Application of Visual Design Principles and Motion Graphic in Re-Design Interactive Learning Video

E-learning-based learning has been widely applied in several educational institutions, one of which is Telkom University (Tel-U). Through the Center of e-Learning and Open Education (CeLOE) program established by Tel-U, network-based learning can be enjoyed by students. However, along the way, CeLOE encountered several obstacles, including the very rigid teaching materials that could have an impact on the reduced learning power of students. To solve this, it is necessary to improve the content of the material, especially learning videos by providing designs and animations for lecturer materials which on average contain full text. The approach used is the principle of visual design by utilizing motion graphics as the main aspect of material content with the ultimate goal of making learning videos more interesting and animated. Thus, the material presented can stimulate interest in learning for students at Telkom University.

Utilizing Digital Storytelling Structure for Developing an Electronic Traditional Game Gobak Sodor

Gobak Sodor is a traditional game that came from Indonesia. Gobak Sodor is also known as a different name in Indonesia and Malaysia, such as Panjang tangan in Riau-Sumatra, Asing in Makassar, Galah Asin in West Java, and Galah Panjang in Malaysia. Gobak Sodor is a game that is played in two groups and has a rule that one group must prevent the opponent through the line back to back. However, Indonesia's open area has gradually reduced so that people difficult to play gobak Sodor. The loss of open land for playing Gobak Sodor and game technology advances make children slowly forget the gobak sodor. In the present time, technology is common for people to support their daily life activities. One of technology implementation form is electronic game, where peoples can play without the limitation of time and space. The electronic game also give pleasure and fun as much as conventional game activities. With the form of electronic game, this research develop a game application which implements all of the gobak sodor rules. Where the players can play the gobak sodor using their mobile device and without the trouble to play on a field or open space. Using electronic game for playing Gobak Sodor gives people satisfaction, awareness. In the hope that this will preserves the traditional game Gobak Sodor. The survey found that 80% of people have an interest to play The Gobak Sodor game.

Prototyping Feed-Forward Artificial Neural Network on Spartan 3S1000 FPGA for Blood Type Classification

In this research, a Feed-Forward Artificial Neural Network design was implemented on Xilinx Spartan 3S1000 Field Programable Gate Array using XSA-3S Board and prototyped blood type classification device. This research uses blood sample images as a system input. The system was built using VHSIC Hardware Description Language to describe the feed-forward propagation with a backpropagation neural network algorithm. We use three layers for the feed-forward ANN design with two hidden layers. The hidden layer designed has two neurons. In this study, the accuracy of detection obtained for four-type blood image resolutions results from 86%-92%, respectively.

Usability and User Experience Test on the Muezzin and Khatib Scheduling Mobile Application Using SUS and User Experience Questionnaire (Case Study: Al Abroor Mosque)

One of the Dewan Kemakmuran Masjid (committee to serve public service in a mosque) main task is to provide prayer facilities in a mosque, such as managing schedules for muezzin and imam salat. Most of the time, the plan is executed manually. Moreover, preparing the schedule is not easy. It needs cautious and excessive effort as DKM members should be careful not to make an unbalanced schedule for each muezzin/ khatib. It is also an error-prone process since putting the unavailable person in the schedule slot is possible. To overcome the condition, we build a mobile application for managing schedules for muezzin and imam salat. The application has been tested with usability testing and a user experience questionnaire. The results from both testing tools yield excellent results; the application could implement and comfortably used for managing schedules. From the result, it can be inferred that Al Aboor meets the criteria for a good mobile application and can be developed further.

Modeling and Visualization of Artillery Fire Formation based on Target Coordinates in The Forward Observer Simulator

The Forward Observer (FO) role is vital in military operations, especially in the Medan Artillery unit. FO was in charge of directing artillery fire against the target. In the execution of artillery fire, several types of artillery fire formations are often carried out to hit the target correctly. The formation includes Tama, Tamu, Seka, Seki and Lingkar. In the FO simulator, the artillery fire formation is modeled and visualized in 3D. Modeling and visualization of artillery fire formation can save costs for military operations training in the Medan Artillery unit. In the test results, by entering several parameters, the formula has succeeded in modeling the type of artillery fire according to the type of formation.

