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Journal of Advances in Information Systems and Technology
Published by Universitas Negeri Semarang
ISSN : -     EISSN : 2715999X     DOI : https://doi.org/10.15294/jaist
Core Subject : Science,
Library & Information Science
Journal of Advances in Information Systems and Technology (JAIST) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of advances in information systems and technology which covers 16 major areas of research that include
Arjuna Subject : Ilmu Sosial - Perpustakan dan Informasi
Articles 10 Documents
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Search results for , issue "Vol. 6 No. 1 (2024): April" : 10 Documents clear
Analysis and Evaluation of Storage Systems Using the ABC Classification and Periodic Review Method at Supermarket in Semarang City Manasya Khulafa Alief Rahman; Zaenal Abidin
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.129

Abstract

The warehouse section is one of the parts that must exist in the company, especially for manufacturing or retail companies. Therefore, companies usually implement a storage system which is a policy to control, supervise, and determine the level of goods that need to be maintained. In addition, companies also use supply chain management to control the number of incoming and outgoing goods more effectively and efficiently. This is because the company only has limited warehouse storage space, so the amount of goods stored must also be in accordance with company needs. Including one of the retail companies in Semarang City, it is PT Inti Cakrawala Citra or can be called Indomaret Group which built a supermarket namely Indogrosir which has been established for almost 30 years and a lot of research has been done there, so it has a strong company system, including in the warehouse section. Based on this explanation, this study aims to analyze by implementing the proposed method using ABC Classification and Periodic Review on the storage system and evaluation based on the results obtained. This research uses a mixed-method approach with interview and documentation studies as data collection methods. The results of the interview that have been conducted prove that Indogrosir has a strong storage system and the results of the documentation study also show that the data successfully obtained are 19,872 with six different types of goods in the period October 2022 to August 2023. The result of data processing is the type of tabbacco which amounts to 274 data selected as a sample and results in the calculation of the total storage cost on one of the product codes with the company's method of IDR 10,888,505,214 and the proposed method of IDR 4,473,946, so that the implementation of the proposed method is more optimal. This is due to one of the variables in the company's method that uses purchase data or can be called capital for cashflow in the company, so it has much greater results. In addition, the proposed method also provides other outputs, such as the number of reorders, the amount of safety stock, and a high level of service level by implementing the proposed method that can help companies in managing stock items.
User Experience Evaluation of BPOM Mobile Application Using User Experience Questionnaire and Focus Group Discussion Method Afifah Muthmainnah; Devi Ajeng Efrilianda
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.1125

Abstract

The Indonesian Food and Drug Authority (BPOM) as a government agency has developed the BPOM Mobile application to make it easier for the public to check the safety of drug and food products in circulation. From the research results, several user experience problems were found on BPOM Mobile, especially in the scan product feature. User experience evaluation needs to be carried out to measure the comfort felt by the user and determine the user's level of understanding of the application being used. This research aims to evaluate the user experience on BPOM Mobile using the User Experience Questionnaire and Focus Group Discussion methods. The sampling technique used was purposive sampling which was based on the criteria of public users who had used the scan product feature and were 18-25 years old and had a sample size based on the User Experience Questionnaire guidelines of 30 people. Respondents were 6 users who were willing to do a Focus Group Discussion exploring perceptions and problems in detail related to 6 aspects of the User Experience Questionnaire and aspects of visual aesthetics. The research results show that the BPOM Mobile application currently has a neutral user experience score on the attractiveness, perspicuity, efficiency, dependability, and novelty scales and a positive user experience score on the stimulation scale. Based on the Focus Group Discussion, 20 negative perceptions and problems were found, with details of 2 perceptions and problems of attractiveness, 3 perceptions and problems of perspicuity, 4 perceptions and problems of efficiency, 5 perceptions and problems of dependability, 1 perception and problem of novelty, and 5 perceptions and problems of visual aesthetics, while stimulation obtained 1 positive perception. The problems obtained were corrected through a prototype and resulted in positive user experience values in all aspects.
The Effect of S-Commerce Tiktok Shop Recommendation Products on Changes in Consumer Impulsive Buying Behavior: A Study with Signaling Theory Asharinnisa Salsabila; Budi Prasetyo
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.1718

Abstract

Product recommendation was introduced as a marketing technique that is quite commonly used in online shopping platforms, one of which is TikTok Shop. The use of recommended products in the digital market environment is intended to learn consumer interests and preferences so that the target market can conduct marketing. It is expected to make it easier for consumers to find their desired products. However, the use of product recommendations in the digital market also has the potential to have a negative effect in the form of forming consumer impulsive behavior. For this reason, this research was conducted to understand what factors of product recommendations can motivate consumer impulsive behavior at TikTok Shop and to see the effectiveness of video advertisements in motivating consumers to make purchases. In its implementation, this research uses the principles of signaling theory as the basis of research. Then, the research was carried out using a quantitative approach to collect and process data. The data collection method was carried out through questionnaire distribution by utilizing Google form as a data collection medium and social media as a medium for distributing questionnaires. Meanwhile, the data from the questionnaire was processed using the SmartPLS 3 application. The study results show that providing product recommendations through video content (VC) has the potential to shape consumer impulsive behavior.
Analysis Acceptance of LinkedIn Application Users Using the Revised Technology Acceptance Model for Social Media and Information System Success Model Bagas Mahardika; Anggy Trisnawan Putra
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.2231

