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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization IJAIT (International Journal of Applied Information Technology) Journal of Appropriate Technology for Community Services JOURNAL of LEGAL RESEARCH Yayasan Cita Cendikiawan Al Khwarizmi JUSTIN (Jurnal Sistem dan Teknologi Informasi) NERO (Networking Engineering Research Operation) Journal of Intelligent Systems Technology and Informatics International Journal of Applied Information Systems and Informatics
Rachman, Andi Nur
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Application of Content-Based Filtering for Moisturizer Recommendation System Based on Skin Type Suitability Iswanto, Muhammad Edi; Latifah, Azzahra Putri; Rachman, Andi Nur; Tarempa, Genta Nazwar
Journal of Applied Information System and Informatic (JAISI) Vol 3, No 1 (2025): MEI 2025
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v3i1.15531

Abstract

Many users face significant challenges when trying to select the most suitable moisturizer for their skin. This difficulty often arises due to the overwhelming variety of available products on the market, combined with a lack of personalized information that could guide users toward the best choice. To address this issue, the present study aims to develop a recommendation system based on the Content-Based Filtering approach, which is specifically designed to align the benefits of moisturizer products with the unique needs of users' skin types. The data for this study were collected manually from 17 moisturizer products featured on the Sociolla e-commerce platform. Each product was carefully analyzed according to the descriptive information provided, including the benefits claimed and the skin types for which the product is recommended. The methodology involved several important steps: preprocessing the text from product descriptions, applying TF-IDF to assign term weights, and calculating cosine similarity scores between the user’s skin profile and product attributes. The analysis revealed that products such as D10 and D6, which yielded the highest similarity values, are strongly aligned with particular skin types. The resulting system demonstrates its ability to generate relevant and personalized product suggestions without the need for prior user preference data. This study concludes that using descriptive content as the foundation for recommendation logic can significantly enhance accuracy and targeting. Future enhancements may involve expanding the product database, integrating user-generated reviews, and leveraging machine learning techniques to produce even more adaptive and intelligent recommendations.
Information Technology Governance Assessment Using The Cobit 2019 Framework and ISO/IEC 38500 at RSUD XYZ Azzahra, Berliana; Rachman, Andi Nur; Fitriani Dewi, Euis Nur
Journal of Applied Information System and Informatic (JAISI) Vol 2, No 2 (2024): November 2024
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v2i2.12722

Abstract

The advancement of Information Technology (IT) is a crucial prerequisite for bolstering the efficacy and efficiency of organizational operations, encompassing healthcare establishments like RSUD XYZ. But problems like unreliable networks, antiquated computers, and a lack of IT knowledge in human resources (HR) arise. Therefore, to guarantee efficient IT usage, a thorough IT governance assessment is required. In order to help overcome current challenges, this study intends to assess IT governance at RSUD XYZ utilizing the COBIT 2019 framework and ISO 38500 standards.Three primary processes are assessed using the Capability Maturity Model Integration (CMMI) framework: Ensured Risk Optimisation (EDM03), Managed Risk (APO12), and Human Resources (APO07). According to the evaluation results, APO07 successfully attained level 4 as intended, APO12 was at level 3 of goal 5, and the EDM03 process was at level 2 of target 4. The identified competency gaps formed the basis for the preparation of improvement recommendations. In addition, this research also proposes introducing other processes such as ITIL for IT service management and TOGAF integration to support enterprise architecture.It is anticipated that these findings would enable agencies to strengthen their IT governance capacities in order to minimize current gaps and meet more ideal goals. This study offers RSUD XYZ thorough guidelines for enhancing more effective and efficient IT governance, hence facilitating the integration of IT plans with hospital business objectives.
Implementation Of C5.0 Classification And Support Vector Machine Algorithm With Correlation-Based Feature Selection In Application Liver Disease Rachman, Andi Nur; Ramdani, Cecep Muhamad Sidik; Insani, Muhammad Hanif
Journal of Applied Information System and Informatic (JAISI) Vol 2, No 1 (2024): Mei 2024
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v2i1.10848

