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Prototype Alat Pengamanan Pintu dengan Menggunakan Sensor Sidik Jari Berbasis Arduino Mega2560 Rudi Handika; Dedy Hartama; Ika Okta Kirana; M. Safii; Iin Parlina
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 1 No. 6 (2021): Juni 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The door is the most important and important part of a room to pay attention to its safety compared to other parts because it is from the door that everyone will enter or leave. This study aims to build a door security device using a Fingerprint sensor based on Arduino Mega 256. The door that will be given a security device is the door in classes at STIKOM Tunas Bangsa Pematangsiantar. This tool can be used as a security control system at the classroom door, users do not need to use manual security such as keys, and this tool is also equipped with an alarm as a marker when the Fingerprint sensor is accessed by someone who is not the owner, this alarm will sound. This system consists of hardware and Software. The hardware consists of an Arduino Uno, Fingerprint sensor, buzzer, Selenoid door, LCD and then the Software on this system uses the Arduino IDE program. This system runs if the Fingerprint sensor detects a finger from the user, the solenoid as a door lock will open. Otherwise, if the sensor does not see a finger from the user, the solenoid as a door lock will not open, and an alarm will sound. This door safety device can effectively be used as security on classroom doors and other rooms such as leadership rooms, education rooms and staff rooms
Model of emergence evacuation route planning with contra flow and zone scheduling in disaster evacuation Dedy Hartama; Herman Mawengkang; Muhammad Zarlis; Rahmad Widia Sembiring
Computer Science and Information Technologies Vol 2, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v2i1.p1-10

Abstract

Evacuation is characterized by rapid movement of people in unsafe locations or disaster sites to safer locations. The traffic management strategy for commonly used evacuations is the use of Shoulder-Lane, contra-flowing traffic and gradual evacuation. Contra-flow has been commonly used in traffic management by changing traffic lanes during peak hours. To implement the contra-flow operation, there are two main problems that must be decided, namely Optimal contra-flow lane configuration problem (OCLCP) and optimal contra-flow scheduling. Within the OCSP there are two approaches that can be used: zone scheduling and flow scheduling. Problem of contra-flow and zone scheduling problem is basically an Emergence evacuation route planning (EERP) issue. This research will discuss EERP with contra-flow and zone scheduling which can guarantee the movement of people in disaster area to safe area in emergency situation.
Analisa Visualisasi Data Akademik Menggunakan Tableau Big Data Dedy Hartama
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 3 (2018): Edisi Juli
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v3i0.65

Abstract

This research explains the benefits of data analysis by visualizing Big data in performing optimization in the academic management environment. The data used is academic information system database that related with student status. In this study the authors use Tableau tools to perform data analysis based on the number of students worksheet, student status, student name table and generate student dashboard data. The results of the analysis obtained by using visualization in bemtuk management graph is very fast and optimize data processing so mengatahui the development of academic database situation.
Analisa Visualisasi Data Akademik Menggunakan Tableau Big Data Dedy Hartama
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 3 (2018): Edisi Juli
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (903.09 KB) | DOI: 10.30645/jurasik.v3i0.65

Abstract

This research explains the benefits of data analysis by visualizing Big data in performing optimization in the academic management environment. The data used is academic information system database that related with student status. In this study the authors use Tableau tools to perform data analysis based on the number of students worksheet, student status, student name table and generate student dashboard data. The results of the analysis obtained by using visualization in bemtuk management graph is very fast and optimize data processing so mengatahui the development of academic database situation.
The Application of Data Mining in Determining Timely Graduation Using the C45 Algorithm Asro Pradipta; Dedy Hartama; Anjar Wanto; Saifullah Saifullah; Jalaluddin Jalaluddin
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v3i1.30

Abstract

Graduating on time is one element of higher education accreditation assessment. In the Strata 1 level, students are declared to graduate on time if they can complete their studies <= eight semesters or four years. BAN-PT sets a timely graduation standard of >= 50%. If the standard is not met, it will reduce the value of accreditation. These problems encourage the Universitas Simalungun Pematangsiantar to conduct evaluations and strategic steps in an effort to increase student graduation rates so that the targets of BAN-PT can be achieved. For this reason it is necessary to know in advance the pattern of students who tend not to graduate on time. In this study, C4.5 Algorithm is proposed to predict student graduation. This algorithm will process student profile datasets totaling 150 data. This dataset has a graduation status label. The value of the label is categorical, that is, right and late. The features or attributes used, namely the name of the student, gender, student status, GPA. The results of the C4.5 algorithm are in the form of a decision tree model that is very easy to analyze. In fact, even by ordinary people. This model will map the patterns of students who have the potential to graduate on time and late.
Pelatihan Pemanfaatan Mendeley Desktop Sebagai Program Istimewa Untuk Akademisi Dalam Membuat Citasi Karya Ilmiah Agus Perdana Windarto; Dedy Hartama; Anjar Wanto; Iin Parlina
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 2, No 2 (2018): Agustus
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (663.339 KB) | DOI: 10.30651/aks.v2i2.1319