Abstract

Social media is a web-based application that provides facilities for communicating and chatting online, sharing videos and images, carrying out activities related to education and business, making learning easier, searching for information, and looking for work. LinkedIn is a social media designed to help many people make connections in business, share experiences, and find work. So far, LinkedIn is the most popular social network when it comes to recruiting. More than 95% of recruiters use social media in their recruiting process, which indicates that they use LinkedIn. The aim of this research is to determine the factors that influence perceived usefulness, perceived ease of use, and intention to use by using a combination of the revised Technology Acceptance Model (TAM) for social media and the Information System Success Model (ISSM) methods. This research uses a quantitative approach with sample criteria, namely people from Central Java who have used LinkedIn to look for work and are aged between 19 – 34 years. This research obtained 140 valid data through surveys distributed via social media. The results obtained found influencing factors. The results of the hypothesis test showed that there were 10 hypotheses that were accepted. From this hypothesis, there are several factors that influence perceived usefulness, namely information quality, service quality, critical mass, perceived playfulness, and trustworthiness. Then the factors that influence perceived ease of use are system quality and service quality. Then the factors that influence intention to use are information quality, trustworthiness, perceived usefulness, and perceived ease of use.
Acceptance of Artificial Intelligence-Based Online Shopping Applications: A Combination of Artificially Intelligent Device Use Acceptance and Online Shopping Service Quality Tiffany Ovilia Dwi Lestari; Endang Sugiharti
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.2232

Abstract

Nowadays, e-commerce, including Shopee, is often associated with Artificial Intelligence (AI). The use of AI systems triggers the emergence of new marketing methods to reach consumers effectively and offer a better shopping experience. Moreover, the increased use of AI in online commerce occurs because AI is considered an excellent tool to meet rapidly changing consumer demands. Currently, more sellers are using AI-supported features such as chatbots, smart logistics, and personalized recommendations. This makes online channels more competitive and enticing for consumers to make purchases. Despite the numerous benefits of e-commerce and AI, they are not exempt from shortcomings that make customers reluctant to use them. Therefore, this research aims to understand the relationship among factors influencing the acceptance and objection of AI-based Shopee by using a combination of Artificially Intelligent Device Use Acceptance (AIDUA) and Online Shopping Service Quality (OSSQ). The study employs a quantitative method with survey data collection techniques. The collected sample from the survey process consists of 169 respondents, mostly females aged 17-26 years, and students. The results obtained find that factors significantly influencing performance expectancy are social influence, hedonic motivation, anthropomorphism, website design, responsiveness, communication, and trustworthiness. Factors affecting effort expectancy are social influence, reliability, communication, anthropomorphism, and website design. Meanwhile, the factor influencing emotion is performance expectancy. Lastly, the factors influencing willingness to use and objection to use are emotion. Based on the research findings, Shopee developers can enhance the quality of their AI programming algorithms and improve the design quality of Shopee.
Evaluating User Continuance Intentions for QRIS Mobile Payments Services Using Information System Success Model and Expectation Confirmation Model Wiyan Herra Herviana; Zaenal Abidin
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.2398

Abstract

QRIS services on mobile payment applications are one of Indonesia's most popular payment methods, and they allow transactions by scanning or displaying the QR code. This enables mobile-based payments to be easy and flexible anywhere and anytime. As it grows and benefits, some obstacles exist regarding users' desire to continue using it. Some users decided to stop using the QRIS service for mobile payments due to indications of potential risks associated with the service. This research aims to find out what variables support or influence the intention to continue using QRIS services for mobile payments using quantitative methods and the information system success model (ISSM) and expectation confirmation model (ECM) frameworks by adding perceived risk and trust variables. The data collection technique used in this study was a questionnaires survey using Google Forms and applying purposive sampling techniques. The survey targeted QRIS service users aged 17 to 65 who experienced transactions using mobile payments (e-wallets and mobile banking). The data was collected from 513 respondents and analyzed using the partial least squares structural equation model (PLS-SEM) by Smart-PLS 4 software tools. The findings were that 10 hypotheses were declared accepted and five hypotheses were rejected. Based on the accepted hypothesis, research shows that satisfaction and trust influence the intention to continue using QRIS services for mobile payments. Satisfaction is a key factor that supports or influences a user's decision to continue using or utilizing QRIS payment services. The findings of this research can be an essential consideration for developers and companies providing QRIS services in mobile payments.
Customer Lifetime Value Clustering Using K-Means Algorithm with Length Recency Frequency Monetary Model to Enhance Customer Relationship Management Chairun Nisak; Endang Sugiharti
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.5011

