Aplikasi Monitoring Smartlab Menggunakan Algoritma Enigma Berbasis Android (Studi Kasus : Laboratorium Komputer Dasar Stt Pln)

Smartphones based on Android, iOS, or Windows Phone is very fast technology in accessing information and mobile data services, this technology allows us to work anytime and anywhere is not limited by location and time. need fast and accurate information on basic computer lab researchers STT PLN background create an application that serves to monitor the conditions and activities in a computer lab by applying mobile technology at Smart Information Systems Laboratory in the College of Engineering PLN. It is hoped that with the development of these applications can facilitate laboratory users to access data and information and can control the computer lab activities are based on Android. At present the STT PLN elementary computer lab, for security and energy savings have been designed using technology to detect finger print fingerprint and smart cards to control the work of power tools that exist in the computer lab. So the lab assistant was able to turn on and turn off the electrical appliances automatically, the smart card has to work according to the contract of lectures so that students are expected to perform tapping the smart card is otomatais and students are able to turn on the computer and access the computer in accordance with the schedule of his courses, as well as with the lecturer. And on smartlab It can be detected using a personal schedule and access doors can be made of printed reports, and all the activities that have been automated is expected to be monitored by mobile so they invented smartlab monitoring applications in basic computer lab PLN.Metode STT is composed of several stages namely initialization IP and subnet mask, forming connections and wireless network, send data requests to the Arduino to send characters, sends a data request to Arduino by sending a character, receive data from arduino and make a key partner of the algorithm enigma, sending the key pair, the results appear on androi

Klasifikasi Kompetensi Alumni Berdasarkan Masa Tunggu Alumni untuk Mendapatkan Pekerjaaan Menggunakan Metode Agoritma C4.5

Tracer Study is a search for information about alumni that aims to identify how much higher education graduates can move in the world of work according to the relevance of their education. In this study, tracer study data were obtained from a questionnaire distributed to alumni. The data consists of data from the last 5 years, namely 2015 to 2019, which is processed to find out how long the alumni have to wait for a job from the time of graduation based on competency. C4.5 algorithm is used to form a decision tree to see which competencies have the most influence on alumni in order to get a job in a short time. The results of the analysis carried out there are several competencies that most influence the waiting period of alumni to get a job, namely disciplinary education, time management, analytical skills and computer skills. The highest accuracy was found in 2016, which was 82.86%.   &nbsp

Perancangan Aplikasi Pengelolaan Rumah Tangga Laboratorium Komputer STT-PLN

PLN STT campus Department of Information Engineering have 5 computer labs, each of which has a different function so that the needs of households and any inventory each has different needs as well, but will need to be especially household applications required by the all the computer labs are broadly have the same needs: managing demand for goods, equipment and laboratory equipment, household budget until the correspondence. Where at the moment the data needs of households still created and stored using Microsoft Word and Microsoft Excel because of the perceived lack of effective then the author will make the application more household management automatically so as to facilitate and speed up the process of calculation of the household budget, manufacture of correspondence, filing goods and storage of data and information. So it is expected that these applications can help the process of managing the household of computer laboratories in order to more effectively and efficiently

Protokol Routing pada Vanet: Taksonomi dan Analisis Perbandingan antara Dsr, Aodv, dan Tora

VANET yang merupakan bagian dari MANET adalah teknologi yang memungkinkan komunikasi nirkabel antar berbagai kendaraan yang bergerak atau antara kendaraan dengan unit komunikasi yang terdapat di sepanjang jalan. VANET dikembangkan untuk mendukung ITS dalam meningkatkan keselamatandi jalan raya dan efisiensi lalu lntas. Jaringan ad-hoc ini juga dirancang untuk memungkinkan pertukaran pesan-pesan peringatan antar kendaraan untuk meningkatkan keselamatan penumpang dan informasi-informasi lain terkait dengan aplkasi dan layanan VANET. Untuk mewujudkan hal tersebut, ada beberapa hal yang perlu dipertimbangkan supaya VANET dapat beroperasi denganbaik. Hal-hal tersebut antara lain masalah keterbatasan bandwidth, keamanan, skalabilitas, protokol kendali akses media (MAC) dan mekanisme routing. Ada beberapa karakteristik khusus dari VANET yang perlu diperhatikan oleh protokol routing, antara lain : mobilitas node yang tinggi, jumlah dan kepadatana node yang tidak tetap, dan topologi jaringan yang terus berubah. Diperlukan protokol routing tertentu untuk mewujudkan komunikasi yang handal, kontinyu dan tanpa batas antar node pada VANET. Secara garis besar, protokol routing pada VANET dikelompokkan menjadi dua: kelompok protokol yang berdasarkan posisi kendaraan dan kelompok yang berdasar pada topologi jaringan. Tulisan ini akan membahas mengenai protokol routing DSR, AODV, TORA dan menjelaskan bagaimana ketiga protokol reaktif ini menjalankan mekanisme routing pada VANET. Kelebihan dan kekurangan dari ketiga protokol tersebut juga akan dianalisis dengan didukung oleh beberapa hasil simulasi dari penelitian-penelitian yang telah dilakukan sebelumnya