Abstract

Desktop mendeley application is actually an application intended to facilitate the creation of citations and a list of libraries commonly used by the authors, so the authors will be pressed error in making the bibliography and facilitate in obtaining the writings to be cited. In addition to creating scientific papers, this application can also be used to manage the files of online journal articles that are the output of a scientific work. Furthermore, participants can utilize this application for the purpose of making a bibliography or collection of abstracts of certain fields of journal articles subscribed. Training activities undertaken in Community Service activities show that participants have a material understanding and the potential to make refernsi managers better and maximum by utilizing mendeley desktop applications.
Evacuation Planning for Disaster Management by Using The Relaxation Based Algorithm and Route Choice Model Dedy Hartama; Agus Perdana Windarto; Anjar Wanto
IJISTECH (International Journal of Information System and Technology) Vol 2, No 1 (2018): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (236.102 KB) | DOI: 10.30645/ijistech.v2i1.14

Abstract

Research in the field of disaster management is done by utilizing information and communication technology. Where disaster management is discussed is about evacuation planning issues. The evacuation stage is a very crucial stage in the disaster evacuation process. There have been many methods and algorithms submitted for the evacuation planning process, but no one has directly addressed evacuation planning on dynamic issues concerning time-varying and volume-dependent. This research will use the Relaxation-Based Algorithm combined with the Route Choice Model to produce evacuation models that can be applied to dynamic issues related to time-varying and volume-dependent because some types of disaster will result in damage as time and evacuation paths are volume-dependent so as to adjust to the change in the number of people evacuated. Disaster data that will be used in this research is sourced from Disaster Information Management System sourced from DesInventar. The results of this study are expected to produce an evacuation planning model that can be applied to dynamic problems that take into account the time-varying and volume-dependent aspects.
Evacuation Planning for Disaster Management by Using The Relaxation Based Algorithm and Route Choice Model Dedy Hartama; Agus Perdana Windarto; Anjar Wanto
IJISTECH (International Journal of Information System and Technology) Vol 2, No 1 (2018): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v2i1.14

Abstract

Research in the field of disaster management is done by utilizing information and communication technology. Where disaster management is discussed is about evacuation planning issues. The evacuation stage is a very crucial stage in the disaster evacuation process. There have been many methods and algorithms submitted for the evacuation planning process, but no one has directly addressed evacuation planning on dynamic issues concerning time-varying and volume-dependent. This research will use the Relaxation-Based Algorithm combined with the Route Choice Model to produce evacuation models that can be applied to dynamic issues related to time-varying and volume-dependent because some types of disaster will result in damage as time and evacuation paths are volume-dependent so as to adjust to the change in the number of people evacuated. Disaster data that will be used in this research is sourced from Disaster Information Management System sourced from DesInventar. The results of this study are expected to produce an evacuation planning model that can be applied to dynamic problems that take into account the time-varying and volume-dependent aspects.
Prediction of Mortlity Rate in Indonesia due to Covid-19 Using the Naïve Bayes Algorithm Abdi Rahim Damanik; Dedy Hartama; Irfan Sudahri Damanik
Sistemasi: Jurnal Sistem Informasi Vol 11, No 1 (2022): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (738.977 KB) | DOI: 10.32520/stmsi.v11i1.1519

Abstract

One of the functions of this research is to obtain the latest information regarding the level of accuracy and death rates due to the Covid-19 pandemic. One of the tasks of planning a response to a pandemic is to access data related to the number of deaths due to Covid-19. The research that the author is carrying out will predict the death rate due to the COVID-19 pandemic in Indonesia. This study collects all data sourced from the website address https://sinta.ristekbrin.go.id/covid/datasets. By using Indonesia's death rate data due to covid-19 from March 2020 to July 2021. The calculation process and prediction workflow will use the Naïve Bayes Algorithm to be able to measure accuracy and predict the death rate due to the coronavirus in 2022. Prediction testing data figures with a total of 20 the area is in the highest class with a death rate of 120,568 cases obtained based on the calculation of the Naive Bayes algorithm, for an accuracy performance of 100% by testing using Rapidminer tools. It is hoped that the results of this prediction can be used by the government to overcome and set plans for good improvements to the community during the coronavirus pandemic.
Increasing Prediction Accuracy with the Backpropagation Algorithm (Case Study: Pematangsiantar City Rainfall) Yogi Prayoga; Dedy Hartama; Jalaluddin Jalaluddin; Sumarno Sumarno; Zulaini Masuro Nasution
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v3i1.27

Abstract

The more advanced science and technology from various disciplines, currently rainfall can be predicted by carrying out various empirical approaches, one of which is by using Artificial Neural Networks (ANN). This study aims to apply ANN with backpropogation algorithm in predicting rainfall. The research data used is BPS data of the transfer city. The results of the study state that of the 6 models (4-5-1, 4-10-1, 4-25-1, 4-5-10-1, 4-5-25-1 and 4-5-50-1) architecture that was trained and tested using Matlab 6.1 application software, the results showed that the 4-5-25-1 architectural model was the best model for making predictions with 75% truth accuracy, Training MSE 0.001004582, Testing MSE 0.021882712 and Epoch 59,076 . It is expected that research can provide input to the government, especially BMKG Pematangsiantar city in predicting Rainfall based on computer science so as to improve the quality of services in the fields of Meteorology, Climatology, Air Quality and Geophysics in accordance with applicable laws and regulations.