Abstract

The current era of business growth is fraught with challenges and competition due to rapid technological advancements, rapid market growth, and globalization. This research discusses customer management strategies to enhance Customer Relationship Management (CRM) at PT Digibook Sarana Promosi Indonesia, a company in the digital printing industry. With the emergence of numerous competitors in this challenging business growth era, the k-means algorithm and Length, Recency, Frequency, Monetary (LRFM) model are employed for customer clustering. The results identify two main customer groups. The first group falls into the category of almost lost or uncertain lost customers with the symbol L↓R↑F↓M↓, exhibiting low Customer Lifetime Value (CLV), suggesting a "let go" strategy to focus on more valuable customers. The second group comprises high-value loyal customers with the symbol L↑R↓F↑M↑, demonstrating high CLV, recommending an "enforced" strategy to maintain customer loyalty through loyalty programs. This research indicates that the optimal number of clusters is 2, validated using the ClValid method, with the best values on connectivity, Dunn index, and silhouette.
A Periodic Review Inventory Control of Medicine at Hospital Devi Ajeng Efrilianda; Manasya Khulafa Alief Rahman
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.5954

Abstract

One of the important problems in inventory control is the problem of managing stock in the system. In the case of medicine product storage management, over inventory will lead to high storage costs and increase the risk of spoilage or expiration. While the shortage of inventory causes demand that cannot be fulfill. In addition, optimal storage management in the case of medicinal products is also an effort to create a socially responsible supply chain. Lack of product management causes products to experience stockout, resulting in low service levels at the hospital. This study aims to create a storage management model using periodic reviews so that the medicines in the hospital do not experience stockout or overstock and the hospital does not experience losses due to this. The periodic review method was chosen because it is considered capable of being a model of the problems faced by hospitals in storage. The calculation of the periodic review method requires data obtained from hospitals, such as demand data, lead time data, drug data, cost data, so the data used is primary data. After obtaining the required data, a periodic review is calculated which will become a benchmark for hospitals to place orders for medicines that have run out based on the demand for medicines and the time period from the sender of these medicines and so on 
Analysis of Factors Affecting Continued Interest in Using Online Food Delivery Features Using ECM and UTAUT2 Subhan Subhan; Afan Ismi Fauzan; Yusuf Wisnu Mandaya
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.6568

Abstract

The development of e-commerce in Indonesia itself is currently at the level of being able to provide online food delivery services, making it easier for users to order food. In addition, the Covid-19 pandemic has indirectly changed consumer behavior to avoid or reduce activities outside the home, including ordering food. This study was conducted to identify what factors influence consumers in using online food delivery services with continuance intention after the pandemic and uses a method that integrates variables from the ECM (Expectancy Confirmation Model) and UTAUT2 (Extended Unified Theory of Use and Acceptance of Technology 2). The data in this study were obtained by distributing questionnaires online on 252 online food delivery users. Meanwhile, the data analysis method uses excel for the data screening process and the SmartPLS 3 application to test the inner model and outer model. The results of this study show that the most frequently used online food delivery service application is Go-Food and is dominated by women, with an age group of 17 years to 25 years, the majority of students domiciled mostly in West Java province. Then, there are six accepted hypotheses and five rejected hypotheses. Based on the accepted hypothesis, it is found that the variable price saving orientation, habit has an effect in influencing users in using online food delivery services in continuance intention. This research is expected to provide positive input for the authorities to be able to improve the quality of service provided to users in the future.
Analysis of Public Awareness of Cybercrime in The Form of Adware suprih murdyantara; Kholiq Budiman
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.10769

Abstract

The development of information technology has had a big impact on human life. The impact of the development of information technology is the internet, which reaches all circles of society. The development of the internet has positive and negative impacts. The positive impact of the internet is that it helps humans get information quickly and can be reached anywhere. Meanwhile, the negative impact of the internet itself is the existence of cybercrime. There are various modes of cybercrime, one of which is the most often encountered by the public: adware-type malware, often known as malicious online advertising. The purpose of this study is to determine the factors that influence public awareness of cybercrime in adware. This research uses a quantitative method approach with sample criteria for respondents who live on Java Island with an age range of 18–45 years and actively use the internet. The data from the distributed questionnaires was processed with the partial least squares structural equation model (PLS-SSEM) using SmartPLS 4. The results obtained showed that of the 10 hypotheses that had been proposed, 8 were accepted. Based on these results, there are factors that influence public awareness of cybercrime, including the use of social media, cybercrime information and news, cybercrime law enforcement, and adware knowledge. Furthermore, adware knowledge is influenced by cybercrime information, news, and social media usage.

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