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INDONESIA
Journal of Information Systems and Informatics
Published by Asosiasi Doktor Sistem Informasi Indonesia
ISSN : 26565935     EISSN : 26564882     DOI : 10.63158/journalisi
Core Subject : Science,
Computer Science & IT
Journal-ISI is a scientific article journal that is the result of ideas, great and original thoughts about the latest research and technological developments covering the fields of information systems, information technology, informatics engineering, and computer science, and industrial engineering which is summarized in one publisher. Journal-ISI became one of the means for researchers to publish their great works published two times in one year, namely in March and September with e-ISSN: 2656-4882 and p-ISSN: 2656-5935.
Arjuna Subject : -
Articles 653 Documents
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IoT and Edge Computing Technologies as Security Option for Train Service in Nigeria Eli Adama Jiya; Faith Titobiloluwa Akinyemi; Uriah A Nwocha
Journal of Information System and Informatics Vol 5 No 3 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i3.560

Abstract

The revival of rail transport service in Nigeria in recent years came at a critical moment of insecurity in Nigeria, it promised not only to serve as an alternative to overloaded vehicles on the roads but was also thought to be a safer means of transportation. Due to kidnapping on many roads, both high and low-class Nigerians patronized rail transport. However, train attacks and terrorism are major challenges that have impacted the sector negatively. Though the government has tried to improve surveillance along train routes, however, the result has not been impressive. The current level of insecurity in Nigeria is beyond the use of traditional surveillance and monitoring systems. It requires the adoption of technology to fight attacks and to monitor the health of train facilities. While the insecurity challenges that have overwhelmed the security forces will not permit the assignment of more personnel to the rail tracks that stretch several kilometres across the country, the incorporation of IoT and edge computing can be an optimal solution to the challenges of constant security problems. Among the trending technologies, IoT is a viable option that the country can adopt to improve security in the sector. It will increase the confidence of passengers and improve revenue and growth in rail transport.
Modified Genetic Algorithm and Association Rule Mining for the Retail Sector Piyush Vyas; Aditya Nagdiya
Journal of Information System and Informatics Vol 5 No 3 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i3.561

Abstract

This paper concentrates on the optimization of elementary association rule mining. The basic approach of association rule mining generates the positive association rule but focusing on both positive and negative association rule mining to find out efficient results is lacking. Thus our aim is to provide an approach to optimize all positive and negative association rules with the help of a modified genetic algorithm. A genetic algorithm is an optimization technique that provides the best possible solutions that are stronger than the other solutions. The present approach focuses on the importance of population through mean fitness value for further genetic algorithm operation. This paper also shows a comparison between normal Apriori, the Genetic Algorithm, and our proposed algorithm. Where in as a result the proposed approach worked better than others. We believe that the proposed methodology would increase the efficiency of the Decision support system of retail stores.
Information Security Evaluation Using Case Study Information Security Index on Licensing Portal Applications Wardhani, Widiastuti Kusumo; Soewito, Benfano; Zarlis, Muhammad
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.563

Abstract

There's a lot of cyber attacks going on right now, so the Ministry of Public Works and People's Housing (PUPR) has to get serious about preventing them. One of the information system that contains critical public data need to be secured is Portal Perizinan. In order to maintain information security, an evaluation should be carried out to assess the level of readiness (comprehensiveness and consistency) of the implementation of information security based on the SNI ISO/IEC 27001:2013 criteria using the Information Security Index. (KAMI Index). The five areas assessed aim to determine the level of organization preparedness in the implementation of information security. Obtained a score of 31 for the level of organization dependence on electronic systems, with a high level of category. The presence of technology security is at level I through to level II and our index measures 351, which means that the level of maturity of the new ISMS is at the stage of Achievement of the Basic Framework. From the results of this case study it can be seen that the state of information security readiness in the Ministry of PUPR still needs to be improved to meet ISO 27001 standard.
Machine Learning-Based E-Archive for Archives Management of South Sumatra Province Atmojo, Toni Tri; Kunang, Yesi Novaria
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.566

