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Register: Jurnal Ilmiah Teknologi Sistem Informasi
Published by Universitas Pesantren Tinggi Darul ulum
ISSN : 25030477     EISSN : 25023357     DOI : -
Core Subject : Science,
Computer Science & IT
Register: Jurnal Ilmiah Teknologi Sistem Informasi published by the Department of Information Systems Unipdu Jombang. Register published twice a year, in January and July, Registerincludes research in the field of Information Technology, Information Systems Engineering, Intelligent Business Systems, and others. Editors invite research lecturers, the reviewer, practitioners, industry, and observers to contribute to this journal.
Arjuna Subject : -
Articles 8 Documents
 1 
Search results for , issue "Vol. 8 No. 1 (2022): January" : 8 Documents clear
Block-hash of blockchain framework against man-in-the-middle attacks Imam Riadi; Rusydi Umar; Iqbal Busthomi; Arif Wirawan Muhammad
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol. 8 No. 1 (2022): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2190

Abstract

Payload authentication is vulnerable to Man-in-the-middle (MITM) attack. Blockchain technology offers methods such as peer to peer, block hash, and proof-of-work to secure the payload of authentication process. The implementation uses block hash and proof-of-work methods on blockchain technology and testing is using White-box-testing and security tests distributed to system security practitioners who are competent in MITM attacks. The analyisis results before implementing Blockchain technology show that the authentication payload is still in plain text, so the data confidentiality has not minimize passive voice. After implementing Blockchain technology to the system, white-box testing using the Wireshark gives the result that the authentication payload sent has been well encrypted and safe enough. The percentage of security test results gets 95% which shows that securing the system from MITM attacks is relatively high. Although it has succeeded in securing the system from MITM attacks, it still has a vulnerability from other cyber attacks, so implementation of the Blockchain needs security improvisation.
Software similarity measurements using UML diagrams: A systematic literature review Evi Triandini; Reza Fauzan; Daniel O. Siahaan; Siti Rochimah; I Gede Suardika; Devi Karolita
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol. 8 No. 1 (2022): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2248

Abstract

Every piece of software uses a model to derive its operational, auxiliary, and functional procedures. Unified Modeling Language (UML) is a standard displaying language for determining, recording, and building a software product. Several algorithms have been used by researchers to measure similarities between UML artifacts. However, there no literature studies have considered measurements of UML diagram similarities. This paper presents the results of a systematic literature review concerning similarity measurements between the UML diagrams of different software products. The study reviews and identifies similarity measurements of UML artifacts, with class diagram, sequence diagram, statechart diagram, and use case diagram being UML diagrams that are widely used as research objects for measuring similarity. Measuring similarity enables resolution of the problem domains of software reuse, similarity measurement, and clone detection. The instruments used to measure similarity are semantic and structural similarity. The findings indicate opportunities for future research regarding calculating other UML diagrams, compiling calculation information for each diagram, adapting semantic and structural similarity calculation methods, determining the best weight for each item in the diagram, testing novel proposed methods, and building or finding good datasets for use as testing material.
The influence of familiarity and personal innovativeness on the acceptance of fintech lending services: A perspective from Indonesian borrowers Yekti Wirani; Randi Randi; Muh Syaiful Romadhon; Suhendi Suhendi
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol. 8 No. 1 (2022): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2327

Abstract

Financial Technology (FinTech) Lending in Indonesia is an innovative solution for financial services in Indonesia because it has convenience and benefits for Indonesians who need loans, fund management, and other financial transaction activities. FinTech Lending is growing fast because it offers reasonable interest rates and access to conventional financial institutions. The growth of FinTech Lending is expected to support financial inclusion planned by the Indonesian government. In 2020, 126 FinTech Lending Companies were operating illegally by exploiting communities experiencing economic difficulties. This study aims to determine the factors that influence the adoption of FinTech services in Indonesia, considering obstacles and occasions. Factors related to obstacles are Trust and Security in Online Lending platforms, while factors related to occasions are Personal Innovativeness, Interest Rate, and Familiarity. This study used a sampling technique, namely purposive sampling, and involved 85 respondents from Indonesian Borrowers with the age majority between 20 to 25 years old. Processes data obtained from survey results using Partial Least Square-Structural Equation Modeling (PLS-SEM). The results are that Familiarity and Personal Innovativeness affect the acceptance of FinTech Lending companies in Indonesia. In addition, it produces guidance for the improvement of FinTech Lending Companies in Indonesia, which be used to develop and support financial inclusion in Indonesia.
Spatial dynamics model of land use and land cover changes: A comparison of CA, ANN, and ANN-CA Moh. Dede; Chay Asdak; Iwan Setiawan
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol. 8 No. 1 (2022): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2339

