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All Journal Techno.Com: Jurnal Teknologi Informasi Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) JAIS (Journal of Applied Intelligent System) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control EDUMATIC: Jurnal Pendidikan Informatika Jurnal Informatika dan Rekayasa Perangkat Lunak Teknosains : Jurnal Sains,Teknologi dan Informatika International Journal of Artificial Intelligence and Robotics (IJAIR) Mathematics and Applications (MAp) Journal Jurnal Ekonomi dan Manajemen (JEKMA) Journal of Artificial Intelligence and Digital Business Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Seminar Nasional Teknologi dan Multidisiplin Ilmu Jurnal Informatika Polinema (JIP) Jurnal Pengabdian Kepada Masyarakat Jurnal Maisyatuna Synergy In Economic & Business Management (SEBM)
Moch. Sjamsul Hidajat
Universitas Dian Nuswantoro Kediri
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Transportation Other

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Journal : JAIS (Journal of Applied Intelligent System)

 1 
Securing Digital Color Image based on Hybrid Substitution Cipher Moch Sjamsul Hidajat; Ichwan Setiarso
Journal of Applied Intelligent System Vol 4, No 2 (2019): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v4i2.3380

Abstract

This study proposes securing digital color images with hybrid substitution cryptographic methods combined with the Vigenere and Beaufort methods. The hybrid process is carried out using the help of two randomly generated keys. The first key is a matrix with an 8-bits value and the second key is a matrix with a binary value. The binary key is used to determine the Vigenere or Beaufort process, while the 8-bit key is used for modulus operations based on the Vigenere or Beaufort algorithm. At the test stage used a standard image that has an RGB color channel as a dataset. The quality of the cryptographic method is measured by several measuring instruments such as MSE, PSNR, and SSIM to determine the quality of encryption visually and the perfection of decryption, besides that it is used Entropy, NPCR and UACI to determine the probability of encryption resistance and quality against differential attacks. The TIC TOC function is also used to measure the computing speed of the encryption and decryption process. Measurement results using all measuring instruments indicate that the proposed method has very satisfying results and has fast computing. Keywords – Cryptography, Substitution Cipher, Modulus Function, Encryption, Decryption, Image Transmission 
Classification and Regression Trees (CART) Algorithm for Employee Selection Aulia Rahmawati; Rizal Muhammad Affandi; Dea Debora Aprillia; Daffa Maulana; Zudha Pratama; Moch. Sjamsul Hidajat
Journal of Applied Intelligent System Vol 7, No 3 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i3.7201

Abstract

Recruitment is the main key in an effort to improve the quality of human resources in a company. Good or bad employees greatly affect the quality of the company. Therefore, it is necessary to be thorough and take a long time in screening applicants in order to get competent, professional and as expected prospective employees. The absence of professional staff to conduct employee selection is the background of this research. So the researcher uses the CART algorithm for the classification of employee recruitment, so it is hoped that it can help companies in conducting employee selection. The dataset was obtained from the selection of freelance daily workers at the Pati Regency Civil Service Police Unit in 2018, totaling 290 prospective employees. Based on calculations on 5-fold cross validation, the resulting accuracy is 98.27%, precision is 99.13% and recall is 96.88%.
Poverty Modeling in East Java Province Using the Spatial Seemingly Unrelated Regression (Sur) Method Wibowo, Dibyo Adi; Hidajat, Moch Sjamsul; Widyatmoko, Widyatmoko
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.8178

Abstract

Poverty is a complex problem because it relates to various aspects of human life. In Indonesia, there is one province that has a very high percentage of poverty, namely East Java Province. Although from year to year the poverty rate has decreased, when viewed from the national level it is still very far from the government's expectations of reducing the poverty rate. Cases of poverty can be modeled by Econometrics. Econometric models are often applied to problems involving one or more related equations. One method that can be used to solve several interrelated equations because there is a correlation error regression between one another, namely Seemingly Unrelated Regression which is usually abbreviated as SUR, in this case Spatial Seemingly Unrelated Regression (SUR-Spatial) is development that takes into account the spatial influence between locations. From the results of tests conducted in the SUR-Spatial Lagrange Multiplier model, the poverty data generated by the East Java Province is the SUR-Spatial Autoregressive Model (SUR-SAR). So with the SUR-SAR model it can be seen that the variable that has a significant effect on the percentage of poor people is the growth rate of Gross Regional Domestic Product based on the constant price of the minimum wage for each district, as well as the average length of school years. Meanwhile, the Poverty Depth Index has an effect because of the growth rate of Gross Regional Domestic Product on the basis of constant prices and the average length of schooling. The Poverty Severity Index is influenced by the growth rate of Gross Regional Domestic Product at constant prices and average years of schooling.
Covid-19 Classification using Convolutional Neural Networks Based on Adam, RMSP, and SGD Optimalization Hidajat, Moch Sjamsul; Wibowo, Dibyo Adi
(JAIS) Journal of Applied Intelligent System Vol. 8 No. 3 (2023): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i3.9492

