This paper focuses in the selection of an optimal path pair for cooperative diversity based on cross-layer optimization in multihop wireless ad hoc networks. Cross-layer performance indicators, including power consumption, signal-to-noise ratio, and load variance are optimized using multi-objective optimization (MOO) with Pareto method. Consequently, optimization can be performed simultaneously to obtain a compromise among three resources over all possible path pairs. The Pareto method is further compared to the scalarization method in achieving fairness to each resource. We examine the statistics of power consumption, SNR, and load variance for both methods through simulations. In addition, the complexity of the optimization of both methods is evaluated based on the required computing time.
Dengan perkembangan teknologi informasi yang sangat pesat pada zaman ini membutuhkan penyesuaian yang tepat dalam pemanfaatan teknologi informasi tersebut. Pemanfaatan teknologi informasi sudah mencakup kesegala bidang kehidupan termasuk organisasi maupun industri digital. Didalam sebuah organisasi atau industri digital pasti akan memerlukan suatu aplikasi maupun sistem informasi. Didalam membuat sebuah sistem informasi maka diperlukanlah suatu metode pengembangan perangkat lunak. Metode pengembangan perangkat lunak berbagai macam jenisnya, salah satunya yang sering dipakai adalah metode SDCL Waterfall. SDCL Waterfall pada prinsipnya mengikuti tahapan – tahapan yang terorganisir dan sistematis. Metode Waterfall sangat menekankan kepada requirement yang jelas pada suatu perangkat lunak yang akan di kembangkan. Maka daripada itu sering terjadinya masalah ketika suatu perangkat lunak yang akan dikembangkan tetapi kebutuhan awal belum begitu jelas dan kemungkinan untuk perubahan pada saat development besar kemungkinannya. Seiiring berkembangnya teknologi, maka metode pengembangan perangkat lunakpun mengalami perkembangan, maka muncullah sebuah metode baru yaitu metode scrum.
This research analyzes the metaheuristic methods, that is, ant colony optimization (ACO), genetic algorithm (GA), and particle swarm optimization (PSO), in the selection of path pairs on multicriteria ad hoc network. Multicriteria used are signal-to-noise ratio (SNR), load variance, and power consumption. Analysis of the simulation result is done as follows: first, in terms of computing time, the ACO method takes the most time compared with GA and PSO methods. Second, in terms of multicriteria performance, i.e., the performance of SNR, load variance, and power consumption, the GA method shows the same value in each repetition. It is different from ACO and PSO that show varying values. Finally, the selection of the path pairs by the GA method indicates the pairs of the path that are always the same as by the ACO and PSO methods indicate those that vary.
The Internet has become something important in the communication development. One communication facilities on the Internet is the Internet relay chat or known as chat. Chat applications in real time is often misused for the purpose of spreading the virus, promotions, and other interests known as spam. Spamming is the sending of unwanted messages by someone who has a chat account. This causes the chat account feel uncomfortable with the condition. Based on these problems this research create a chat application that can filter messages or spam filtering by applying text mining. Spam filtering process can be done in two phases: text pre-processing and analyzing. These two phases are carried out to calculate the weight (W) of connectedness with the word spam messages. Based on the results of tests performed on chat applications by applying text mining to perform filtering on spam messages generate the level of accuracy of 91.41%.
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