Analisis Sistem dan Prosedur Penjualan dan Penerimaan Kas dalam Mendukung Pengendalian Intern pada PT. Aneka Gas Industri Medan

Tujuan penelitian ini adalah untuk mengetahui sistem dan prosedur penjualan dan penerimaan kas dalam mendukung upaya peningkatan pengendalian intern PT Aneka Gas Industri Cabang Medan. Penelitian ini merupakan penelitian deskriptif dengan pendekatan kualitatif. Data diperoleh dari data sekunder. Teknik pengumpulan data menggunakan metode dokumentasi. Analisis data meliputi sistem dan prosedur penjualan dan penerimaan kas dan aspek pengendalian intern di PT Aneka Gas Industri Cabang Medan. Hasil penelitian ini menunjukkan bahwa terjadi penggabungan fungsi keuangan dengan fungsi pembelian, fungsi pajak belum dicantumkan pada struktur organisasi, pelaksanaan kegiatan penjualan dilakukan oleh fungsi yang terpisah atau tidak tergabung dalam bagian penjualan, dan terjadi perangkapan fungsi administrasi dengan fungsi kasir

PENGARUH PROMOSI, KUALITAS PELAYANAN DAN KUALITAS PRODUK TERHADAP KEPUTUSAN MENABUNG PADA BANK SUMUT

The purpose of this research is to analyze how the influence of promotion, service quality, and product quality on the saving decision at Bank Sumut. decrease in customer levels was due to inappropriate promotions, service quality, and product quality. the sample in this research amount to 119 employees. The results of partial hypothesis testing obtained tcount>ttable 3,791 > 1,980 with a significant value of 0.016<0.05, tcount > ttable or 2,301 > 1,980 with a significant value of 0.021 < 0.05, and tcount > ttable or 4.931 > 1.980 with a significant value 0.000 < 0.05. Fcount (10.014) > Ftable (2.45) and significance probability 0.000 < 0.05. The results of the coefficient of determination test obtained the Adjusted R Square value of 0.476, this means 47.6% of the dependent variable, namely the saving decision which can be explained by the independent variables, namely promotion, service quality, and product quality. The conclusion in this research is that partially and simultaneously the variables of promotion, service quality, and product quality have a positive and significant effect on saving decisions at Bank Sumut.  

Improved Instance Selection Methods for Support Vector Machine Speed Optimization

Support vector machine (SVM) is one of the top picks in pattern recognition and classification related tasks. It has been used successfully to classify linearly separable and nonlinearly separable data with high accuracy. However, in terms of classification speed, SVMs are outperformed by many machine learning algorithms, especially, when massive datasets are involved. SVM classification speed scales linearly with number of support vectors, and support vectors increase with increase in dataset size. Hence, SVM classification speed can be enormously reduced if it is trained on a reduced dataset. Instance selection techniques are one of the most effective techniques suitable for minimizing SVM training time. In this study, two instance selection techniques suitable for identifying relevant training instances are proposed. The techniques are evaluated on a dataset containing 4000 emails and results obtained compared to other existing techniques. Result reveals excellent improvement in SVM classification speed

Pengontrolan Penjejak Dinding dengan Batasan Orientasi pada Kursi Roda Robotik

Pada makalah ilmiah ini disajikan desain sistem kontrol penjejak dinding pada kursi roda robotik dengan keterbatasan pada pembacaan sensor. Rangkaian sensor ultrasonik digunakan untuk menentukan jarak dan sudut orientasi dari kursi roda robotik terhadap dinding yang menjadi acuan. Algoritma kontrol diturunkan menggunakan fungsi Lyapunov Barrier untuk menjamin kestabilan asimtotik dari sistem dengan batasan sudut pembacaan sensor ultrasonik. Hasil simulasi dari sistem kontrol memperlihatkan kursi roda robotik dapat bergerak dengan jarak yang diinginkan dari dinding dengan mempertahankan sudut orientasi tidak melebihi batasan pembacaan sensor ultrasonik

Intelligent instance selection techniques for support vector machine speed optimization with application to e-fraud detection.

