cover
Contact Name
Agus Perdana Windarto
Contact Email
agus.perdana@amiktunasbangsa.ac.id
Phone
+6282273233495
Journal Mail Official
ijistech@gmail.com
Editorial Address
Jalan Sudirman Blok A No. 1/2/3, Siantar Barat Kota Pematang Siantar, Sumatera Utara Kode Pos: 21127, Telepon: (0622) 22431
Location
Kota pematangsiantar,
Sumatera utara
INDONESIA
IJISTECH
ISSN : -     EISSN : 25807250     DOI : https://doi.org/10.30645/ijistech
IJISTECH (International Journal of Information System & Technology) has changed the number of publications to six times a year from volume 5, number 1, 2021 (June, August, October, December, February, and April) and has made modifications to administrative data on the URL LIPI Page: http://u.lipi.go.id/1492681220 IJISTECH (International Journal Of Information System & Technology) is a peer-reviewed open-access journal published two times a year in English-language, provides scientists and engineers throughout the world for the exchange and dissemination of theoretical and practice-oriented papers dealing with advances in intelligent informatics. All the papers are refereed by two international reviewers, accepted papers will be available online (free access), and no publication fee for authors. The articles of IJISTECH will be available online in the GOOGLE Scholar. IJISTECH (International Journal Of Information System & Technology) is published with both online and print versions. The journal covers the frontier issues in computer science and their applications in business, industry, and other subjects. 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. • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Autonomous Agents and Multi-Agent Systems • Bayesian Networks and Probabilistic Reasoning • Biologically Inspired Intelligence • Brain-Computer Interfacing • Business Intelligence • Chaos theory and intelligent control systems • Clustering and Data Analysis • Complex Systems and Applications • Computational Intelligence and Soft Computing • Cognitive systems • Distributed Intelligent Systems • Database Management and Information Retrieval • Evolutionary computation and DNA/cellular/molecular computing • Expert Systems • Fault detection, fault analysis, and diagnostics • Fusion of Neural Networks and Fuzzy Systems • Green and Renewable Energy Systems • Human Interface, Human-Computer Interaction, Human Information Processing • Hybrid and Distributed Algorithms • High-Performance Computing • Information storage, security, integrity, privacy, and trust • Image and Speech Signal Processing • Knowledge-Based Systems, Knowledge Networks • Knowledge discovery and ontology engineering • Machine Learning, Reinforcement Learning • Memetic Computing • Multimedia and Applications • Networked Control Systems • Neural Networks and Applications • Natural Language Processing • Optimization and Decision Making • Pattern Classification, Recognition, speech recognition, and synthesis • Robotic Intelligence • Rough sets and granular computing • Robustness Analysis • Self-Organizing Systems • Social Intelligence • Soft computing in P2P, Grid, Cloud and Internet Computing Technologies • Stochastic systems • Support Vector Machines • Ubiquitous, grid and high-performance computing • Virtual Reality in Engineering Applications • Web and mobile Intelligence, and Big Data
Articles 223 Documents
Implementation of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in Recommendations for New Position in Companies Mesran M; Eka Pratiwi Sumantri; Supriyanto S; Syafrida Hafni Sahir; Nelly Khairani Daulay
IJISTECH (International Journal of Information System and Technology) Vol 4, No 2 (2021): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

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

Abstract

This study aims to provide support to management in recommendations for promotion of employee promotions, with the aim of providing motivation to employees. The problem encountered at this time is the number of employees making it difficult for management to choose employees to recommend in promotions for promotions. In this research, the method used is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) which is a fairly good method in ranking where the best alternative is the alternative that has the closest distance to the best alternative and far from the worst alternative. From the research results, it can be concluded that the A5 alternative is the best with a value of 0.748 and can be recommended in a new position promotion at the company.
Generating Mersenne Prime Number Using Rabin Miller Primality Probability Test to Get Big Prime Number in RSA Cryptography Dicky Apdilah; Nurul Khairina; Muhammad Khoiruddin Harahap
IJISTECH (International Journal of Information System and 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.v1i1.1

Abstract

Cryptography RSA method (Rivest - Shamir - Adelman) require large-scale primes to obtain high security that is in greater than or equal to 512, in the process to getting the securities is done to generation or generate prime numbers greater than or equal to 512. Using the Sieve of Eratosthenes is needed to bring up a list of small prime numbers to use as a large prime numbers, the numbers from the result would be combined, so the prime numbers are more produced by the combination Eratosthenes. In this case the prime numbers that are in the range 1500 < prime <2000, for the next step the result of the generation it processed by using the Rabin - Miller Primarily Test. Cryptography RSA method (Rivest - Shamir - Adleman) with the large-scale prime numbers would got securities or data security is better because the difficulty to describe the RSA code gain if it has no RSA Key same with data sender.
Implementation and Analysis Zhu-Takaoka Algorithm and Knuth-Morris-Pratt Algorithm for Dictionary of Computer Application Based on Android Handrizal Handrizal; Andri Budiman; Desy Rahayu Ardani
IJISTECH (International Journal of Information System and 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.v1i1.2

