TIERS Information Technology Journal

Application of The Waterfall Method to the Website-Based JM Leather & Shoes Point of Sales Information System

Ni Wayan Jeri Kusuma Dewi — 2024-06-21

Trading business is a type of business that has the basic concept of buying supplies of goods and reselling them with the aim of making a profit. In the current era, people continue to flock to set up a place of business, this is due to changes in market conditions as well as increasingly sophisticated economy and technology. JM Leather & Shoes continues to supervise and record the processing of goods data, supplier data, expenditure data, sales transactions, purchase transactions, and the preparation of reports which are always evaluated every month by superiors. During this time, both cashiers and administration record in the ledger. This of course causes various problems. Where the process of making reports takes a relatively long time, because the administration must first adjust the real stock at the place of business with the stock in the records until finally the difference between the two is found. One effort that can be made is to create an application that can help facilitate business process activities and minimize the occurrence of errors that could have a negative impact on the company's future. With this system, the data processing process from searching, adding, changing, to creating reports as evaluation material becomes easier and faster. The risk of data loss or damage can also be reduced to a minimum because it has been stored in the database, making it more effective and efficient. Future researchers are expected to add features for forecasting the items that are most and least desired by customers.

Marvel Movie Recommendation System Using Hybrid Item-Based and Content-Based Filtering Methods

Daffa Rizki Putra Noordi — 2024-06-25

Currently, there are so many movie genres available to the general public, making it difficult for viewers to choose a movie. One of the most popular movies is the “Marvel Movies” or MCU (Marvel Cinematic Universe), which has become the highest grossing franchise of all time with 90 movies released. The large number of movie titles makes it difficult for people to choose which movie to watch. Therefore, a Marvel movie recommendation system is needed using a hybrid item-based and content-based filtering method. The content-based method calculates the similarity between movies by identifying similar Marvel movies based on content such as genre, actor, director, and synopsis. Meanwhile, item-based completes content-based recommendations by considering user preferences. The reason for using the hybrid item-based and content-based filtering method is to be able to produce more accurate recommendations than a single method. The types and sources of data used are secondary data from journals and the internet (Imdb and Movielens), as well as datasets about Marvel movies. From the results of testing the hybrid model, the precision value is 0.8 or 80% which indicates that the model is accurate. In item-based filtering testing, the similarity result of 0.68 shows good item similarity. In the content-based filtering test, the highest similarity is 0.14 and the lowest similarity is 0.10 which shows that the similarity between the searched content and the generated content is relevant.

Implementing Design Thinking for UI/UX Optimization: Insights from PT. Asuransi Simas Jiwa

Vivi Rahayu — 2024-06-25

PT Asuransi Simas Jiwa is one of the companies that has implemented a fairly good information system in carrying out business processes. Siji Sales Force is a website-based information system used by Sales Agents to create, design and manage digital marketing activities. Based on the data collection results, it is known that several problems with the Siji Sales Force Web include shortcomings in terms of the appearance and functionality of the website. Based on observations of the features in the report menu, errors often occur and there has been no evaluation from the relevant parties. This research aims to provide recommendations for UI/UX design on the Siji Sales Force Website based on the results of analysis using the Design Thinking method. Design Thinking is an approach or method of problem solving both cognitively, creatively and practically to answer human needs as users. Design recommendations are built in prototype form using the Figma application. The prototype that was built was tested for usability using the System Usability Scale (SUS), obtaining a score of category B or "Good" which indicates that the prototype design meets acceptable requirements or is declared acceptable by interested parties. Based on the test results, the design redesign was acceptable and considered effective, so it is hoped that the design created can become a recommendation for the system development team to improve the Siji Sales Force website.

