Accurate data aggregation for VANETs

2007 ◽  
Author(s):  
Khaled Ibrahim ◽  
Michele C. Weigle
Keyword(s):  
Data Aggregation ◽  
Accurate Data

scholarly journals Accurate Data Aggregation Created by Neural Network and Data Classification Processed Through Machine Learning in Wireless Sensor Networks

2021 ◽  
Author(s):  
Sudha C ◽  
Suresh D ◽  
Nagesh A
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Data Classification ◽  
Wireless Sensor ◽  
Accurate Data ◽  
Network Resources ◽  
Aggregated Data

Abstract Data aggregation is the process of efficiently collecting and transferring sensing data to a destination; it aids in the methodical and cautious utilization of sensor network resources. In the same way, when opening aggregated data that is free of noise and errors, the accuracy and efficiency of the data received improve. For this to happen, the data must flow to the destination in the most precise manner and in the shortest possible time by understanding the area's circumstances and addressing the immediate demands of the site where the sensors are positioned. This necessitates precise algorithms that eliminate errors and noise in the sense of data before aggregating it. The network used the ACNM technique – accurate data aggregation created by neural networks and data classification processed through machine learning in wireless sensor networks. We employ machine learning as part of artificial intelligence that learns from data. Following that, it can detect errors and noise in that Data in stages, reduce them, process them in a neural network model, and finally aggregate them to deliver the most accurate data to the destination. When data was provided using this ACNM protocol, the results showed that it arrived at its destination with the least delay.

PENERAPAN ALGORITMA K-MEANS UNTUK PENGELOMPOKAN DAERAH RAWAN BENCANA DI INDONESIA

2019 ◽  
Vol 1 (2) ◽  
pp. 1-10
Author(s):  
Amril Mutoi Siregar
Keyword(s):  
Natural Disasters ◽  
Accurate Data ◽  
Disaster Victims ◽  
Central Java ◽  
North Sulawesi ◽  
Natural Beauty ◽  
Or Groups ◽  
Disaster Data ◽  
The Government ◽  
Almost All

Indonesia is a country located in the equator, which has beautiful natural. It has a mountainous constellation, beaches and wider oceans than land, so that Indonesia has extraordinary natural beauty assets compared to other countries. Behind the beauty of natural it turns out that it has many potential natural disasters in almost all provinces in Indonesia, in the form of landslides, earthquakes, tsunamis, Mount Meletus and others. The problem is that the government must have accurate data to deal with disasters throughout the province, where disaster data can be in categories or groups of regions into very vulnerable, medium, and low disaster areas. It is often found when a disaster occurs, many found that the distribution of long-term assistance because the stock for disaster-prone areas is not well available. In the study, it will be proposed to group disaster-prone areas throughout the province in Indonesia using the k-means algorithm. The expected results can group all regions that are very prone to disasters. Thus, the results can be Province West java, central java very vulnerable categories, provinces Aceh, North Sumatera, West Sumatera, east Java and North Sulawesi in the medium category, provinces Bengkulu, Lampung, Riau Island, Babel, DIY, Bali, West Kalimantan, North Kalimantan, Central Sulawesi, West Sulawesi, Maluku, North Maluku, Papua, west Papua including of rare categories. With the results obtained in this study, the government can map disaster-prone areas as well as prepare emergency response assistance quickly. In order to reduce the death toll and it is important to improve the services of disaster victims. With accurate data can provide prompt and appropriate assistance for victims of natural disasters.

STUDI KARAKTERISTIK SISWA SLTA DI KOTA MEDAN

2013 ◽  
Vol 6 (2) ◽  
Author(s):  
Nathanael Sitanggang ◽  
Abdul Hasan Saragih
Keyword(s):  
High School ◽  
Quantitative Method ◽  
Female Students ◽  
Senior High School ◽  
Reliability Coefficient ◽  
Male Students ◽  
Accurate Data ◽  
Male And Female ◽  
Student Characteristic