Abstract

The string matching algorithm is the one of the most important parts in the various processes related to data and text types, which is the word search on computer dictionary. Computers have a basic role in the field of education, especially in teaching and learning activities. So that the classical learning model, that is by using the book as learning resource can be boring. To make it easier for users who searching words, we made an offline dictionary application based on Android by applying Zhu-Takaoka algorithm and Knuth-Morris-Pratt algorithm. The performance of Zhu-Takaoka is doing a search starts from the end of pattern that is tailored to the text, but in Knuth-Morris-Pratt algorithm starts from the beginning of pattern till match which the pattern used is word searched. The result of this research indicates that the Zhu-Takaoka algorithm is faster than the Knuth-Morris-Pratt algorithm which showed the running time of each algorithm.
Neural Network Analysis With Backpropogation In Predicting Human Development Index (HDI) Component by Regency/City In North Sumatera Muhammad Noor Hasan Siregar
IJISTECH (International Journal of Information System and 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.v1i1.3

Abstract

Human Development Index (HDI) measures human development outcomes based on a number of basic components of quality of life. As a measure of the quality of life, HDI is built through a basic three-dimensional approach. Data obtained from the Central Bureau of Statistics 2015 for Human Development Index (HDI) by Regency / City in North Sumatera Province consisting of 32 alternatives and with 4 parameters ie life expectancy (year), expectation, school length (%), the average length of school (year) and per capita real expenditure (Rp). By using backpropagation obtained result of 6 testing of architecture pattern that is: 4-5-1, 4-10-1, 4-5-10-1, 4-10-5-1, 4-10-20-1 and 4- 15-20-1 obtained best architectural pattern is 4-10-20-1 with epoch 2126, error 0.0011757393, execution time 00:16 and accuracy 100%.
Analysis of Artificial Neural Network Accuracy Using Backpropagation Algorithm In Predicting Process (Forecasting) Sandy Putra Siregar; Anjar Wanto
IJISTECH (International Journal of Information System and 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.
Use of Binary Sigmoid Function And Linear Identity In Artificial Neural Networks For Forecasting Population Density Anjar Wanto; Agus Perdana Windarto; Dedy Hartama; Iin Parlina
IJISTECH (International Journal of Information System and 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.
Cloud Computing Implementation with Docker Engine Swarm Mode for Data Availability Infrastructure of Rice Plants Oktalia Juwita; Diksy Media Firmansyah
IJISTECH (International Journal of Information System and 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.v1i2.10

Abstract

Data of rice plant is important in Indonesia because rice is the staple food for Indonesian people. Rice plant data can be formatted into web service, so anyone can access the information from anywhere by using internet. But, high numbers of request are the problem for web server apps. One of the solution is by distributing request into some server. In this paper, we will compare failed request and time per request in conventional server and clustered server with docker swarm. Server apps in clustered server shows lower value of failed request than conventional server in our experiment. With two containers, number of failed request obtain 0.78% lower than conventional server in 25.000 requests, and 0.69% lower than conventional server in 50.000 requests.
Message Security on Chat App based on Massey Omura Algorithm Taronisokhi Zebua; Rivalri Kristianto Hondro; Eferoni Ndruru
IJISTECH (International Journal of Information System and 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.v1i2.11

Abstract

Security of message on chat apps is very important to do so that messages that distributed always safety for others who do not have access permission. However, not all chat apps currently have tools that used to secure messages. This is still often overlooked, thus providing an easy space for the attackers to hack messages that are distributed. This research explains the usage of the massey-omura algorithm to secure text type message in chat apps when message distributed
ANN: Model of Back-Propagation Architecture on the Logs Production by Type of Wood Muhammad Noor Hasan Siregar
IJISTECH (International Journal of Information System and 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.
Comparative Analysis of Pathfinding Algorithms A *, Dijkstra, and BFS on Maze Runner Game Silvester Dian Handy Permana; Ketut Bayu Yogha Bintoro; Budi Arifitama; Ade Syahputra
IJISTECH (International Journal of Information System and 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.v1i2.7

Abstract

Maze Runner game is a game that requires pathfinding algorithm to get to the destination with the shortest path. This algorithm is used in an NPC that will move from start node to destination node. However, the use of incorrect algorithms can affect the length of the computing process to find the shortest path. The longer the computing process, the longer the players have to wait. This study compared pathfinding algorithms A *, Dijkstra, and Breadth First Search (BFS) in the Maze Runner game. Comparison process of these algorithms was conducted by replacing the algorithm in the game by measuring the process time, the length of the path, and the numbers of block played in the existing computing process. The results of this study recommend which algorithm is suitable to be applied in Maze Runner Game.

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