Implementation Of Decision Tree Algorithm For Classification Of Eligibility In Social Assistance Fund Distribution

Raden Deasy Mandasari — 2024-06-25

This study examined the use of decision tree algorithms, specifically C4.5, in classifying the eligibility for social assistance fund distribution in Kelurahan Bangka Belitung Laut, Kecamatan Pontianak Tenggara. Inaccuracies in distribution were caused by recipient selection based on village officials' recommendations, which only considered the type of occupation. To address this issue, this study developed a system based on the C4.5 algorithm to process economic census data. This research used a quantitative method with a descriptive analytical approach, collecting data through literature studies and economic census, and processing data using the Rapid Miner application. The classification model generated was evaluated using 10-fold cross-validation to ensure high accuracy. The results showed that the C4.5 algorithm achieved 100% accuracy, precision, and recall. The decision tree model indicated that the main attributes determining eligibility were occupation and income. Some rules derived from this model, such as those who are unemployed with an income below Rp29,500 being eligible for assistance, provided clear guidelines for policymakers. The implementation of this algorithm is expected to improve fairness and effectiveness in the distribution of social assistance funds in Kelurahan Bangka Belitung Laut, reduce public dissatisfaction, and prevent potential social conflicts. This study recommended adopting the model in other areas with adjustments to local data to enhance broader fairness in aid distribution.

AI in Dermatology: A Systematic Review on Skin Cancer Detection

Safrian Andromeda — 2024-06-25

Skin cancer is the most common type of cancer worldwide and poses a significant public health challenge. Its visible nature often leads individuals to seek medical attention, highlighting the importance of early detection for better patient outcomes. In recent years, Artificial Intelligence (AI) has shown promise in improving the detection and diagnosis of skin cancer, offering the potential to enhance clinical outcomes. A systematic review was conducted, involving a comprehensive literature search to identify studies focused on AI techniques in detecting, diagnosing, or treating skin cancer. Strict inclusion and exclusion criteria were applied to assess the eligibility of scientific articles, resulting in the selection of nine relevant studies. These studies were analyzed to address predefined research questions about the effectiveness of AI in diagnosing skin cancer. The review found that AI-assisted clinicians achieved higher sensitivity and specificity in diagnosing skin cancer than those without assistance. Various AI algorithms demonstrated high sensitivity in detecting skin cancers, highlighting their potential to support primary care clinicians in evaluating suspicious lesions. The analysis also highlighted the effectiveness of smartphone applications designed for skin cancer risk assessment, which could facilitate self-examinations and enhance early detection rates. Despite these promising findings, the field of AI in skin cancer diagnosis is still in its early stages. Challenges remain, including developing robust algorithms, addressing data quality issues, and improving the interpretability of AI-generated results. Collaboration between AI developers and healthcare professionals is crucial to ensure these tools' clinical effectiveness and safety. The review emphasizes the need for continued validation of AI technologies and their integration into clinical practice to improve patient outcomes and alleviate the burden on healthcare systems.

Consequences of Misclassification in Data Categorization for Tourism Attraction Recommendation DSS Using ARAS

Gede Surya Mahendra — 2024-06-25

This research focuses on optimizing tourism attraction management in Bali using DSS and the ARAS method, emphasizing the importance of accurate data categorization. Bali’s tourism industry, faced significant challenges during the COVID-19 pandemic, highlighting the need for effective management strategies. This study addresses these challenges by utilizing the ARAS method to analyze and rank tourist attractions. The research methodology follows the CRISP-DM model. The study demonstrates that improper use of conversion scales for quantitative data can lead to inaccurate rankings, as seen when comparing converted and non-converted data rankings. Alter01, Alter03, and Alter02 occupy the top three ranks in the non-converted data, while Alter09, Alter06, and Alter15 rank highest in the converted data. These findings highlight the need to use precise numerical values for criteria whenever possible and to reserve conversion scales for qualitative data, to ensure accurate and reliable recommendations. ARAS has a simple and easy-to-understand computational procedure. However, the results from ARAS heavily depend on the weights assigned to the criteria. Inaccurate determination of these weights can lead to outcomes that do not reflect actual preferences. The research concludes that implementing more refined data categorization techniques can enhance tourism management, promoting sustainable growth and more informed decision-making.

Artificial Intelligence-Entrepreneurship Future Research and Opportunities for New Business Model

Made Ayu Chandra Dewi Harika Putri — 2024-06-25

Artificial Intelligence (AI) is a capability related to intelligent creatures in the form of artificial robots which are fully controlled by digital computers. The presence of Artificial Intelligence (AI) certainly changes the structure of human life which affects the effectiveness of human performance such as in the field of entrepreneurship. The main scope in artificial intelligence technology is gaining strategic advantage in digital business, human resources, market research, customer relations, accounting and finance, sales, marketing, and others. The investigation of this work is centered to understand more about Artificial Intelligence, opportunities for using Artificial Intelligence for entrepreneurship, perspectives that support AI technology as part of the new model of business, perspectives against the development of artificial intelligence, as well as future opportunities from artificial intelligence technology.