Android-Based Geolocation Technology on a Blood Donation System (BDS) Using the Dijkstra Algorithm

Blood transfusion is an activity that is often carried out in order to save human life. The availability of appropriate bloodstock is crucial for use during special medical conditions. Therefore, the blood collection center must ensure availability; therefore, it needs to recruit active blood donors, difficult patients to find blood stocks, which will be discussed in this study. The contribution of this research is to design an information system that can find blood donors in the Bandar Lampung area with geolocation technology and use the Dijkstra algorithm to determine the closest route, with a system developed on the Android platform. The system can recommend donors to patients who need blood according to the patient's qualifications. Results obtained are an android-based mobile application that can search for geolocation-based blood donors using the Dijkstra algorithm, which can map the location of the nearest blood donor based on the patient's location. Based on data obtained from the results of system testing on functionality and usability, the system can map the location of blood donors and provide blood donor recommendations for patients in need. System testing is carried out using the ISO 9126 standard using the usability aspect, which consists of four test characteristics: the understanding aspect, the learning aspect, the ability aspect, and the operability aspect, and the attractiveness aspect.

Implementation of Roll Control on Mini Remotely Operated Vehicle

This paper describes the design and manufacture of an underwater explorer robot. The proposed Mini Remotely Operated Vehicle (ROV) is designed to be controlled remotely using a wireless communication module outside the water. ROV stability is needed to support the operation of ROV when do maneuvering in the water. The design of the ROV is aimed to maintain stability using a PID control system. Moreover, the gain PID values, kP gain, kI gain, and kD gain, must be set to perform roll stability. After performing a fine-tuning of the PID gain values, the experiment result shows that the system can maintain an average error of -1.70 degrees.

Artificial Neural Network Model with PSO as a Learning Method to Predict Movement of the Rupiah Exchange Rate against the US Dollar

The movement of currency exchange rate can be predicted in the next few days, this is used by economic actors to get profit. Artificial Neural Network with the backpropagation learning method is good enough to use for forecasting time series data, it's just that in its application this method was considered to have shortcomings such as a long training time to achieve convergence. The purpose of this research is to form a Multilayer Perceptron Artificial Neural Network model with the Particle Swarm Optimization (PSO) algorithm as a learning method in the case of currency exchange rate prediction. This research produced a model that can predict the movement of the Rupiah exchange rate against the US Dollar, while the model formed was the MLP-PSO model with an error rate of 5.6168 x 10-8, slightly better than the MLP-BP model with an error rate of 6.4683 x 10-8. These results indicated that the PSO algorithm can be used as a learning algorithm in the Multilayer Perceptron Artificial Neural Network.

Study of Internet and Social Media Addiction in Indonesia during Covid-19

Since February 2020, Indonesia was struck by the Covid-19 pandemic. This led to the imposition of Large-scale Social Restrictions. The government issued a policy of working from home, learning from home, and worshiping at home. To carry out their activities from home, people are becoming increasingly dependent on the internet. With the increasing use of the internet during this pandemic, we are conducting a study on whether there is a phenomenon of internet addiction and social media in Indonesia. A survey of 2309 respondents from 31 provinces in Indonesia using Kimberley Young's Internet Addiction Test (IAT) has been conducted. After the data cleaning process to remove redundant data, only data from 2206 respondents were analyzed further with the binary logistic regression method. 25% of respondents were indicated with Internet addiction. High school students and college students tend to have a 1.7% higher risk of addiction. The length of time accessing e-commerce web and social media also increases the risk of internet addiction. YouTube and Instagram are social media applications that tend to pose a risk of addiction to respondents. A critical analysis of the Internet Addiction Test from a Philosophy of Science perspective was conducted. Finally, we formulate recommendations on strategies the government and society could take in dealing with the problem of internet addiction.

A Comparison of The Predictive Ability between Logistic and Gompertz Model on COVID-19 Outbreak

A predictive model can be learned using historical information. Thereafter, information about a running case is combined with a predictive model to estimate the case's remaining flow time. The predictive model is based on data from past events, which can be used to make predictions for current operating situations. For example, the case of coronavirus disease 2019 (COVID-19), which is currently infecting the whole world, including Indonesia, have influenced various aspects, ranging from the educational environment, business, economy, to the companies. Data scientists are urgently needed who can help organizations improve their operational processes. Therefore, this journal discusses the prediction of the peak number of COVID-19 cases in Indonesia, using two prediction models, logistic and Gompertz. The results obtained show that the Gompertz model has higher accuracy than the logistic model, with an accuracy of 99.85%. This journal's results are expected to help organizations estimate the time to rebuild themselves after being affected by COVID-19.