Fish Eggs Calculation Models Using Morphological Operation

Calculations on group objects are the concern of current researchers, to find optimal detection and calculation solutions. One of them is fish eggs in a group. Fish cultivators need precision in calculations, because currently conventional methods often make errors in calculations. If the calculation is wrong, it will have an impact on production and sales that are not balanced (loss). Small and easily broken fish eggs are grouped and it isdifficult to do manual calculations. The purpose of this study is to test which segmentation method is the most optimal in calculating these grouped fish egg objects and produce precise and fast calculations. The test model was developed from algorithm of morphological operations,watershed and statistical approaches with the same number of samples. The result shows morphological operation is better than the others with 96.67%, watershed 81.28% and the count statistic is 95.62% with an average calculation process speed of 54.5 seconds for morphological operations, watershed 1 minute 55 seconds and statistical approach 58.9 seconds. As a result. morphology gets the most optimal and fast calculation results

PENGARUH KUALITAS LAYANAN INTERNET BANKING BANK MANDIRI TERHADAP KEPUASAN NASABAH BANK MANDIRI DENGAN MENGGUNAKAN METODE WEBQUAL (Studi Kasus Mahasiswa Telkom University)

Pertumbuhan Teknologi Informasi dan Komunikasi yang demikian pesat menjadikan website sebagai bagian yang tidak terpisahkan dari sebuah perusahaan dalam hal layanan bagi pelanggan. Layanan suatu website perlu diukur untuk mengetahui tingkat kepuasan pelanggan. Dalam penelitian ini, kualitas website internet banking Bank Mandiri diukur dengan menggunakan metode WebQual. WebQual merupakan instrumen yang untuk menilai kualitas suatu website Metode penelitian yang digunakan adalah metode deskriptif kuantitatif. Populasi penelitian ini adalah mahasiswa Telkom University dengan pengambilan sampel dengan metode insidental sampling dengan jumlah responden sebanyak 100 responden. Kemudian untuk analisis data digunakan analisis dskriptif dan analisis berganda dengan pengujian hipotesis uji F dan uji t. Tanggapan responden mengenai kualitas layanan internet banking adalah Baik. Hasil uji F menunjukan bahwa kualitas pelayanan secara simultan berpengaruh signifikan terhadap kepuasan nasabah. Hasil uji t menunjukan terdapat 2 variabel yang secara parsial berpengaruh signifikan yaitu variabel information quality dan interaction quality, sedangkan variabel usability tidak berpengaruh signifikan. Nilai koefisien determinasi sebesar 29,6% yang diartikan bahwa besarnya pengaruh kualitas layanan internet banking terhadap kepuasan nasabah adalah sebesar 29,6% sedangkan sisanya sebesar 70,4% dipengaruhi oleh faktor lain yang tidak diteliti dalam penelitian ini. Dari hasil penelitian dapat disimpulkan bahwa secara simultan kualitas layanan internet banking Bank Mandri berpengaruh terhadap kepuasan pelanggan. Sedangkan secara parsial dua dimensi WebQual yaitu information quality dan interaction quaity berpengaruh terhadap kepuasan pelanggan secara signifikan.. Kata kunci : WebQual, kepuasan pelangga

Testing Big Data Applications

Today big data has become the basis of discussion for the organizations. The big task associated with big data stream is coping with its various challenges and performing the appropriate testing for the optimal analysis of the data which may benefit the processing of various activities, especially from a business perspective. Big data term follows the massive volume of data, (might be in units of petabytes or exabytes) exceeding the processing and analytical capacity of the conventional systems and thereby raising the need for analyzing and testing the big data before applications can be put into use. Testing such huge data coming from the various number of sources like the internet, smartphones, audios, videos, media, etc. is a challenge itself. The most favourable solution to test big data follows the automated/programmed approach. This paper outlines the big data characteristics, and various challenges associated with it followed by the approach, strategy, and proposed framework for testing big data applications

Classification of Physiological Signals for Emotion Recognition using IoT

Emotion recognition gains huge popularity now a days. Physiological signals provides an appropriate way to detect human emotion with the help of IoT. In this paper, a novel system is proposed which is capable of determining the emotional status using physiological parameters, including design specification and software implementation of the system. This system may have a vivid use in medicine (especially for emotionally challenged people), smart home etc. Various Physiological parameters to be measured includes, heart rate (HR), galvanic skin response (GSR), skin temperature etc. To construct the proposed system the measured physiological parameters were feed to the neural networks which further classify the data in various emotional states, mainly in anger, happy, sad, joy. This work recognized the correlation between human emotions and change in physiological parameters with respect to their emotion

Aggressive driving behaviour classification using smartphone's accelerometer sensor

Aggressive driving is the most common factor of road accidents, and millions of lives are compromised every year. Early detection of aggressive driving behaviour can reduce the risks of accidents by taking preventive measures. The smartphone's accelerometer sensor data is mostly used for driving behavioural detection. In recent years, many research works have been published concerning to behavioural analysis, but the state of the art shows that still, there is a need for a more reliable prediction system because individually, each method has it's own limitations like accuracy, complexity etc. To overcome these problems, this paper proposes a heterogeneous ensemble technique that uses random forest, artificial neural network and dynamic time wrapping techniques along with weighted voting scheme to obtain the final result. The experimental results show that the weighted voting ensemble technique outperforms to all the individual classifiers with average marginal gain of 20%

