Article Per Year (5 Year)
p-Index From 2020 - 2025
0.778
P-Index
This Author published in this journals
All Journal Techno Nusa Mandiri : Journal of Computing and Information Technology Journal of Information System, Applied, Management, Accounting and Research INTI Nusa Mandiri KLIK: Kajian Ilmiah Informatika dan Komputer
Agung Fazriansyah
Universitas Bina Sarana Informatika
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
ANIMASI INTERAKTIF PEMBELAJARAN SHALAT MENGGUNAKAN METODE MULTIMEDIA DEVELOPMENT LIFE CYCLE PADA RA AT-TAUFIQ CIKARANG Yulihani Yulihani; Siti Masturoh; Agung Fazriansyah; Ahmad Hafidzul Kahfi
INTI Nusa Mandiri Vol 14 No 2 (2020): INTI Periode Februari 2020
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v14i2.1106

Abstract

Abstract— Education is one of the main foundations in shaping one's personality. Learning to pray must be instilled in children from an early age. Prayer is a weapon of believers, a pillar of religion, light in the sky and on earth. Prayers can prevent vile and morbid deeds. Prayers can be judged if they fulfill all the conditions and pillars. The obligation to perform prayer as well as by carrying out other obligations according to the Islamic Shari'ah. This research was conducted using the Adobe Flash application program, using the method of developing Multimedia Development Life Cycle (MDLC) software, the data collection method used in this study were Observation, Interview, and Library methods. From the results of this study, obtained an Interactive Animation of Five Times Prayer Learning using Adobe Flash CS6 as a learning vehicle for students and facilitating RA Ataufiq students at Cikarang in obtaining material information, especially for prayer learning.
ANALYSIS OF NEURAL NETWORK CLASSIFICATION ALGORITHM TO KNOW THE SUCCESS LEVEL OF IMMUNOTHERAPY Agung Fazriansyah; Mochammad Abdul Azis; Yudhistira Yudhistira
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1365.984 KB) | DOI: 10.33480/techno.v17i1.1089

Abstract

Cancer is a disease that is feared by humans at this stage, the genetic term of most diseases that have the characteristics of abnormal cell growth and beyond the normal cell limits so that they can attack cells that cover and are able to spread to other organs. For cancer recovery therapy is immunization therapy. Of course in this alternative treatment still needs to be done research to determine the level of success with existing conditions and parameters. Increasingly sophisticated, developing technology that helps human work. The neural network algorithm is used to analyze large datasets, the purpose of this study is to find the accuracy and immunotherapy methods of the dataset using a neural network learning machine with 200 data training cycles, 0.9 momentum and 0.01 learning levels that produce quite high accuracy 80 % and AUC value of 0.738
Deep learning untuk pendeteksian penyakit kanker payudara dengan optimasi Adam Irmawati Irmawati; Yuris Alkhalifi; Agung Fazriansyah; Mohammad Syamsul Azis; Kudiantoro Widianto
JISAMAR (Journal of Information System, Applied, Management, Accounting and Research) Vol 7 No 1 (2023): JISAMAR : February 2023
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v7i1.1015

Abstract

Breast cancer is the second leading cause of death in female patients in the world. Breast cancer has caused death in more than 100 countries. Early diagnosis of breast cancer patients is important to reduce the possibility of death. Researchers focus on accurate breast cancer detection, automated diagnostic methods and breast cancer diagnosis. This paper proposes Adam's optimization for Deep Learning Algorithm to classify breast cancer detection. This study aims to overcome the problem of data instability and overfitting, as well as update network weights on deep learning training data. In this study, the authors conducted experiments with a combination of three hidden layers and learning speed to improve classification accuracy. The experiment used the breast cancer data set obtained from the UCI Study: the WBCD data set (Original) while the experimental results showed that the proposed scheme achieved 96.3% accuracy for classifying breast cancer.
Perancangan Program Pembayaran Administrasi Sekolah Berbasis Website Menggunakan Metode Waterfall Hasan Muhamad; Ahmad Hafidzul Kahfi; Agung Fazriansyah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.801

Abstract

Payment of school administration fees is still problematic, including manual data collection and processing of payment information. Recorded reports still use ledgers, making work less efficient, and a lot of time and energy is wasted searching for student data and archiving it by committee staff. In the current technological era, there is a need to renew the use of technology in education to help manage school finances so that data collection and processing of payment information becomes effective and efficient. This study describes the design of a website-based school administration payment program. This design is intended to assist committee staff in recording school administration payments. The research method used is the waterfall-type software development method. In database design using Entity Relationship Diagram and Logical Record Structure, while for making applications using the PHP programming language. With this program, the administrative payment process is better, easier, and faster
Co-Authors Ahmad Hafidzul Kahfi Hasan Muhamad Irmawati Irmawati Kudiantoro Widianto, Kudiantoro Mochammad Abdul Azis Mohammad Syamsul Azis Siti Masturoh Yudhistira Yudhistira Yulihani Yulihani Yuris Alkhalifi