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IJISTECH (International Journal Of Information System & Technology)
ISSN : 25807250     EISSN : -     DOI : -
Core Subject : Science,
IJISTECH (International Journal Of Information System & Technology) is published with both online and print versions. The journal covers the frontier issues in the computer science and their applications in business, industry and other subjects. The computer science is a branch of engineering science that studies computable processes and structures. It contains theories for understanding computing systems and methods; computational algorithms and tools; methodologies for testing of concepts. The subjects covered by the journal include artificial intelligence, bioinformatics, computational statistics, database, data mining, financial engineering, hardware systems, imaging engineering, internet computing, networking, scientific computing, software engineering, and their applications etc.
Arjuna Subject : -
Articles 33 Documents
Analysis of Artificial Neural Network Accuracy Using Backpropagation Algorithm In Predicting Process (Forecasting) Siregar, Sandy Putra; Wanto, Anjar
IJISTECH (International Journal Of Information System & Technology) Vol 1, No 1 (2017): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v1i1.4

Abstract

Artificial Neural Networks are a computational paradigm formed based on the neural structure of intelligent organisms to gain better knowledge. Artificial neural networks are often used for various computing purposes. One of them is for prediction (forecasting) data. The type of artificial neural network that is often used for prediction is the artificial neural network backpropagation because the backpropagation algorithm is able to learn from previous data and recognize the data pattern. So from this pattern backpropagation able to analyze and predict what will happen in the future. In this study, the data to be predicted is Human Development Index data from 2011 to 2015. Data sourced from the Central Bureau of Statistics of North Sumatra. This research uses 5 architectural models: 3-8-1, 3-18-1, 3-28-1, 3-16-1 and 3-48-1. From the 5 models of this architecture, the best accuracy is obtained from the architectural model 3-48-1 with 100% accuracy rate, with the epoch of 5480 iterations and MSE 0.0006386600 with error level 0.001 to 0.05. Thus, backpropagation algorithm using 3-48-1 model is good enough when used for data prediction.
Implementation of Backpropagation Artificial Neural Networks to Predict Palm Oil Price Fresh Fruit Bunches Ismanto, Edi; Effendi, Noverta; Cynthia, Eka Pandu
IJISTECH (International Journal Of Information System & 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.v2i1.17

Abstract

Riau Province is one of the regions known for its plantation products, especially in the oil palm sector, so that Riau Province and regional districts focus on oil palm plants as the main commodity of plantations in Riau. Based on data from the Central Bureau of Statistics (BPS) of Riau Province, the annual production of oil palm plantations, especially smallholder plantations in Riau province has always increased. So is the demand for world CPO. But sometimes the selling price of oil palm fresh fruit bunches (FFB) for smallholder plantations always changes due to many influential factors. With the Artificial Neural Network approach, the Backpropagation algorithm we conduct training and testing of the time series variables that affect the data, namely data on the area of oil palm plantations in Riau Province; Total palm oil production in Riau Province; Palm Oil Productivity in Riau Province; Palm Oil Exports in Riau Province and Average World CPO Prices. Then price predictions will be made in the future. Based on the results of the training and testing, the best Artificial Neural Network (ANN) architecture model was obtained with 9 input layers, 5 hidden layers and 1 output layer. The output of RMSE 0000699 error value and accuracy percentage is 99.97% so that it can make price predictions according to the given target value.
ANN: Model of Back-Propagation Architecture on the Logs Production by Type of Wood Hasan Siregar, Muhammad Noor
IJISTECH (International Journal Of Information System & Technology) Vol 1, No 2 (2018): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v1i2.12

Abstract

Indonesia is rich in forest products. The production forest is a forest area that can be utilized for the community, such as logs, rattan, and some forest plants that have high economic value. This research aims to make the best architectural model by using artificial neural network. The method used is backpropagation algorithm. With this model it will continue to predict the output of logs. Data are sourced from BPS-Statistics Indonesia. Based on the results of research results of logs production using backpropogation method, obtained the result of 3 model architecture (18-18-1, 18-25-1 and 18-18-25- 1) that model of architecture 18- 25-1 is the best model with 72% accuracy, MSE: 0.0221670942 and epochs: 660.
Use of Binary Sigmoid Function And Linear Identity In Artificial Neural Networks For Forecasting Population Density Wanto, Anjar; Windarto, Agus Perdana; Hartama, Dedy; Parlina, Iin
IJISTECH (International Journal Of Information System & Technology) Vol 1, No 1 (2017): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v1i1.6

Abstract

Artificial Neural Network (ANN) is often used to solve forecasting cases. As in this study. The artificial neural network used is with backpropagation algorithm. The study focused on cases concerning overcrowding forecasting based District in Simalungun in Indonesia in 2010-2015. The data source comes from the Central Bureau of Statistics of Simalungun Regency. The population density forecasting its future will be processed using backpropagation algorithm focused on binary sigmoid function (logsig) and a linear function of identity (purelin) with 5 network architecture model used the 3-5-1, 3-10-1, 3-5 -10-1, 3-5-15-1 and 3-10-15-1. Results from 5 to architectural models using Neural Networks Backpropagation with binary sigmoid function and identity functions vary greatly, but the best is 3-5-1 models with an accuracy of 94%, MSE, and the epoch 0.0025448 6843 iterations. Thus, the use of binary sigmoid activation function (logsig) and the identity function (purelin) on Backpropagation Neural Networks for forecasting the population density is very good, as evidenced by the high accuracy results achieved.
The Authenticity of Image using Hash MD5 and Steganography Least Significant Bit Khairina, Nurul; Harahap, Muhammad Khoiruddin; Lubis, Juanda Hakim
IJISTECH (International Journal Of Information System & 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.v2i1.13