Doctor of Philosophy in Computer Science. University of KwaZulu-Natal, Durban 2017.Decision-making is a very important aspect of many businesses. There are grievous penalties involved in wrong decisions, including financial loss, damage of company reputation and reduction in company productivity. Hence, it is of dire importance that managers make the right decisions. Machine Learning (ML) simplifies the process of decision making: it helps to discover useful patterns from historical data, which can be used for meaningful decision-making. The ability to make strategic and meaningful decisions is dependent on the reliability of data. Currently, many organizations are overwhelmed with vast amounts of data, and unfortunately, ML algorithms cannot effectively handle large datasets. This thesis therefore proposes seven filter-based and five wrapper-based intelligent instance selection techniques for optimizing the speed and predictive accuracy of ML algorithms, with a particular focus on Support Vector Machine (SVM). Also, this thesis proposes a novel fitness function for instance selection. The primary difference between the filter-based and wrapper-based technique is in their method of selection. The filter-based techniques utilizes the proposed fitness function for selection, while the wrapper-based technique utilizes SVM algorithm for selection. The proposed techniques are obtained by fusing SVM algorithm with the following Nature Inspired algorithms: flower pollination algorithm, social spider algorithm, firefly algorithm, cuckoo search algorithm and bat algorithm. Also, two of the filter-based techniques are boundary detection algorithms, inspired by edge detection in image processing and edge selection in ant colony optimization. Two different sets of experiments were performed in order to evaluate the performance of the proposed techniques (wrapper-based and filter-based). All experiments were performed on four datasets containing three popular e-fraud types: credit card fraud, email spam and phishing email. In addition, experiments were performed on 20 datasets provided by the well-known UCI data repository. The results show that the proposed filter-based techniques excellently improved SVM training speed in 100% (24 out of 24) of the datasets used for evaluation, without significantly affecting SVM classification quality. Moreover, experimental results also show that the wrapper-based techniques consistently improved SVM predictive accuracy in 78% (18 out of 23) of the datasets used for evaluation and simultaneously improved SVM training speed in all cases. Furthermore, two different statistical tests were conducted to further validate the credibility of the results: Freidman’s test and Holm’s post-hoc test. The statistical test results reveal that the proposed filter-based and wrapper-based techniques are significantly faster, compared to standard SVM and some existing instance selection techniques, in all cases. Moreover, statistical test results also reveal that Cuckoo Search Instance Selection Algorithm outperform all the proposed techniques, in terms of speed. Overall, the proposed techniques have proven to be fast and accurate ML-based e-fraud detection techniques, with improved training speed, predictive accuracy and storage reduction. In real life application, such as video surveillance and intrusion detection systems, that require a classifier to be trained very quickly for speedy classification of new target concepts, the filter-based techniques provide the best solutions; while the wrapper-based techniques are better suited for applications, such as email filters, that are very sensitive to slight changes in predictive accuracy

Pengaruh Disiplin Kerja, Stres Kerja Dan Kepuasan Kerja Terhadap Kinerja Karyawan Pada PT. Sardana Indah Berlian Motor

This study aims to examine the impact of discipline,stress and satisfaction on employee performance at PT Sardana Indah Berlian Motor. Respondent as many as 92 employees. This study applies a quantitative approach.  The use of data is questionnaires, interviews and documentation. Data analysis techniques using multiple linear regression análisis. The results obtained that partially and simultaneously work discipline, work stress and job satisfaction have a positive and significant effect on employee performance at PT Sardana Indah Berlian Motor. Keyword:Discipline,Stress,Satisfaction,Performance

Improved techniques for phishing email detection based on random forest and firefly-based support vector machine learning algorithms.