Abstract

In this comprehensive study, a meticulous analysis of the application of Convolutional Neural Network (CNN) methodologies in the classification of Covid-19 and non-Covid-19 cases was conducted. Leveraging diverse optimization techniques such as RMS, SGD, and Adam, the research systematically evaluated the performance of the CNN model in accurately discerning intricate patterns and distinct features associated with Covid-19 pathology. the implementation of the RMS and Adam optimization methods resulted in the highest accuracy levels, with both models achieving an impressive 98% accuracy in the classification of Covid-19 and non-Covid-19 cases. Leveraging the robust capabilities of these optimization techniques, the study successfully demonstrated the effectiveness of the RMS and Adam models in enhancing the precision and reliability of the Convolutional Neural Network (CNN) for the accurate identification and differentiation of Covid-19 patterns within the medical imaging datasets. The notable achievement of 98% accuracy further emphasizes the potential of these optimization methods in advancing the capabilities of CNN-based diagnostic tools, thus contributing significantly to the ongoing efforts in Covid-19 diagnosis and management.  
Predicting Gold Price Movement Using Long Short-Term Memory Model Nagata, Azaria Beryl; Hidajat, Moch Sjamsul; Wibowo, Dibyo Adi; Widyatmoko, Widyatmoko; Yaacob, Noorayisahbe Bt Mohd
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i1.10305

Abstract

Gold, as a valuable commodity, has been a primary focus in the global financial market. It is often utilized as an investment instrument due to the belief in its potential price appreciation. However, the unpredictable and complex movement of gold prices poses a significant challenge in investment decision-making. Therefore, this research aims to address this issue by proposing the use of the Long Short-Term Memory (LSTM) model in time series analysis. LSTM is a robust approach to understanding patterns and trends in gold price data over time. In the context of time series analysis, historical gold price data includes daily, weekly, and monthly datasets. Each model with its respective dataset is useful for identifying patterns in gold prices. The daily model achieves an MSE of 452.2284140627481 and an RMSE of 21.26566279387379. The weekly model achieves an MSE of 1346.1816584357384 and an RMSE of 36.69034830082345. The monthly model achieves an MSE of 11649.597907584808 and an RMSE of 107.93330305139747. With these RMSE results, the LSTM model can predict gold prices effectively. Based on the trained models, it can also be concluded that gold prices exhibit long-term temporal dependence.
Data Mining Application Analyzing Customer Purchase Patterns Using The Apriori Algorithm Prayugo, Moh. Lambang; Wibowo, Dibyo Adi; Hidajat, Moch. Sjamsul; Mintorini, Ery; Ali, Rabei Raad
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i1.10308

Abstract

The study aims to implement Data Mining with Apriori Algorithm and Association Methods (shop cart analysis) to analyze the sales pattern of Kaffa Beauty Shop stores as a case study. Sales information obtained from stores is used to find out the repeated buying habits of cosmetic products. This analysis provides store owners with valuable information to make more useful decisions about product inventory management, marketing strategies, and other aspects of their business. The Apriori Algorithm implementation follows steps including data preprocessing, subsetting, frequent dataset search, and strong association rules (strong Association Rules). The results of the analysis show that there are important purchasing patterns among some cosmetic products that can be the basis of a more effective sales strategy. The study helps understand how data mining and Apriori Algorithms can be applied in business contexts such as Kaffa Beauty Shop stores. Therefore, the results of this analysis are expected to contribute greatly to improving business efficiency and optimizing marketing strategies for store owners and stakeholders. The research is also expected to show the enormous potential of data analysis to support optimal business decision making.
Co-Authors Ainun Muhtadin Ali, Rabei Raad Angel Frilyaningrum Aulia Rahmawati Azhari, Daffa Maulana Bhekti Eka Ferdianto Bonifacius Vicky Indriyono Budi Widjajanto Choerul Umam Daffa Hafizh Dzamara Daffa Maulana Dea Debora Aprillia Dibyo Adi Wibowo Ery Mintorini Ery Mintorini Evita Citra Yustiqomah Ichwan Setiarso Ida Farida Iffah Irdinawati Imam Nuryanto Iqlima Zahari Jaka Prasetya karmila karmila Lewa, Andi Hallang Muhammad Burhanudin, Muhammad Nagata, Azaria Beryl Natanael, David Febrian Pratama, Zudha Prayugo, Moh. Lambang Puspa, Silfi Andriana Rizal Muhammad Affandi Setiawan, Aries Stevani Tri Wahyu Putri Toni Wibowo Tri Esti Rahayuningtyas Widyatmoko Widyatmoko Wildan Mahmud Yaacob, Noorayisahbe Bt Mohd Yulianti, Shinta Rachma