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All Journal Register: Jurnal Ilmiah Teknologi Sistem Informasi Emerging Science Journal Jurnal Sistem Cerdas Journal of Economics and Business UBS Jurnal Cahaya Mandalika Journal La Multiapp Cerdika: Jurnal Ilmiah Indonesia
Jayadi, Riyanto
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Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Public Health Social Sciences

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A Change Management for Transformation of Digital Banking In Indonesia Samosir, Paulima; Jayadi, Riyanto
Jurnal Sistem Cerdas Vol. 6 No. 1 (2023)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v6i1.280

Abstract

Bank 4.0 is about the ease of accessing banks or making banks in our hands. Also, the utility whenever and wherever we need financial solutions, in real-time, is programmed according to the behavior of each customer. Banks in their development can choose to change their business model towards digital banking. For this reason, it is necessary to carry out a good change management strategy so that the digital bank transformation process can be carried out. Not only those who are directly involved in the Change Management project but stakeholders within the organization are also involved. This study uses qualitative descriptive methods to design how change management strategies help banks transform into digital banks. The author collects several theories to explore the use of change management in organizations more deeply. In implementing change management, organizations can use a framework as introduced by Kurt Lewin, John Kotter, or the ADKAR framework from PROSCI. The ADKAR model is considered to have advantages in identifying gaps that occur during the change process by instilling awareness, desire, knowledge, ability, and reinforcement. The impact of this transformation led to changes in the organizational structure, business processes, and use of technology within the bank. It is hoped that applying the ADKAR model can help banks change their business models toward digital banking.
An Optimized Hybrid Model for Perishable Product Quality Inference in the Food Supply Chain Asrol, Muhammad; Suharjito, .; Jayadi, Riyanto
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-027

Abstract

The supply chain for perishable products faces significant challenges in monitoring and maintaining product quality. These products are particularly vulnerable to environmental dynamic conditions and variations in distribution and transportation. To address these challenges, leveraging the Internet of Things (IoT) and quality inference techniques during transportation can provide valuable insights for both consumers and producers. The objective of the research is to develop a model for inferring the quality of perishable products using an IoT sensor dataset to monitor perishable product quality continuously. This research applied a hybrid approach combining a Fuzzy Inference System (FIS), clustering models, and genetic algorithms to infer the product quality during supply chain distribution with IoT sensors. The result shows that the hybrid FIS model, which employs Gaussian membership functions and fuzzy c-means clustering for rule generation, achieves a high accuracy with an R²: 0.873. This research contributes to improving the model by employing genetic algorithms in optimizing the inference model by activating only five out of seven rules. The model optimization achieves optimal computation time while aiming to preserve model accuracy. However, test results indicate that the combination of rules has not yet significantly enhanced the model's accuracy, though it holds potential for future development. Doi: 10.28991/ESJ-2025-09-01-027 Full Text: PDF
Sentiment Analysis of Bamboo Charcoal: Comparing Machine Learning Algorithms for Effective Insights Agustine, Giovanni Ega; Jayadi, Riyanto
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.2010

Abstract

This research aims to analyze sentiments toward bamboo charcoal on social media, with a focus on public perception in the global market in English. Using data collected from the social media platform X, this study applies various machine learning algorithms, including Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Deep Learning, Naïve Bayes, Decision Tree, and Gradient Boosted Trees, with TF-IDF as the text representation. The analysis reveals that the SVM model achieved the most accurate result of 92.33%, demonstrating its effectiveness in sentiment detection. The study also found that the KNN model performed well, achieving an accuracy of 92.26%, although slightly lower than SVM. These findings highlight the growing interest in bamboo charcoal as a sustainable product, reflecting positive sentiments in the data. Additionally, the Deep Learning model also showed promising results, although it was slightly less effective than SVM and KNN. However, there were also notable concerns regarding the environmental impact of bamboo harvesting, which were primarily expressed in posts. The Decision Tree model, while useful, did not perform as well as the other models, indicating the need for further refinement. Future research could explore a broader range of social media platforms, models, and languages to gain a more comprehensive understanding of global perceptions. Furthermore, integrating sentiment analysis with real-time monitoring could help stakeholders respond more effectively to shifts in public opinion.
Predicting the Number of Passengers of MRT Jakarta Based on the Use of the QR-Code Payment Method during the Covid-19 Pandemic Using Long Short-Term Memory Jayadi, Riyanto; Indriasari, Taskia Fira; Chrisna, Charis; Fanuel, Putri Natasya; Afita, Rayhana
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8 No 2 (2022): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i2.2546

