Perbandingan Algoritma C4.5 Dan Neural Network Untuk Memprediksi Hasil Pemilu Legislatif DKI Jakarta

General elections are a means of implementation of the sovereignty of the people in the Unitary State of Indonesia based on Pancasila and 1945 Constitution. Elections held in Indonesia is to choose the leadership of both the president and vice president, member of parliament, parliament, and the DPD. In this study comparison of data mining methods, namely C4.5 and neural network algorithm is applied to both the data legislative candidates to be elected to the legislature and were not selected. C4.5 algorithm is one of the algorithms in a decision tree method that converts the data into a decision tree using entropy calculation formula. While the neural network algorithm is a method like human neurons to find the best path. From the test results to measure the performance of both methods using cross validation test method, confusion matrix and ROC curves is known that the neural network has the highest accuracy value which is equal to 98.50%, followed by the C4.5 algorithm method with 97.84% accuracy values. AUC values for the neural network method showed the highest value of 0.982 and a decision tree algorithm with a value of 0.970

Penerapan Metode Neural Network Untuk Memprediksi Hasil Pemilu Legislatif

Pemilihan Umum di Indonesia telah mengalami beberapa Perubahan dari periode Pemilu ke periode Pemilu yang lain. Selama pemilu Orde Baru, kita mengenal sistem pemilu proporsional dengan daftar tertutup. Keterpilihan calon legislatif bukan ditentukan pemilih, melainkan menjadi kewenangan elite partai politik sesuai dengan susunan daftar caleg beserta nomor urut. Dalam sistem demikian, kedudukan parpol menjadi sangat kuat terhadap kadernya di parlemen. Namun di satu sisi, basis sosial dan relasi politik para wakil rakyat dengan konstituen menjadi lemah. Inilah yang menyebabkan kedudukan caleg terpilih mereka menjadi ”jauh” dalam hubungannya dengan konstituen. Semangat memilih langsung wakil rakyat baru mulai diakomodasi pada Pemilu 2004 melalui UU No. 12 Tahun 2003, dengan menggunakan sistem proporsional dengan daftar calon terbuka. Pemilih tidak hanya memilih tanda gambar parpol, tetapi juga diberi kesempatan memilih caleg.Penelitian yang berhubungan dengan pemilu sudah pernah dilakukan oleh peneliti yaitu dengan menggunakan metode decision tree dan classification tree dan estimator bayesian. Pada penelitian ini peneliti akan menggunakan metode neural network. Neural network telah menunjukkan hasil yang menjanjikan dalam prediksi untuk data time-series dibandingkan dengan pendekatan tradisional sehingga hasil prediksi pemilu legislatif DKI Jakarta lebih akura

Open Vpn-access Server dengan Enskripsi Ssl/ti Open Ssl

Computer network is one technology that is widely used by some companies today. one of the functions of a computer network is to connect one location to another. Use of the Internet as a communication medium other than very beneficial for the company, but still have drawbacks in terms of safety. PT.Indra Jalayatra not be separated from the use of the network and the Internet to the company's operations. constraints faced is how to access the data to obtain data from outside the office are required as a reports without having to come directly to the office, of course, with a very adequate level of security. Solutions that can be used for the issue of building a network with a Virtual Private Network technology. One of the applications that can be used is OpenVPN-Access Server by applying encryption using Open SSL. OpenVPN-Access Server provides convenience and security in forming a network of Virtual Private Network. Keywords: OpenVPN-Access Server, Security, Virtual Private networ

Penerapan Metode Open Vpn-access Server sebagai Rancangan Jaringan Wide Area Network

The development of information technology has developed rapidly from year to year. The use of the Internet as a communication mediation in addition to very useful but still has flaws in its security. PT. Valdo International to build a computer network to facilitate the conduct of operations, such as Rejuvenation application systems and other purposes. we need a way to connect to the intranet access existing LAN network at headquarters and branch offices in order to be able to access data easily and safely. , Data information is not safe to be in the public network because it can be intercepted by unauthorized parties. Therefore PT. Valdo International build VPN (Virtual Private Network) using the PPTP mirkrotik with lines, and can perform other operations in private in the public network, with connections an economical and secure data security

A computational fluid dynamics study of combustion and emission performance in an annular combustor of a jet engine

This paper is a Computational Fluid Dynamics (CFD) study of the performance of a jet engine annular combustor that was subjected to various loading conditions. The aim is to comprehend the effect of various genuine working conditions on ignition and emission performance. The numerical models utilized for fuel ignition is the feasible k-ω model for turbulent stream, species transport (aviation fuel and air) with eddy-dissipation reaction modelling and pollution model for nitrogen oxides (NOX) emission. The results obtained confirm the findings described in the literature