Person tracking with non-overlapping multiple cameras

Monitoring and tracking of any target in a surveillance system is an important task. When these targets are human then this problem comes under person identification and tracking. At present, large scale smart video surveillance system is an essential component for any commercial or public campus. Since field of view (FOV) of a camera is limited; for large area monitoring, multiple cameras are needed at different locations. This paper proposes a novel model for tracking a person under multiple non-overlapping cameras. It builds the reference signature of the person at the beginning of the tracking system to match with the upcoming signatures captured by other cameras within the specified area of observation with the help of trained support vector machine (SVM) between two cameras. For experiments, wide area re-identification dataset (WARD) and a real-time scenario have been used with color, shape and texture features for person's re-identification

Email classification via intention-based segmentation

Email is the most popular way of personal and official communication among people and organizations. Due to untrusted virtual environment, email systems may face frequent attacks like malware, spamming, social engineering, etc. Spamming is the most common malicious activity, where unsolicited emails are sent in bulk, and these spam emails can be the source of malware, waste resources, hence degrade the productivity. In spam filter development, the most important challenge is to find the correlation between the nature of spam and the interest of the users because the interests of users are dynamic. This paper proposes a novel dynamic spam filter model that considers the changes in the interests of users with time while handling the spam activities. It uses intention-based segmentation to compare different segments of text documents instead of comparing them as a whole. The proposed spam filter is a multi-tier approach where initially, the email content is divided into segments with the help of part of speech (POS) tagging based on voices and tenses. Further, the segments are clustered using hierarchical clustering and compared using the vector space model. In the third stage, concept drift is detected in the clusters to identify the change in the interest of the user. Later, the classification of ham emails into various categories is done in the last stage. For experiments Enron dataset is used and the obtained results are promising

SISTEM PEMERIKSA KEAMANAN INFORMASI MENGGUNAKAN NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY (NIST) CYBERSECURITY FRAMEWORK

Masalah kemanan informasi dapat mempengaruhi operasional di suatu perusahaan/organisasi. Resiko yang timbul dapat berakibat proses bisnis tidak optimal, kerugian finansial, berkurangnya kepercayaan pelanggan, menurunnya reputasi dan yang paling buruk adalah hancurnya bisnis perusahaan. Untuk itu diperlukan suatu cara untuk memonitor keamanan informasi di perusahaan ini secara periodik. Metode yang bisa digunakan sebagai best practise  adalah National Institute of Standards and Technology (NIST) Cybersecurity Framework. Framework ini menyediakan mekanisme penilaian yang memungkinkan organisasi/perusahaan menentukan kemampuan cybersecurity saat ini, menetapkan sasaran individual, dan membuat rencana untuk memperbaiki dan memelihara program cybersecurity. Dari penelitian ini didapatkan hasil pengujian untuk fungsi Mengenali (Identify) sebesar 16.67%, Melindungi (Protect) sebesar 32.86%, Mendeteksi (Detect) sebesar 25%, Menanggapi (Respond) sebesar 23.33% dan Memulihkan (Recover) sebesar 58.33%. Namun untuk keseluruhan nilai NIST Security Framework yang didapat hanya 27.55%

Design and Implementation of Web-based Church Information Systems (Case Study : HKBP Kebon Jeruk)

HKBP Kebon Jeruk Church has a lot of data consisting of church data, Pastor data, Church server data, family data, marital data, baptismal data, and also about church agenda such as the schedule of activities Church, schedule of church service. The problem in HKBP Kebon Jeruk is that the Data is provided and managed manually, as well as difficulties in finding the necessary information. Therefore, the system needs to be built by the HKBP Kebon Jeruk Church to request church management data.The method used in the HKBP Kebon Jeruk system is the Extreme Programming method, and the analysis used is the PIECES analysis. The result of this research is to build the HKBP Kebon Jeruk system according to the needs of the user

PID controller design for mobile robot using Bat Algorithm with Mutation (BAM)

By definition, a mobile robot is a type of robot that has capability to move in a certain kind of environment and generally used to accomplish certain tasks with some degrees of freedom (DoF). Applications of mobile robots cover both industrial and domestic area. It may help to reduce risk to human being and to the environment. Mobile robot is expected to operate safely where it must stay away from hazards such as obstacles. Therefore, a controller needs to be designed to make the system robust and adaptive. In this study, PID controller is chosen to control a mobile robot. PID is considered as simple yet powerful controller for many kind of applications. In designing PID, user needs to set appropriate controller gain to achieve a desired performance of the control system, in terms of time response and its steady state error. Here, an optimization algorithm called Bat Algorithm with Mutation (BAM) is proposed to optimize the value of PID controller gain for mobile robot. This algorithm is compared with a wellknown optimization algorithm, Particle Swarm Optimization (PSO). The result shows that BAM has better performance compared to PSO in term of overshoot percentage and steady state error. BAM gives 2.29% of overshoot and 2.94% of steady state error. Meanwhile, PSO gives 3.07% of overshoot and 3.72% of steady state error