This study aims to analyze the performance of symmetrical encryption algorithms between the AES and DES algorithms, and the use of mini PC devices such as Raspberry Pi. It aims to find algorithms that excel in performance. The performance, which is a measure is the time and memory used to encrypt and decrypt with the same key - the method used in research with an experimental approach. Where experimental done on Raspberry PI with PHP programming language, the results of this study indicate that the AES algorithm requires a shorter time in encrypting messages compared to the DES algorithm. The AES algorithm uses a larger memory capacity in encrypting messages compared to the DES algorithm. The AES algorithm is recommended to use because in terms of security AES has a more significant number of keys that is 128 bits while the DES algorithm has a key length of 64 bits or half of the number of keys in the AES Algorithm. The results of the comparison of the two algorithms can be used as a reference where two encryption algorithms are compatible with the applications and devices developed.

The research objective was to develop a learning media support system using chatbot technology that was integrated with the LINE messaging mobile application and content management system (CMS) with homeschooling students and teachers as target users. The renewal of this research is to add access to subject matter features and discussion forum features. These features do not yet exist in the chatbot application system in other studies. Authentication on the chatbot is needed to find out who the user is accessing the chatbot for the material, discussion forum, and work on the problem training and National Examination exercises. E-learning innovation from chatbots is integrated with the LINE and CMS messaging mobile application that contains subject matter, exam practice, discussion forums, and evaluation of student evaluations. This system supports students who have limited time to attend traditional face-to-face classes and have limited access to laptops. The results of this study prove that Chatbot on smartphones can maximize student learning functions, increase student interest and achievement (value).

The performance of the Civil Servants information system in the Indramayu Regency Government is the work done by the employees along with the work system applied. The role of employees as information system personnel is needed to provide the best performance to superiors and customers. Competence is the knowledge and skills needed to support business processes. They represent the basis for creating value in an organization. This study has observed and measured competency factors. Competencies are used to measure the success of organizations and individuals in the field of information technology, namely technical knowledge, work coordination, problem solving and prevention, communication, and service, and accountability. This study aims to determine how strong the influence of education, mastery, position and information technology competencies on the performance of information system actors in Indramayu District Government. Descriptive research method with survey technique, hypothesis testing is done by using path analysis. The result is, simultaneous hypothesis testing with the level of education, mastery and level of position, and information technology competencies affect the effectiveness and efficiency, discipline and work initiatives of information system actors. In the partial examination of formal education does not significantly influence the effectiveness and efficiency of information system factors.

Every day, vehicle accidents occur and many of them might be avoided if the drivers demonstrated excellent driving without mistakes. This paper presents a novel prototype applied in a real transportation system, particularly for buses, to avoid accidents, which may involve numerous victims, and even occasionally cause death. This system consists of a wearable device and embedded system with several sensors connected via Bluetooth, similar to the Internet of Things (IoT). Wearable devices are made to monitor the driver’s heart rate and alert the driver if they are in a state of sleep deprivation to prevent any potential accidents. The embedded system includes a Global Positioning System (GPS), accelerometers, and gyroscopes attached to a Smart Box mounted on the bus. The embedded system alert function will be triggered if an accident occurs and automatically sends the geolocation of the accident to the registered phone number through a message using a mobile phone. The results for all scenarios were significant when measured by an automatic accident trigger via the smart box if the value of measured values in each axis exceeded 583. In conclusion, the implementation of this innovative solution at the system-level was shown to be satisfactory in terms of the safety mechanism used by the nominated drivers.

The information system is one brand for educational institutions to face various challenges from competitors in the same field. The information system is also the main media for consumers to assess and measure the achievements of an educational institution. The purpose of this study was to help the School of Computer Science (STIKOM) Dinamika Bangsa Jambi conduct an audit of the academic information system and information technology governance using the COBIT 5 standard. Data were collected using a questionnaire that refers to the scale. Based on the calculation of capability level, the current capability level of STIKOM Dinamika Bangsa Jambi in managing Academic Information Systems focuses on Evaluate, Direct, and Monitor (EDM) domains. The current capability level generally leads to level 2 managed process with a value of 1.80, which means that IT processes have been carried out, achieved goals, and are well managed. This result is obtained based on the average value of governance practice.

Face recognition has long been a hot topic and challenging research point in areas such as image processing, pattern recognition, and machine vision. The face is a biometric feature with the intrinsic nature of a human. So that the face has self-stability, deep individual differences and can be an ideal basis for verification of an identity. In this research use, Deep Learning Network method uses to perform detection or face recognition. In this study, we present a framework that can be used to detect faces. This research is also able to present a DNN model that is used to study data sources from the data stream in sequence. The most important part of this study is able to adjust the capacity of the model from the simple one. This research uses experimental design method. The first step is a collection of face image data. Then the architecture design starts from the determination of the depth of the network, layout layers, and the selection of layer types that will be used to get the model based on input dataset and label name index.