Abstract

Land use and land cover (LULC) changes through built-up area expansion always increases linearly with land demand as a consequence of population growth and urbanization. Cirebon City is a center for Ciayumajakuning Region that continues to grow and exceeds its administrative boundaries. This phenomenon has led to peri-urban regions which show urban and rural interactions. This study aims to analyze (1) the dynamics of LULC changes using cellular automata (CA), artificial neural network (ANN), and ANN-CA; (2) the influential factors (drivers); and (3) change probability in the period 2030 and 2045 for Cirebon’s peri-urban. We used logistic regression as quantitative approach to analyze the interaction of drivers and LULC changes. The LULC data derived from Landsat series satellite imagery in 1999-2009 and 2009-2019, validation of dynamic spatial model refers to 100 LULC samples. This research shows that LULC changes are dominated by built-up area expansion which causes plantations and agricultural land to decrease. The drivers have a simultaneous effect on LULC changes with r-square of 0.43, where land slope, distance from existing built-up area, distance from CBD, and accessibility are significant triggers. LULC simulation of CA algorithm is the best model than ANN and ANN-CA based on overall accuracy and overall accuracy (0.96, 0.75, 0.73 and 0.95, 0.66, 0.66 respectively), it reveals urban sprawl through the ribbon and compact development. The average probability of built-up area expansion is 0.18 (2030) and 0.19 (2045). If there is no intervention in spatial planning, this phenomenon will decrease productive agricultural lands in Cirebon's peri-urban.
Fuzzy-AHP MOORA approach for vendor selection applications I’tishom Al Khoiry; Rahmat Gernowo; Bayu Surarso
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol. 8 No. 1 (2022): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2356

Abstract

Vendor selection is a critical activity in order to support the achievement of company success and competitiveness. Significantly, the company has some specific standards in the selection. Therefore, an evaluation is needed to see which vendors match the company's criteria. The purpose of this study is to evaluate and select the proposed vendor in a web-based decision support system (DSS) by using the fuzzy-AHP MOORA approach. The fuzzy-AHP method is used to determine the importance level of the criteria, while the MOORA method is used for alternative ranking. The results showed that vendor 4 has the highest score than other alternatives with a value of 0.2536. Sensitivity analysis showed that the proposed DSS fuzzy-AHP MOORA concept was already solid and suitable for this problem, with a low rate of change.
Effect of information gain on document classification using k-nearest neighbor Rifki Indra Perwira; Bambang Yuwono; Risya Ines Putri Siswoyo; Febri Liantoni; Hidayatulah Himawan
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol. 8 No. 1 (2022): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2397

Abstract

State universities have a library as a facility to support students’ education and science, which contains various books, journals, and final assignments. An intelligent system for classifying documents is needed to ease library visitors in higher education as a form of service to students. The documents that are in the library are generally the result of research. Various complaints related to the imbalance of data texts and categories based on irrelevant document titles and words that have the ambiguity of meaning when searching for documents are the main reasons for the need for a classification system. This research uses k-Nearest Neighbor (k-NN) to categorize documents based on study interests with information gain features selection to handle unbalanced data and cosine similarity to measure the distance between test and training data. Based on the results of tests conducted with 276 training data, the highest results using the information gain selection feature using 80% training data and 20% test data produce an accuracy of 87.5% with a parameter value of k=5. The highest accuracy results of 92.9% are achieved without information gain feature selection, with the proportion of training data of 90% and 10% test data and parameters k=5, 7, and 9. This paper concludes that without information gain feature selection, the system has better accuracy than using the feature selection because every word in the document title is considered to have an essential role in forming the classification.
An empirical study on the various stock market prediction methods Jaymit Bharatbhai Pandya; Udesang K. Jaliya
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol. 8 No. 1 (2022): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2533

Abstract

Investment in the stock market is one of the much-admired investment actions. However, prediction of the stock market has remained a hard task because of the non-linearity exhibited. The non-linearity is due to multiple affecting factors such as global economy, political situations, sector performance, economic numbers, foreign institution investment, domestic institution investment, and so on. A proper set of such representative factors must be analyzed to make an efficient prediction model. Marginal improvement of prediction accuracy can be gainful for investors. This review provides a detailed analysis of research papers presenting stock market prediction techniques. These techniques are assessed in the time series analysis and sentiment analysis section. A detailed discussion on research gaps and issues is presented. The reviewed articles are analyzed based on the use of prediction techniques, optimization algorithms, feature selection methods, datasets, toolset, evaluation matrices, and input parameters. The techniques are further investigated to analyze relations of prediction methods with feature selection algorithm, datasets, feature selection methods, and input parameters. In addition, major problems raised in the present techniques are also discussed. This survey will provide researchers with deeper insight into various aspects of current stock market prediction methods.
Associate Editors, Reviewers, & Table of Contents Register Register
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol. 8 No. 1 (2022): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2803

Abstract

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