 2013 dengan korban terbanyak laki – laki dan berada direntang usia 15 – 24 yang berstatus sebagai pengendara sepeda motor. Lokasi kejadian kecelakaan tersering di wilayah Tomohon Tengah yang didominasi jalan dalam kota.Kata kunci: kematian, kecelakaan lalu lintas

scholarly journals Analisa Penyebab Kemacetan Dan Kecelakaan Jalan Raya Ngaliyan Kota Semarang Tanjakan Silayur

2021 ◽  
Vol 8 (2) ◽  
pp. 174-181
Author(s):  
Samba Wangsa ◽  
Prasasta Samba ◽  
Mudjiastuti Handajani ◽  
Agus Muldiyanto
Keyword(s):  
Traffic Accident ◽  
Human Error ◽  
Traffic Accidents ◽  
The Road ◽  
Road Users ◽  
Traffic Performance ◽  
Accident Data ◽  
Road Performance ◽  
On The Road ◽  
Using Data

A traffic accident is a tragedy or accident that occurs on the road involving a motorized or heavy vehicle with other road users or without a vehicle. This incident caused the victim to suffer physical, health and material losses. Traffic accidents occur due to several factors such as human error or inadequate road conditions. Even traffic jams can also lead to traffic accidents. The problem of driving and road safety needs to be considered to reduce the number of traffic accidents that occur. This study was conducted to determine the factors that cause accidents, especially those caused by road conditions and traffic performance. The method used in the field observation research and using data on the number of accidents in 2018–2020 located on Jalan Raya Ngaliyan which was taken from the accident data of the West Semarang Police Traffic Unit. The level of road performance on Jalan Tanjakan Silayur Semarang City, at peak hours in the morning and non-peak hours during the day category C and at peak hours in the afternoon category E. Damage to the flexible pavement surface on Jalan Tanjakan Silayur is dominated by the type of damage cracks, grooves, and bleeding. One of the factors that caused the accident was because the traffic signs were not optimal on the Jalan Tanjakan Silayur section.

scholarly journals ROAD SAFETY CAMPAIGNS TO REDUCE TRAFFIC ACCIDENTS FOR YOUNG ROAD USERS

ICCD ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 601-606
Author(s):  
Widodo Budi Dermawan ◽  
Dewi Nusraningrum
Keyword(s):  
School Environment ◽  
Road Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
School Administrators ◽  
Road User ◽  
The Road ◽  
Road Users ◽  
Accident Data

Every year we lose many young road users in road traffic accidents. Based on traffic accident data issued by the Indonesian National Police in 2017, the number of casualties was highest in the age group 15-19, with 3,496 minor injuries, 400 seriously injured and 535 deaths. This condition is very alarming considering that student as the nation's next generation lose their future due to the accidents. This figure does not include other traffic violations, not having a driver license, not wearing a helmet, driving opposite the direction, those given ticket and verbal reprimand. To reduce traffic accident for young road user, road safety campaigns were organized in many schools in Jakarta. This activity aims to socialize the road safety program to increase road safety awareness among young road users/students including the dissemination of Law No. 22 of 2009 concerning Road Traffic and Transportation. Another purpose of this program is to accompany school administrators to set up a School Safe Zone (ZoSS), a location on particular roads in the school environment that are time-based speed zone to set the speed of the vehicle. The purpose of this paper is to promote the road safety campaigns strategies by considering various campaign tools.

Study on condition setting of micro-drill catalogs for PCBs by using data-mining method

2016 ◽  
Vol 2016.11 (0) ◽  
pp. B05
Author(s):  
Shogo TABATA ◽  
Toshiki HIROGAKI ◽  
Eiichi AOYAMA ◽  
Hiroyuki KODAMA
Keyword(s):  
Data Mining ◽  
Mining Method ◽  
Data Mining Method ◽  
Using Data ◽  
Micro Drill

scholarly journals Empirical Modelling for exploring the factors contributing to disability severity from road traffic accidents in Thailand

1970 ◽  
Vol 6 (2) ◽  
pp. 176-185
Author(s):  
Jaratsri Rungrattanaubol ◽  
Anamai Na-udom ◽  
Antony Harfield
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Traffic Accidents ◽  
Injury Severity ◽  
Road Traffic ◽  
Road Traffic Accidents ◽  
Empirical Modelling ◽  
Standard Data ◽  
Accident Data ◽  
Computer Based

This paper introduces a computer-based model for predicting the severity of injuries in road traffic accidents. Using accident data from surveys at hospitals in Thailand, standard data mining techniques were applied to train and test a multilayer perceptron neural network. The resulting neural network specification was loaded into an interactive environment called EDEN that enables further exploration of the computer-based model. Although the model can be used for the classification of accident data in terms of injury severity (in a similar way to other data mining tools), the EDEN tool enables deeper exploration of the underlying factors that might affect injury severity in road traffic accidents. The aim of this paper is to describe the development of the computer-based model and to demonstrate the potential of EDEN as an interactive tool for knowledge discovery.

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