Master of Science in Computer Science. University of KwaZulu-Natal, Durban, 2014.Electronic fraud is one of the major challenges faced by the vast majority of online internet users today. Curbing this menace is not an easy task, primarily because of the rapid rate at which fraudsters change their mode of attack. Many techniques have been proposed in the academic literature to handle e-fraud. Some of them include: blacklist, whitelist, and machine learning (ML) based techniques. Among all these techniques, ML-based techniques have proven to be the most efficient, because of their ability to detect new fraudulent attacks as they appear.There are three commonly perpetrated electronic frauds, namely: email spam, phishing and network intrusion. Among these three, more financial loss has been incurred owing to phishing attacks. This research investigates and reports the use of MLand Nature Inspired technique in the domain of phishing detection, with the foremost objective of developing a dynamic and robust phishing email classifier with improved classification accuracy and reduced processing time.Two approaches to phishing email detection are proposed, and two email classifiers are developed based on the proposed approaches. In the first approach, a random forest algorithm is used to construct decision trees,which are,in turn,used for email classification. The second approach introduced a novel MLmethod that hybridizes firefly algorithm (FFA) and support vector machine (SVM). The hybridized method consists of three major stages: feature extraction phase, hyper-parameter selection phase and email classification phase. In the feature extraction phase, the feature vectors of all the features described in Section 3.6 are extracted and saved in a file for easy access.In the second stage, a novel hyper-parameter search algorithm, developed in this research, is used to generate exponentially growing sequence of paired C and Gamma (γ) values. FFA is then used to optimize the generated SVM hyper-parameters and to also find the best hyper-parameter pair. Finally, in the third phase, SVM is used to carry out the classification. This new approach addresses the problem of hyper-parameter optimization in SVM, and in turn, improves the classification speed and accuracy of SVM. Using two publicly available email datasets, some experiments are performed to evaluate the performance of the two proposed phishing email detection techniques. During the evaluation of each approach, a set of features (well suited for phishing detection) are extracted from the training dataset and used to constructthe classifiers. Thereafter, the trained classifiers are evaluated on the test dataset. The evaluations produced very good results. The RF-based classifier yielded a classification accuracy of 99.70%, a FP rate of 0.06% and a FN rate of 2.50%. Also, the hybridized classifier (known as FFA_SVM) produced a classification accuracy of 99.99%, a FP rate of 0.01% and a FN rate of 0.00%

PENGARUH KUALITAS PELAYANAN DAN PROMOSI TERHADAP KEPUASAN PELANGGAN PADA PT. HORASINDO WISATANUSA MEDAN

Abstract  This research objective is to analyze the effect of service quality and promotion on employees' satisfaction at PT. Horasindo Wisata Nusa Medan. This is survey research. PT. Horasindo Wisatanusa Medan is a company engaged in the service of Tours and Travel in which one of its functions is to support tourism activities and provide ease for society to get tour ant services. In providing its services, the company has complaints from the customers that they often canceled the service. The data analysis used in the research was multiple regression analysis using software SPSS v. 22:00. The value of determination coefficient of (r2) shows that the effect of service quality and promotion was 74.6% and the remaining 25.4% can be explained by other factors outside this research. Service quality has a positive and significant effect on employee performance and service quality and promotion simultaneously affected service quality, as well as competence to handle customers at PT. Horasindo Wisatanusa, Medan. PT. Horasindo Wisatanusa should improve media promotion routinely, and called customers to inform promo provided at PT. Horasindo Tour & Travel. Keywords: Quality of Service, Promotion, Customer Satisfactio

PENGARUH GAYA KEPEMIMPINAN DAN KOMPENSASI FINANSIAL TERHADAP KINERJA KARYAWAN PADA PT ASIA PARAMITA INDAH MEDAN

AbstractThe object of the study is PT. Asia Paramita Indah Medan. The object selection was due to a decrease in the performance of employees in the company. Employee performance is the result of the work carried out by employees in the position that is their responsibility. Leadership style is the nature, habits and personality owned by a boss to deal with problems and handle various jobs. Financial compensation is a result of the benefits (in the form of money) received by employees for their services while working at the company. Financial compensation has an important role to improve employee work. The research used some theories of human resource management related to leadership style, financial compensation and employee performance. The research used a quantitative research approach with quantitative descriptive research types. The research samples were drawn by using saturated sampling techniques. The data collection was performed by interviews, questionnaires and documentation studies. The research data were analyzed by using multiple linear regression analysis, coefficient of determination, simultaneous testing (F-test) and partial testing (t-test). the research population and samples were 80 employees. The result of the study showed that leadership style and financial compensation were partially and simultaneously had a significant effect on employee performance with a coefficient of determination up to 43.9% and the remaining 56.1% were explained by independent, unexamined variables such as leadership, discipline and communication. The calculation showed that F-count> F-table (31,868> 3.11) and the T test showed that T-count> T-table on leadership style variables (7.825> 1.991) and financial compensation variables (2,313> 1,991). Therefore, leadership style and financial compensation have a positive and significant effect on employee performance at PT. Asia Paramita Indah Medan.Keywords: Leadership Style, Financial Compensation Employee Performanc