Dijkstra is a greedy algorithm that gives a choice of several available shortest routes and then provides a solution. The application of Dijkstra's Algorithm in everyday life is very diverse. This study collects research results regarding the application of Dijkstra's Algorithm to solve everyday problems such as the shortest path problem, this mini-review paper can explain the study of Dijkstra's Algorithm for various things, including solving bi-objective shortest routes, multi-objective routes, emergency evacuation, Dijkstra's graph, the connection between LBS features, best route distribution, and fuzzy solution.

Jumlah bencana akibat kebakaran baik yang diakibatkan kelalaian manusia ataupun instalasi listrik yang sudah tidak layak atau gejala alam masih sering terjadi. Posisi lokasi kebakaran yang sulit dijangkau, terlambatnya pemberitahuan kepada petugas pemadam kebakaran, dan trafik lalu lintas yang padat, mengakibatkan rumah atau bagunan tersebut menjadi punah dilalap api. Penelitian ini dimaksudkan untuk merancang alat pendeteksi kebakaran yang dapat mendeteksi gejala awal kebakaran akibat adanya asap, gas, panas/suhu, lalu sistem mengambil keputusan untuk menghubungi kantor pemadam kebakaran via telepon voice over IP atau pun pemilik lokasi kebakaran. Sistem ini berbasis pada mikrokontroler ESP8266 dan juga IFTTT (If this, then that) dari google asisten. Sistem ini memiliki dashboard web untuk dapat mengontrol aktifitas dalam rumah dan dapat dimonitor. Sistem juga dapat mengontrol water pump bila terjadi kebakaran, memonitoring suhu ruangan untuk menghindari panas berlebihan dalam ruangan dengan menghidupkan fan/exhaust untuk mendinginkan ruangan pada saat suhu ruangan diluar batas suhu manusia. Untuk mengantisipasi terjadinya kebakaran, maka dipasang sensor api atau pun gas. Sistem akan mendeteksi adanya api atau gas yang berpotensi menjadi penyebab terjadinya kebakaran. Apabila kebakaran sudah terjadi, maka fan akan mati otomatis untuk menghindari peluasan api karena udara dan water pump akan menyala untuk memadamkan api dengan air. Smartphone petugas kebakaran akan menerima pesan telepon bahwa terjadi kebakaran dirumah tersebut. Hasil pengujian sistem menunjukan semua fungsi dapat berjalan dengan baik. Setiap sensor dan aktuator menjalankan fungsinya serta IFTTT sebagai pengambil keputusan juga berjalan dengan baik. The number of disasters due to fires, whether caused by human negligence or improper electrical installations or natural phenomena, happens a lot. The position and the location of the fire that is difficult to reach, the delay in notification to the firefighters, and heavy traffic, have resulted in the house or building being destroyed by the fire. This study is intended to design a fire detection device that can detect early of fire sign due to smoke, gas, heat, then the system makes a decision to contact the fire department via voice over IP telephone or the owner of the fire location. This system is based on the ESP8266 microcontroller and also IFTTT (If this, then that) from google assistant. This system has a web dashboard to be able to control activities in the house and can be monitored. The system can also control the water pump in the event of a fire, monitor the room temperature to avoid overheating in the room by turning on the fan/exhaust to cool the room when the room temperature is outside the human temperature limit. To anticipate a fire, a fire or gas sensor is installed. The system will detect the presence of fire or gas that has the potential to cause a fire. If a fire has occurred, the fan will turn off automatically to avoid the expansion of the fire because the air and water pump will turn on to extinguish the fire with water. Smartphone firefighters will receive a phone message that there is a fire in the house. The system test results show that all functions can run well. Each sensor and actuator performs its function and IFTTT as a decision maker also works well.

Forensics has become an essential part of the disclosure of criminal evidence. A bioinformatics approach in the form of DNA forensics and digital forensics can be a good combination in disclosing digital-based criminal evidence. This study explains how the role of bioinformatics through the digital approach can be a means of forming new approaches in integration with digital forensics, called cyber-bioinformatics. Despite many hopes and challenges ahead, it does not rule out the possibility of criminal cases related to the privacy of human genomic data, so it proposes a new hypothesis, “cyber-bioinformatics.” The role of cyber-bioinformatics is very central in this regard.

Since Covid-19 was declared a global pandemic because it has spread throughout the world, every effort has been made to help prevent and tackle the transmission of Covid-19, including information technology. Information technology developed to determine the shortest distance for Covid-19 cases around us needs to be developed. This research implements Dijkstra's Algorithm written in the React Native programming language to build a Covid-19 tracking application. The system can display the closest distance with a radius of at least one meter, and the test results can map the nearest radius of 41 meters and the most immediate radius of 147 meters. This system is built for the compatibility of Android OS and iOS applications with React Native programming.

Covid-19 has now spread extremely worldwide. World still fighting against Covid-19, as well as vaccination programs. The problem to get one of the existing vaccines, it is required first to carry out a vaccination eligibility screening test, then usually carried out with traditional form method by the healthcare staff. Seeing the development of an expert system that can be used as an alternative for health workers to help reduce the number of Covid-19 suppression so that it does not spread to health workers, because after all, someone who will vaccinate Covid-19 must be in good health, this is related to the pre-vaccination procedure. We proposed the expert system with forward-chaining method. The result is the dataset (rules collection) of an expert system based on a forward-chaining inference machine for administering all Covid-19 vaccines.