Keyphrase distance analysis technique from news articles as a feature for keyphrase extraction: An unsupervised approach

Due to the rapid expansion of information and online sources, automatic keyphrase extraction remains an important and challenging problem in the field of current study. The use of keyphrases is extremely beneficial for many tasks, including information retrieval (IR) systems and natural language processing (NLP). It is essential to extract the features of those keyphrases for extracting the most significant keyphrases as well as summarizing the texts to the highest standard. In order to analyze the distance between keyphrases in news articles as a feature of keyphrases, this research proposed a region-based unsupervised keyphrase distance analysis (KDA) technique. The proposed method is broken down into eight steps: gathering data, data preprocessing, data processing, searching keyphrases, distance calculation, averaging distance, curve plotting, and lastly, the curve fitting technique. The proposed approach begins by gathering two distinct datasets containing the news items, which are then used in the data preprocessing step, which makes use of a few preprocessing techniques. This preprocessed data is then employed in the data processing phase, where it is routed to the keyphrase searching, distance computation, and distance averaging phases. Finally, the curve fitting method is used after applying a curve plotting analysis. These two benchmark datasets are then used to evaluate and test the performance of the proposed approach. The proposed approach is then contrasted with different approaches to show how effective, advantageous, and significant it is. The results of the evaluation also proved that the proposed technique considerably improved the efficiency of keyphrase extraction techniques. It produces an F1-score value of 96.91% whereas its present keyphrases are 94.55%

Toll-like receptor-4 299Gly allele is associated with Guillain-Barre syndrome in Bangladesh

Objective: TLR4 plays an important role in the pathogenesis of Guillain-Barre syndrome (GBS). The relationships between TLR4 polymorphisms and susceptibility to GBS are poorly understood. We investigated the frequency and assessed the association of two single nucleotide polymorphisms (SNPs) in the extracellular domain of TLR4 (Asp299Gly and Thr399Ile) with disease susceptibility and the clinical features of GBS in a Bangladeshi cohort. Methods: A total of 290 subjects were included in this study: 141 patients with GBS and 149 unrelated healthy controls. The TLR4 polymorphisms Asp299Gly and Thr399Ile were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. Results: The minor 299Gly allele was significantly associated with GBS susceptibility (P = 0.0137, OR = 1.97, 95% CI = 1.17–3.31), and was present at a significantly higher frequency in patients with the acute motor axonal neuropathy (AMAN) subtype of GBS (P = 0.0120, OR = 2.37, 95% CI = 1.26–4.47) than acute inflammatory demyelinating polyneuropathy (AIDP) subtype (P = 0.961, OR = 1.15, 95% CI = 0.38–3.48); when compared to healthy controls. The genotype frequency of the Asp299Gly polymorphism was not significantly different between patients with GBS and healthy controls. The Asp299-Thr399 haplotype was associated with a significantly lower risk of developing GBS (P = 0.0451, OR = 0.63, 95% CI = 0.40– 0.99). No association was observed between the Thr399Ile polymorphism and GBS disease susceptibility. Interpretation: The TLR4 minor 299Gly allele was associated with increased susceptibility to GBS and the axonal GBS subtype in the Bangladeshi population. However, no associations were observed between the genotypes of the Asp299Gly and Thr399Ile SNPs and antecedent C. jejuni infection or disease severity in Bangladeshi patients with GBS

Keyphrases Frequency Analysis from Research Articles: A Region-Based Unsupervised Novel Approach

Due to the advancement of technology and the exponential proliferation of digital sources and textual data, the extraction of high-quality keyphrases and the summarizing of content at a high standard has become increasingly difficult in current research. Extracting high-quality keyphrases and summing texts at a high level demands the use of keyphrase frequency as a feature for keyword extraction, which is becoming more popular. This article proposed a novel unsupervised keyphrase frequency analysis (KFA) technique for feature extraction of keyphrases that is corpus-independent, domain-independent, language-agnostic, and length-free documents, and can be used by supervised and unsupervised algorithms. This proposed technique has five essential phases: data acquisition; data pre-processing; statistical methodologies; curve plotting analysis; and curve fitting technique. First, the technique begins by collecting five different datasets from various sources and then feeding those datasets into the data pre-processing phase using text pre-processing techniques. The preprocessed data is then transmitted to the region-based statistical process, followed by the curve plotting phase, and finally, the curve fitting approach. Afterward, the proposed technique is tested and assessed using five (5) standard datasets. Then, the proposed technique is compared with our recommended systems to prove its efficacy, benefits, and significance. Finally, the experimental findings indicate that the proposed technique effectively analyses the keyphrase frequency from articles and delivers the keyphrase frequency of 70.63% in 1st region and 10.74% in 2nd region of the total present keyphrase frequency