PELATIHAN MS. Office Word dan Excel BAGI PERANGKAT DESA & MASYARAKAT DESA CIARUTEUN ILIR BOGOR

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Aplikasi Monitoring Smartlab Menggunakan Algoritma Enigma Berbasis Android (Studi Kasus : Laboratorium Komputer Dasar Stt Pln)

Smartphones based on Android, iOS, or Windows Phone is very Fast technology in accessing information and mobile data services, this technology allows us to work anytime and anywhere is not limited by location and time. need Fast and accurate information on basic computer lab researchers STT PLN background create an application that serves to monitor the conditions and activities in a computer lab by applying mobile technology at Smart Information Systems Laboratory in the College of Engineering PLN. It is hoped that with the development of these applications can facilitate laboratory users to access data and information and can control the computer lab activities are based on Android. At present the STT PLN elementary computer lab, for security and energy savings have been designed using technology to detect finger print fingerprint and smart cards to control the work of power tools that exist in the computer lab. So the lab assistant was able to turn on and turn off the electrical appliances automatically, the smart card has to work according to the contract of lectures so that students are expected to perform tapping the smart card is otomatais and students are able to turn on the computer and access the computer in accordance with the schedule of his courses, as well as with the lecturer. And on smartlab It can be detected using a personal schedule and access doors can be made of printed reports, and all the activities that have been automated is expected to be monitored by mobile so they invented smartlab monitoring applications in basic computer lab PLN.Metode STT is composed of several stages namely initialization IP and subnet mask, forming connections and wireless network, send data requests to the Arduino to send characters, sends a data request to Arduino by sending a character, receive data from arduino and make a key partner of the algorithm enigma, sending the key pair, the results appear on androi

Perancangan Aplikasi Pengelolaan Rumah Tangga Laboratorium Komputer STT-PLN

PLN STT campus Department of Information Engineering have 5 computer labs, each of which has a different function so that the needs of households and any inventory each has different needs as well, but will need to be especially household applications required by the all the computer labs are broadly have the same needs: managing demand for goods, equipment and laboratory equipment, household budget until the correspondence. Where at the moment the data needs of households still created and stored using Microsoft Word and Microsoft Excel because of the perceived lack of effective then the author will make the application more household management automatically so as to facilitate and speed up the process of calculation of the household budget, manufacture of correspondence, filing goods and storage of data and information. So it is expected that these applications can help the process of managing the household of computer laboratories in order to more effectively and efficiently

The Classification of Relationship between Alumni Competence and Work Using Decision Tree Method

This study discusses the classification of the relationship between personal competence with work on the tracer study data of the PLN Institute of Technology. The results of the data from the alumni survey will be processed using a decision tree method that aims to provide information related to the relationship between personal competencies which have a very close relationship, close enough and not close to the work that the alumni get and become an evaluation material for the campus in the future. Where the decision tree method is one of the data mining classification methods that provides a tree structure that will serve as a decision tree. The tracer study data used from the graduation years of 2015, 2016, 2017, 2018 and 2019 are processed based on the year. And consists of 13 competency attributes and one competency that is used as a label or target. Based on the application of this method each year of graduation has a different level of accuracy based on the state of each data, for tracer study data 2015 graduation year accuracy of 56.03%, 2016 graduation data accuracy of 56.03%, while for tracer data the 2017 graduation year study was 78.90% accuracy, for the 2018 graduation study tracer data the accuracy was 52.94% and for the 2019 graduation tracer study data the accuracy was 40.12%

Klasifikasi Kompetensi Alumni Berdasarkan Masa Tunggu Alumni untuk Mendapatkan Pekerjaaan Menggunakan Metode Agoritma C4.5

Tracer Study is a search for information about alumni that aims to identify how much higher education graduates can move in the world of work according to the relevance of their education. In this study, tracer study data were obtained from a questionnaire distributed to alumni. The data consists of data from the last 5 years, namely 2015 to 2019, which is processed to find out how long the alumni have to wait for a job from the time of graduation based on competency. C4.5 algorithm is used to form a decision tree to see which competencies have the most influence on alumni in order to get a job in a short time. The results of the analysis carried out there are several competencies that most influence the waiting period of alumni to get a job, namely disciplinary education, time management, analytical skills and computer skills. The highest accuracy was found in 2016, which was 82.86%.   &nbsp