cover
Contact Name
Adyanata Lubis
Contact Email
jmnr@rokania.ac.id
Phone
+628127651902
Journal Mail Official
jmnr@rokania.ac.id
Editorial Address
Jl. Raya Pasir Pengaraian,Km 15 Langkitin, Kec. Rambah Samo. Kab.Rokan Hulu
Location
Kab. rokan hulu,
Riau
INDONESIA
JOURNAL OF ICT APLICATIONS AND SYSTEM
Published by STKIP Rokania
ISSN : 28301404     EISSN : 2830098X     DOI : https://doi.org/10.56313/jictas
The Journal of ICT Applications System is a scientific journal that presents original articles on computer science research. This journal is a means of publication and a place to share research and development work in the field of computers. Loading of articles in this journal is done through submit. Complete information for article loading and article writing instructions are available in each issue. Articles submitted will go through a selection process for bestari partners and/or editors. Journal of ICTAplication System is published 2 times a year, in June and December Journal of ICTAplication System Registered at PDII LIPI with Print ISSN number 2830-1404 and Online ISSN 2830-098X For practitioners, academics, teachers and students in the field of computer science who want articles on research results and ideas to be published in this journal via submit
Articles 3 Documents
Search results for , issue "Vol 1 No 1 (2022): Journal of ICT Aplications and System" : 3 Documents clear
Kajian Literatur Multi Layer Perceptron Seberapa Baik Performa Algoritma Ini Pardede, Doughlas; Hayadi, B.Herawan; Iskandar
Journal of ICT Applications System Vol 1 No 1 (2022): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (306.323 KB) | DOI: 10.56313/jictas.v1i1.127

Abstract

Multi Layer Perceptron (MLP), one of the deep learning algorithms, has been widely used in classification problem research because it has advantages over other conventional classification methods. This study takes 15 articles that have been published in research journals regarding the application of the multi-layer perceptron algorithm to prediction and classification problems. From the results of the analysis carried out, the results show that the lowest performance value of this algorithm is 62.89%, the highest performance value of this algorithm is 100% and the average performance value of this algorithm is 91.98%. From these values, it can be concluded that the multi layer perceptron algorithm is very good and feasible to be used in solving prediction and classification problems
Penerapan Metode Forward Chaining Pada Sakit Gusi Handayani, Meli; Hayadi, B.Herawan; Lubis, Adyanata
Journal of ICT Applications System Vol 1 No 1 (2022): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.79 KB) | DOI: 10.56313/jictas.v1i1.128

Abstract

Sampai saat ini, perkembangan teknologi informasi telah merambah ke berbagai sektor termasuk di sektor kesehatan yang mampu membantu dalam mendiagnosa penyakit melalui gejala yang diberikan serta dapat memberikan solusi penanganan penyakit. Salah satu penyakit yang dapat dilakukan diagnosa dengan adanya perkembangan teknologi komputer adalah penyakit gusi. Penyakit gusi adalah penyakit infeksi yang menyerang pada jaringan di sekitar gigi. Kondisi ini merupakan penyebab utama dari gigi yang lepas pada orang dewasa. Perawatan gigi merupakan salah satu usaha penjagaan untuk mencegah kerusakan gigi dan penyakit gusi. Penyakit gusi dapat menyerang siapa saja baik menyerang bayi, balita, remaja bahkan menyerang orang dewasa. Menurut jurnal penelitian dari Mubasyiroh, dan Andayasari (2017:141) berpendapat bahwa Penyakit gigi dapat berupa kerusakan gigi (karies) dan penyakit gusi. Penyakit gigi dan mulut (termasuk karies dan penyakit periodontal) merupakan masalah yang cukup tinggi yang dikeluhkan oleh masyarakat. Adapun cabang ilmu komputer yang dapat melakukan diagnosa untuk mengetahui penyakit gusi adalah sistem pakar.Berdasarkan hasil pembahasan diatas, maka didapatkan jawaban B1, B2, B3 sampai dengan B9 gejala penyakit berdasarkan pilihan pertanyaan yang dipilih, itu menandakan, bahwa sistem pakar dengan metode forward chaining dapat mengatasi penyakit gusi dengan tingkat kepercayaan 89%
Analisis Optimasi Algoritma Backpropagation Momentum Dalam Memprediksi Jenis Tingkat Kejahatan Di Kecamatan Tambusai Utara Yanto, Budi; Hendri; almadison; Hutagaol, Ramses; Rahman, Ripatullah
Journal of ICT Applications System Vol 1 No 1 (2022): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (591.429 KB) | DOI: 10.56313/jictas.v1i1.165

Abstract

Crime is conduct that disobeys the law and contravenes social norms in a way that society finds objectionable. There is no system that can forecast the kind and quantity of crimes that will happen in the future as a guide in the process of preventing crime, according to the North Tambusai Police. However, the public service process in the form of complaints has been done digitally. Backpropagation is an iterative method that works well even with complex and convoluted data. Backpropagation is an artificial neural network with several levels (multi-layer). Data processing is done on the types and numbers of crimes that took place in North Tambusai District between 2015 and 2020. The first step in the data processing procedure is to normalize the data and choose the network training parameters. Crime data and levels were used in the artificial neural network research, which used a 5-5-1 design. The test results reveal that the average prediction accuracy rate is 92.66%, with the greatest prediction accuracy rate being 99.6% and the lowest forecast accuracy rate being 90.01 percent. Theft had the highest weighting (Curat) of crimes the next year with 15 cases, while fraud, crime, and extortion/threats each had the lowest weighting (1 case). The prediction findings exhibit a sufficiently high level of accuracy to serve as a basis for evaluation.

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