Perbandingan Metode-Metode Klasifikasi untuk Indoor Positioning System

Indoor Positioning System can provide position and navigation guidances inside a building.  This paper discusses about systematic comparison between K-Nearest Neigbors and Naïve Bayes Classifier over WiFi-based Indoor Position System dataset.  The dataset is collected using a custom Android Application, which able to receive and record WiFi signal strengths from the surrounding WiFi hotspots in UKDW campus. The dataset consists of 11658 Received Signal Strength (RSS) data from 41 public locations in UKDW campus.  We use 10-folds cross validation and T-Test with 0.05 significance level to compare classification accuracy between K-Nearest Neigbors and Naïve Bayes classifier.  Based on the experiment result, we can conclude that K-Nearest Neighbors classifier produces better classification accuracy (83.58%) than Naïve Bayes (61.52%)

Aplikasi Optimalisasi Muat Barang Dengan Penerapan Algoritma Dynamic Programming Pada Persoalan Integer Knapsack

In the era of globalization, the use of information technology become a necessity that can not be separated in running a business in all instances. The need of information technology is not only used as a supporter of the process, but also has become a major part of which should go well. It was felt also by the CV. Labatrans engaged in courier services, which often occurs excess or shortage even when the goods are loaded into a vehicle that will deliver. There has been no control of the goods to be delivered, so that sometimes exceed the limit load capacity of the vehicle. This cause a heap of goods in the warehouse, and the main problem consumers will be disappointed because the goods delivered are not accepted at the right promised time. Another problem occurs when consumers asked where the goods they are shipped, they want to know where their goods for some reason such as perishable goods or food. And usually the staff of the company can not give an answer because of limited information. The purpose of this research is to create an application that can handle tracking of goods delivered and the load optimization by applying Dynamic Programming Algorithms on the issue of Integer Knapsac

Metode Hibrida FCM dan PSO-SVR untuk Prediksi Data Arus Lalu Lintas

Abstract — Traffic flow forecasting is one important part in Intelligent Transportation System. There are many methods had been developed for time series and traffic flow forecasting such as: Autoregressive Moving Average (ARIMA), Artificial Neural Network (ANN), and Support Vector Regression (SVR). SVR performance depend on kernel function and parameters of those kernel and data characteristic used in SVR as well. This research proposed hybrid method for traffic flow data clustering and forecasting. Fuzzy C-means is used in  order to minimize the variance in whole dataset. Particle Swarm Optimization (PSO) is used in order to select the appropriate parameters for SVR. Experimental result shows the proposed method give MAPE below 4% in all test sites. Keywords—fuzzy c-means, particle swarm optimization, prediksi data lalu lintas, support vector regression, time-series.Traffic flow forecasting is one important part in Intelligent Transportation System. There are many methods had been developed for time series and traffic flow forecasting such as: Autoregressive Moving Average (ARIMA), Artificial Neural Network (ANN), and Support Vector Regression (SVR). SVR performance depend on kernel function and parameters of those kernel and data characteristic used in SVR as well. This research proposed hybrid method for traffic flow data clustering and forecasting. Fuzzy C-means is used in  order to minimize the variance in whole dataset. Particle Swarm Optimization (PSO) is used in order to select the appropriate parameters for SVR. Experimental result shows the proposed method give MAPE below 4% in all test sites

Pengamanan Sertifikat Tanah Digital menggunakan Digital Signature SHA-512 dan RSA

Land trading as investment is sometimes find some barriers or problems. One of the problems is illegal or misclaimed of the land certificate. Badan Pertanahan Nasional (BPN) and Pejabat Pembuat Akta Tanah (PPAT) as institutions and correlated parties in the process of land certificate making need a system to handle the problem of falsification land certificate. The purpose of this research is to make secure system of digital land certificate document with a data protection system to detect if there is a falsification activity from certain party. This research hopefully can help BPN and PPAT as authorized institution of land certificate making and to lower the number of falsification. Digital signature SHA 512 and RSA are used in this research as a solution to keep data integrity of land certificate in a digital format, in this case, in an electronic book with.pdf format. Digital signature derived from xref table in.pdf file. This program has been consulted with BPN and PPAT officer in Salatiga. The result is, this program can be used and applied for authentication process of digital land certificate and help BPN to solve the problem of high number of falsification digital land certificate. Keywords—Sertifikat Tanah Digital, Digital Signature, Hash SHA 512, RSA, Integritas Data, Xref-Tabl

Halaman Depan Jutisi Agustus 2015

Ini adalah halaman depan JuTISI edisi Agustus 201

Halaman Depan

oai:ojs.journal.maranatha.edu:article/56