Abstract

A creation can be considered as belonging to someone if they have a valid proof. An original creation that have been changed for certain purposes will definitely eliminate proof of ownership of the creation. A hash function is one method used to test the authenticity of data, while steganography is one method used to maintain the security of confidential data from outside parties. In this study, the Hash MD5 method will be combined with the Least Significant Bit method to test the authenticity of an image. The purpose of testing the authenticity is to find out the truth of ownership of a creation, in this case, we are testing the image. The results of this test are the status of an image that will be declared valid or invalid. Measurement of validity depends on whether there is a similarity between the value of the Hash that has been implanted and the value of the Hash obtained during the test. If the tested image has the same Hash value, then the image will be declared valid, but instead ai image is declared invalid if the image has been modified or ownership status has been changed. From the result of testing the authenticity with several images, it can prove that the combination of the Hash MD5 method with LSB has a good level of security and suitable to authenticity testing.
The Design of The TU Service Project Monitoring System in PT. GMF Aeroasia Tbk Ramadhani, Erika; Irawan, Handika
IJISTECH (International Journal Of Information System & Technology) Vol 2, No 2 (2019): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v2i2.19

Abstract

To unit is one of the units in the GMF in the Information & Communication Technology division, one unit is the TOB has a Self Development Application (SDA) task. At present many requests for procurement of goods are submitted to the TU service. This is certainly very influential on TU services that become less optimal and irregular. So a system design was made to monitor the TU Service project. The research method is carried out by analyzing business requirements and business cases. After analyzing the two documents, then make a blueprint containing the system description starting from the explanation of each module or feature and appearance of the system. Then make the interactive prototype as a system simulation. After going through a number of these steps, a monitoring system for the Dinas TU project was developed which could be utilized by the TU Service in project management.
Implementation of Min Max Algorithm as Intelligent Agent on Card Battle Game Permana, Silvester Dian Handy
IJISTECH (International Journal Of Information System & Technology) Vol 2, No 2 (2019): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v2i2.20

Abstract

Information technology brings transformation from the physical world into the digital world. This transformation developed in various fields, especially games. In the past, games that are involving physical objects such as chess, cards, dominoes, and mahjong are popular for the publics. Card battle game is a game that pits strength between 2 cards. The game must have 2 players who will compete. However, if a player wants to practice before the match or wants to play alone, he needs Non Player Character (NPC). The NPC will be the opponent in card battle games. In order for NPCs to be able to fight players, a special algorithm is needed to make the NPCs compete with players. The algorithm that can be implemented into the NPC is the Min Max Algorithm. This algorithm is a responsive algorithm which can count every step of the player. The results of this study are expected to provide suitable opponents for players who want to practice or compete in Card Battle Game on their own.
Classification Analysis Using C4.5 Algorithm To Predict The Level of Graduation of Nurul Falah Pekanbaru High School Students Wiza, Fana; Febriadi, Bayu
IJISTECH (International Journal Of Information System & Technology) Vol 2, No 2 (2019): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v2i2.21

Abstract

School as one of the processes for implementing formal education is required to carry out the learning process optimally to produce quality students. Regarding the research process carried out to predict the graduation rate of SMA Nurul Falah students by using the decision tree method. The data used in this study are student data using the criteria for student names, majors, average report cards from semester one (I), two (II), three (III), four (IV), five (V), and the average value of the National Standard School Examination (USBN). The data is then managed using Rapidminer 5.3 software to make it easier to predict student graduation rates. The application of data mining is used to predict the graduation rate by using the decision tree method and C4.5 algorithm as a supporter as well as to find out information on the graduation rate of Nurul Falah High School students. This study aims to predict student graduation rates in order to get useful information and the school can make policies in the coming year.
E-Commerce Design for Palembang Home Tailors Salamah, Irma; Ciksadan, Ciksadan; Melyani, Riska
IJISTECH (International Journal Of Information System & Technology) Vol 2, No 2 (2019): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v2i2.22

Abstract

Home tailors are SMEs that are business opportunities that are usually chosen by housewives because, being a home tailor can be a solution for housewives to keep earning even though they are at home. The problems faced are in marketing and promoting home tailoring services because usually the target customers are only the surrounding environment, therefore innovation in promotion strategies is needed, the use of modern technology such as E-Commerce can be a strategy in business, so that it can be known to the wider community. Responsive Web-based E-Commerce design for ordering and purchasing information systems in increasing the income of home-tailor SMEs, to design this information system The programming language that will be used is PHP, and MySql as a database.
Model Combination of Activation Functions in Neural Network Algorithms (Case: Retail State Sukuk by Group) Siregar, Muhammad Noor Hasan
IJISTECH (International Journal Of Information System & Technology) Vol 2, No 2 (2019): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v2i2.23

Abstract

This study aims to maximize the activation function used in backpropogation networks in finding the best architectural model. The case study used is the sale of state retail sukuk based on professional groups. The combination of activation functions used for training and testing is tansig-tansig, tansig-purelin and tansig logsig. The architectural model used is the architectural model 6-2-1 and 6-5-1. The evaluation parameters used are epoch, MSE training, MSE testing and accuracy level of truth. Data processing is assisted by using Matlab software. The results showed that the tansig-logsig activation function had more stable results than tansig-tansig and tansig-purelin.

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