Exploring the Integration of AI and Cloud Computing: Navigating Opportunities and Overcoming Challenges

Musawer Hakimi — 2024-06-25

This research seeks to establish how the integration of cloud computing and artificial intelligence identifies opportunities across operational efficiency, cost reduction, and innovation acceleration. This study seeks to establish how this integration is revolutionizing traditional business models and dealing with emerging security, privacy, and regulatory challenges. The applied method in this research was a systematic review strategy whose sources of data will be chosen from IEEE Xplore, Wiley Online Library, Springer, and ScienceDirect. The literature review focused on publications from 2019 to 2024 to deduce current findings that remain relevant. Results have shown that artificial intelligence, when integrated with cloud computing, would significantly enhance operational efficiency through process optimization and reduced cost using scalable cloud solutions. This also provides a greater pace of innovation by allowing real-time data processing and advanced analytics. However, such integration has a specific set of security and privacy concerns related to breaches and compliance with regulations in continuous evolution. It concludes that, though large, the benefits of AI and cloud computing integration must be reined in by strong security measures, updating regulatory frameworks, and continued research into ethical implications.

UI/UX Design of the Shop Feature on the Seafood by Aruna Website Using the Design Thinking Method

Anugerah Tirta Kenanga Unggul Mitra Mandiri — 2024-06-25

The current Seafood by Aruna website functions solely as a landing page to promote products, with actual sales still conducted through a marketplace. This reliance on a marketplace limits the brand's control over personalization, customer value, shopping experience, and brand identity due to strict platform policies and standards. Additionally, shifts in consumer behavior in the digital era indicate a desire for a more personalized, sustainable shopping experience that meets specific needs, including accurate product information and quality assurance. To address these challenges, this research aims to design an online shopping feature for the Seafood by Aruna website using the Design Thinking method. This approach is applied to understand user needs and address various pain points faced by consumers when shopping for seafood online. The research found that users require accurate delivery, reliable product information, and assurances of product freshness. Testing of the designed features using the System Usability Scale (SUS) yielded an average score of 90.12, categorized as "Best Imaginable." This score reflects that the developed features meet user expectations, thanks to the effective application of the Design Thinking method. The implications of this research suggest that developing a dedicated e-commerce platform enables Aruna to better control all aspects of the shopping experience, enhance customer satisfaction and loyalty, and strengthen its position in the e-commerce market. However, further development is needed to adapt the features to changing consumer behavior and market trends.

Application of Allot Secure Service Gateway for WAN Network Bandwidth Management at PT. Bank Permata Tbk

Dimas Trisna Putra Pambarep — 2024-06-25

As is generally experienced by large companies that have a large number of branches and centralized applications, PT. Bank Permata Tbk currently has WAN Bandwidth that manages links and the complexity of current applications and Protocols. However, the application and observation of the Bandwidth settings has not been maximized. If these problems are not regulated, it is feared that this will interfere with the performance of PT. Bank Permata Tbk which in the end will be able to reduce the level of business competition ability when compared to other Top companies that become its competitors. The research method used in this research is the HTB (Hierarchical Token Bucket) method. The HTB method is a method that functions to regulate the distribution of Bandwidth, the division is carried out in a hierarchy which is divided into classes to make Bandwidth Management easier. At this stage, the problem that will become the research object of the problem formulation is the absence of structured reports for Bandwidth usage in each branch. In the analysis of this system it can be concluded that PT. Bank Permata Tbk does not yet have a structured report for Bandwidth usage at each branch and without any special limitations on Bandwidth. And with this problem, the branch application that is used does not run optimally. With the implementation of Bandwidth Management using the Allot Secure Service Gateway on the WAN network of PT. Bank Permata Tbk so that it can produce structured reports and monitor Traffic Bandwidth from both branches to branch applications.