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All Journal Sistemasi: Jurnal Sistem Informasi AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JITK (Jurnal Ilmu Pengetahuan dan Komputer) IJISTECH (International Journal Of Information System & Technology) Jurnal Mantik Journal of Computer System and Informatics (JoSYC) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Abdimas Bina Bangsa Jurnal Sains Teknologi dan Sistem Informasi Prosiding Snastikom Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Dedy Hartama
STIKOM Tunas Bangsa
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Journal : IJISTECH

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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.
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.
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.
Co-Authors Abdi Rahim Damanik Agus Perdana Windarto Alan Boy Sandy Damanik Asro Pradipta Bahrudi Efendi Damanik Dewi, Rafiqa Fahmi Firzada Febriani Fitri Anggraini Iin Parlina Ika Okta Kirana Indra Gunawan Irfan Sudahri Damanik Jalaluddin J Jalaluddin Jalaluddin M. Safii MARIA BINTANG Mawaddah Anjelita Muhammad Irfani Muhammad Rahmansyah Siregar Muhammad Ridwan Lubis Notryady Purba Renaldi Rudi Handika Saifullah Saifullah Solikhun S Solikhun Solikhun Sumarno Sumarno Sumarno Sumarno Surya Darma Wanto, Anjar Wendi Robiansyah Widodo Saputra Yogi Prayoga Zulaini Masuro Nasution