Abstract

The trend of using public transportation has been rising over the last several decades. Because of increased mobility, public transportation has now become more crucial. In modern environments, public transportation is not only used to carry people and products from one location to another but has also evolved into a service company. In Jakarta, Mass Rapid Transit Jakarta (MRTJ) started to operate in late 2019. Recently, they updated their payment gateway system with QR codes. In this study, we predicted the hourly influx of passengers who used QR codes as their preferred payment method. This research applied machine learning to perform a prediction methodology, which is proposed to predict the number of passengers using time-series analysis. The dataset contained 7760 instances across different hours and days in June 2020 and was reshaped to display the total number of passengers each hour. Next, we incorporated time-series regression alongside LSTM frameworks with variations in architecture. One architecture, the 1D CNN-LSTM, yielded a promising prediction error of only one to two passengers for every hour.
EVALUATION OF IT SERVICE MANAGEMENT IMPLEMENTATION RELATED TO INCIDENT MANAGEMENT WITH ITIL FRAMEWORK IN PT.XYZ Oktiviana, Liana; Jayadi, Riyanto
Jurnal Cahaya Mandalika ISSN 2721-4796 (online) Vol. 3 No. 3 (2022)
Publisher : Institut Penelitian Dan Pengambangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jcm.v3i3.1396

Abstract

Information Technology Service Management (ITSM) plays an important role for companies to be able to plan IT Service Management, especially in the implementation of Incident Management and Service Level Management (SLM). This study will discuss the evaluation of the maturity of the service operation domain in the management of information technology services belonging to PT.XYZ. The goal of this study is to measure and determine the maturity level of PT. XYZ related to incident management service in order to find out recommendations for the improvement of IT service management operations. The following procedures were to analyze the interpretation of the existing and the company condition, and provide recommendation lists of the corrective actions to overcome weaknesses and to create improvements in IT Service. Then the recommendations are formulated and refer to several processes that are not yet optimal. It is necessary to evaluate the measurement and recording of existing performance and services so that it can describe the performance that needs to be improved, reduced or eliminated if it is felt to be an obstacle to the progress of the PT. XYZ services related to the incident management.
Market Basket And Time Series Analysis: Case Study PT XYZ Sales Data Wildan, Muhammad; Rizieq Hentihu, Moh Thaha; Jayadi, Riyanto
Cerdika: Jurnal Ilmiah Indonesia Vol. 5 No. 2 (2025): Cerdika: Jurnal Ilmiah Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/cerdika.v5i2.2496

Abstract

PT. XYZ is a retail company that has been operating since 2015 in New York, which seeks to increase sales through attractive package bidding strategies and ensuring stock availability for the following month's highest-selling items. The project aims to analyze and forecast the items that will have the highest sales as well as provide package recommendations that can increase sales. The analysis was carried out using a machine learning model, with the Market Basket Analysis (MBA) method for package recommendations and the Auto Regressive Integrated Moving Average (ARIMA) for sales predictions. The results of the analysis show that the "USB-C Charging Cable" and "Bose SoundSport Headphones" have a strong association with the "Vareebadd Phone", which indicates the potential for increased sales if offered together. In addition, ARIMA's predictions suggest that the MacBook Pro Laptop will generate the highest revenue, with an average projection of around $788,067.45. Based on these findings, we recommend PT. XYZ is preparing a package offering for the Vareebadd Phone with USB-C Charging Cable and Bose SoundSport Headphones, as well as preparing stock for the MacBook Pro Laptop, to meet market demand and maximize revenue potential.
Evaluation of Pedulilindungi Applications in the Jabodetabek Region Kevin, Kevin; Jayadi, Riyanto
Journal of Economics and Business UBS Vol. 12 No. 1 (2023): Regular Issue
Publisher : Cv. Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52644/joeb.v12i1.138

Abstract

This paper will explain the result of evaluation using combination between technology acceptance model (TAM) and updated DeLone and McLean IS success model. The objective of this research is to analyze correlation between system quality, information quality, service quality, perceived risk, attitude, and actual use in moderation of age which is the factor influencing technology acceptance model of PeduliLindungi. The method of research is to analyze the relationship between variable stage before. The data collection techniques used in this paper is using questionnaire and Likert scale. The data analysis method in this study uses partial lease square (PLS) to do validity test, reliability test and hypothesis analysis. The result of this paper is the technology acceptance model of PeduliLindungi which has strong influence to increase users’ attitude that would increase users actual use.
Co-Authors . Suharjito Afita, Rayhana Agustine, Giovanni Ega Alvin Christian Asrol, Muhammad Chrisna, Charis Fanuel, Putri Natasya Indriasari, Taskia Fira Kevin kevin Muhammad Wildan Oktiviana, Liana Rizieq Hentihu, Moh Thaha Samosir, Paulima Tjhin, Jonathan Tandarma