Abstract

Archives play a crucial role in institutional operations, yet efficiently retrieving specific information from them can be challenging. This research addresses this issue by developing an information retrieval system that incorporates advanced methods to enhance search efficiency. The system employs the TF-IDF (Term Frequency-Inverse Document Frequency) formula, which assesses the significance of a word within a document set, and the BM25 method, a sophisticated algorithm for ranking documents based on their relevance to the input query. Both methods undergo a preprocessing stage, enabling the system to calculate the relevance of each document to the given query accurately. The effectiveness of this system is evaluated using key performance metrics: precision (accuracy), recall (completeness), and the F1 Score (the harmonic means of precision and recall, representing the best value). Testing with various keywords revealed that the BM25 method yielded impressive results, achieving an average precision of 0.75, recall of 0.6, and an F1 Score of 0.6665. In contrast, the TF-IDF method scored lower, with a precision of 0.33, recall of 0.2, and an F1 Score of 0.2500. The system was tested using a dataset of 350 documents.
Empowering Pregnancy Risk Assessment: A Web-Based Classification Framework with K-Means Clustering Enhanced Models Wongso, Bernard Pratama; Johan, Monika Evelin; Fianty, Melissa Indah
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.568

Abstract

This study aims to determine whether there is an increase in accuracy results for predicting pregnancy risk with a classification algorithm that goes through and without going through the clustering stage. After that, compare which classification algorithm gets the best improvement. This study uses the K-Means clustering approach, as well as the SVM, Naive Bayes, and K-Nearest Neighbor (KNN) classification algorithms. The pregnancy risk dataset used comes from the UCI Machine Learning Repository. Evaluation metrics used include accuracy, precision, recall, and F1-score. The results of the study revealed that the K-Means model with KNN provided the highest performance compared to the other two, with an accuracy of 79.53% and an average F1-score of 0.8. The implementation of K-Means resulted in an increase in accuracy of 0.4%, 1.57%, and 2.76% on KNN, SVM, and Naive Bayes respectively, which confirms the impact of clustering in improving classification performance. The resulting model can be used in real-time via a website built using the Flask API, and offers tools that can help health practitioners to plan treatments effectively and minimize the risk of pregnancy.
Evaluation the Information Security Management System: A Path Towards ISO 27001 Certification Jevelin, Jevelin; Faza, Ahmad
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.572

Abstract

This study addresses the urgent need for robust data security by evaluating the Information Security Management System (ISMS) of a private contractor poised for ISO 27001 certification. It introduces the context of pervasive data breaches that necessitate stringent security measures. Employing a mixed-methods approach, the research method combines the KAMI index for quantitative maturity assessment with qualitative insights from staff interviews and literature reviews. The results reveal the contractor's ISMS maturity at levels I+ to II, indicating a shortfall in meeting the ISO 27001 benchmark. The discussion highlights the efficacy of the PDCA cycle in ISMS implementation, but also underscores the imperative for enhancements to fulfill certification requirements.
Stream Clustering for Selection Recommendations Using K-Means Algorithm: A Case Study in the Informatics Study Program Anggraini, Riska Fahmita; Sau'da, Siti
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.576

Abstract

Concentration Stream for a major is a process where students focus their attention on a specific discipline according to their interests. The purpose of specialization is to better orient students to the knowledge they have gained from previous courses, so that they can have a clearer focus. In the Informatics Engineering study program at Bina Darma University there are 3 concentrations, namely: Software Engineering, Network Engineering, Data Analytics. The absence of a system that helps students choose a major concentration makes it quite difficult for students to know their academic abilities. By looking at these problems, this research aims to build a Recommendation system for selecting Mk-Stream Concentrations using the K-Means grouping approach using the K-Means cluster method. Where student academic achievement data from the first semester to the 4th semester is used as a variable in the calculations.
Spatial Analysis of Changes in Normalization Differences Vegetation Index in Protected Forest Areas of South Lore District, Poso Regency Suni, Muhammad Adam; Basoka, Muhammad Darmawan; Rafiq, Muhammad; Umar, Mohamad Fahrul Himalaya; Muis, Hasriani; Baharuddin, Rhamdhani Fitrah; Agusman, Agusman
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.577