Abstrak: Tujuan penelitian ini adalah untuk mentetahui karakteristik SMA dan SMK di Medan. Karakteristik yang diteliti adalah: neuroticism, extraversion, keterbukaan, keramahan, dan hati nurani. Dengan penelitian ini kita mendapatkan data perbedaan karakter di SMA dan SMK siswa. Mendapatkan perbedaan karakter antara pria dan wanita dalam setiap kelompok sekolah. Penelitian ini di SMA dan SMK di Medan, 2008. Sampel penelitian 600 siswa. Metode Penelitian kuantitatif. Data diperoleh melalui kuesioner. Kuesioner dicoba dengan nilai koefisien reliabilitas (r=0,875). Hasil penelitian adalah: (1) Karakteristik siswa SMA (Neuroticsm, extraversion, keterbukaan, keramahan, dan hati nurani) sudah cukup dan kategori tinggi, (2) Karakteristik siswa SMK (Neuroticsm, extraversion, keterbukaan, keramahan, dan hati nurani) cukup tinggi dan kategori; (3) Para siswa perempuan SMA lebih tinggi hati nurani daripada siswa laki-laki; (4) Neuroticsm, extraversion, keterbukaan, dan keramahan antara siswa laki-laki secara signifikan tidak berbeda dengan siswa perempuan di SMA; (5) Neuroticsm, extraversion, keterbukaan, keramahan, dan conscientiousness antara mahasiswa laki-laki secara signifikan tidak berbeda dengan siswa perempuan di SMK.   Kata kunci : karakteristik siswa, SMA, SMK.   Abstract: This research was aimed to: investigate the Senior High School Studen’t Characteristic in Medan. The characteristic which investigated are: neuroticism, extraversion, openness, agreeableness, and conscientiousness. By this research we can get the accurate data that describe the differences of characters in SMA and SMK students. And then we can get the differences of characters among the male and female in each group of school. This research was taking place in SMA and SMK in Medan, 2008. The sample of this research is 600 pupils. The research was taken in the quantitative method. The data that we have got from the questioner. Questioner has been tried with the value of reliability coefficient (r=0,875). The results of the research are: (1) The SMA Studen’t Characteristic in Medan (Neuroticsm, extraversion, openness, agreeableness, and conscientiousness) is enough and high categories; (2) The SMK Student Characteristic in Medan (Neuroticsm, extraversion, openness, agreeableness, and conscientiousness) is enough and high categories; (3) The female SMA students are more conscientiousness than male students; (4) Neuroticsm, extraversion, openness, and agreeableness between male students significantly is not different with female students in SMA; (5) Neuroticsm, extraversion, openness, agreeableness, and conscientiousness between male students significantly is not different with female students in SMK. Keywords: characteristics of students, SMA, SMK

DISCRESSION OF THE SAMPLE RESORTS POLICE IN THE IMPLEMENTATION OF ADMINISTRATIVE LAW PERSPECTIVE INVESTIGATION

2020 ◽  
Vol 4 (2) ◽  
pp. 147
Author(s):  
Tamrin Muchsin ◽  
Sri Sudono Saliro ◽  
Nahot Tua Parlindungan Sihaloho ◽  
Sardjana Orba Manullang
Keyword(s):  
Empirical Research ◽  
Qualitative Method ◽  
Government Regulation ◽  
Sampling Technique ◽  
Administrative Law ◽  
Criminal Investigation ◽  
Accurate Data ◽  
Long Distance ◽  
The Impact ◽  
Depth Interviews

It is still found that investigating officers do not have an S1 degree or equivalent in thejurisdiction of the Sambass Resort Police as mandated in PP No. 58 of 2010 concerningAmendments to Government Regulation Number 27 of 1983 concerning theImplementation of KUHAP article 2A paragraph (1) letter a. If the requirements ofinvestigators are not fulfilled, there will automatically be limits of authority, includingthe inability to issue investigation orders, detention warrants and other administrativeletters. This study used a qualitative method with juridical empirical research. Toobtain accurate data, purposive sampling technique was used, and primary datacollection by conducting in-depth interviews. The research results found, among others:first, discretion regarding the administration of investigations in the jurisdiction of theSambas Resort Police for the Sambas District Police who do not have investigatingofficers who meet the requirements, is then taken over by the Head of the CriminalInvestigation Unit as the supervisor of the integrated criminal investigation function.Second, the impact of an integrated investigation administration causes the time tocarry out investigations to be slow due to the long distance between the Sector Policeand the Resort Police.

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