Abstract

Detection of changes in vegetation density generally uses the vegetation index parameter. The value of the vegetation index can provide information on the proportion of vegetation cover, live plant index, plant biomass, cooling capacity, and estimation of carbon dioxide absorption. This study aims to analyze changes in the level of vegetation density using Sentinel 2-A imagery in the protected forest area of South Lore District. This study used the method of calculating the Normalized Difference Vegetation Index (NDVI) to identify changes in density over 5 years. The results of the NDVI analysis are the largest in the range of -0.92960 to 0.871725. The vegetation density class in the Protected Forest Area of South Lore District in 2017 is in the dense class with an area of 15,322.24 Ha or around 47.66%, while the smallest in the non-vegetation class, which is 103.11 Ha or 0.32%, while the largest vegetation density class is in the Protected Forest Area of South Lore District in 2022, namely in the medium/quite dense class with an area of 19,948.18 Ha or 62.01% while the smallest in the non-vegetation class of 219.17 Ha or 0.68%. The largest increase in area was in the moderate/quite dense class of 4,892.33 Ha or 15.20% while the largest decrease in area was in the dense class with an area of 6,651.16 Ha or 20.67% of the total area of the Protected Forest Area of South Lore District.
Assessment of Village Readiness for Electronic Citizen Complaint Services (e-AduMas) Using COBIT 4.1 Ferdiansyah, Doddy; Majapahit, Sali Alas; Muttaqin, Muhammad Fadli
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.578

Abstract

The objective of this study is to investigate the implementation of the electronic community complaint service, known as e-AduMas, in villages utilizing SMS Gateway and GSM network technologies. The research aims to evaluate both the technological readiness of village offices using COBIT 4.1 and the community's acceptance of the e-AduMas system. The study employs a comprehensive research methodology that includes the analysis of community needs, the design of the e-AduMas system, the development of an integrated SMS Gateway application with the village government platform, and field testing involving active participation from the village community. Data will be collected through surveys, interviews, and observations to assess the level of implementation success, user response, and technical feasibility. The anticipated outcomes of this research include practical guidance for other villages looking to construct similar systems to enhance citizen participation in local governance. This study is poised to make a significant contribution to the application of technology in village governance, specifically in the development and utilization of the e-AduMas service. The findings of this research are expected to provide valuable insights for strengthening citizen engagement in local governance through innovative technological solutions.
Product Stock Supply Analysis System with FP Growth Algorithm Hartanti, Dwi; Atina, Vihi
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.580

Abstract

This study explores the application of Data Mining in deciphering consumer purchasing patterns at Tani Heritage Shop, a retailer specializing in agricultural products. Facing the challenge of managing a high volume of daily sales transactions, the shop often encounters difficulties in tracking which products are frequently purchased together. This lack of insight leads to a critical issue: popular products running out of stock unexpectedly. To address this, the research focuses on developing a product stock supply analysis system, utilizing the FP Growth Algorithm. The FP Growth Algorithm, a powerful tool in Data Mining, is employed to analyze sales transaction data and identify consumer purchasing trends, particularly products bought simultaneously. This approach is designed to provide insights into optimal stocking strategies, ensuring the availability of in-demand products. The research methodology involves applying the FP Growth Algorithm to model the product stock supply system, using specific sales data attributes. The results of this study are significant. By setting parameters such as a minimum support value of 30%, a confidence value of 70%, and targeting the highest lift ratio value of 3.67, the research successfully derives several key association rules from the FP Growth algorithm. These rules are instrumental in optimizing the product stock supply analysis system.

Page 27 of 66 | Total Record : 653

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