Abstract

Liver disease is a general term that refers to a number of disorders or problems that affect the liver. The liver is an important organ in the human body and has many diverse functions, including food processing, protein production, toxin removal, and energy storage. Therefore, when the liver experiences disorders or disease, it can have a serious impact on the overall health and function of the body. Liver disease is a significant global health problem. Early detection as well as classification of liver disease can provide valuable guidance for effective treatment. Based on the problems above, the aim of this research is to create a liver disease classification model using C5.0 and Support Vector Machine with Radial Basis Function (RBF) and Sigmoid kernels. With data obtained from the liver disease dataset. The two methods will be compared and we will find out which one produces the best results. The method used is also optimized with CFS (Correlation Based Feature Selection) feature selection. The results of the classification process, namely the C5.0 Model and Support Vector Machine (RBF) with CFS have a similar accuracy of 76%, while the Support Vector Machine (Sigmoid) has an accuracy of 70%, without feature selection the C5.0 algorithm has an accuracy of 66% , Support Vector Machine between RBF and sigmoid kernels has an accuracy of 69% and 55%.
IMPLEMENTATION OF ANALYTICAL HIERARCHY PROCESS (AHP) IN DETERMINING CRITERIA FOR NEW HOUSING DEVELOPMENT AND BEST LOCATIONS IN TASIKMALAYA CITY Nugraha, Muhammad Bisma; Rachman, Andi Nur; Fitriani Dewi, Euis Nur
Journal of Applied Information System and Informatic (JAISI) Vol 2, No 2 (2024): November 2024
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v2i2.13261

Abstract

The growth in the number of households with access to decent and affordable housing in Tasikmalaya City continues to increase. This indicates that housing development in Tasikmalaya City is undergoing significant progress. The criteria for selecting housing vary widely, depending on the priorities of each individual, in line with their expectations for the housing they will live in. These varied choices present challenges for both housing developers and the public in determining the criteria and location of housing. This study aims to develop an information system that can support housing development in new housing projects in Tasikmalaya City. This goal is achieved by creating a Decision Support System (DSS) that considers all housing selection criteria to accelerate and simplify the decision-making process, using the Analytical Hierarchy Process (AHP) method. The research findings indicate that the risk criterion is the highest priority according to the views of stakeholders and the general public, while the design criterion is given the least priority. Information based on selected criteria can be accessed through the "Sistem Masa Depan" (SIMADEP) application, which assists users in making informed decisions.Keywords: Analytical Hierarchy Process (AHP), Decision Support System (DSS), Housing
Designing UI/UX For SDN 1 Sukamulya Ciamis Website Using the Five Planes and WEBUSE Methodologies Gumilah, Dena Surya; Rachman, Andi Nur; Aldya, Aldy Putra
Journal of Applied Information System and Informatic (JAISI) Vol 1, No 1 (2023): November 2023
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v1i1.8994

Abstract

The web-based information world is currently experiencing rapid growth, encompassing interactive, dynamic, and static elements, with educational institutions being one of its prominent users. It provides swift and precise information services, contributing significantly to the fundamental development of the education sector. The school profile website from the Ministry of Education and Culture (KEMENDIKBUD) currently only provides basic profile features. Due to the lack of information and features on the website, a redesign and further development are necessary. Therefore, this research, based on interviews with relevant parties such as SDN 1 Sukamulya, calls for a redesign and development of the website. The approach taken in this redesign and development utilizes the Five Plans method. The creation of a website that aligns with user preferences, combines an attractive design, and offers an experience that meets user needs. The design and development of this website will be evaluated using the WEBUSE method. WEBUSE (Web Usability Evaluation) is a method for assessing the extent of usability based on a comprehensive usability criteria questionnaire. In the UI/UX design phase, the Five Planes method was applied, and after the design phase, the website's feasibility was assessed using the WEBUSE method. This research successfully designed a website for SDN 1 Sukamulya by applying the Five Planes method in the design process. Based on the comparison of evaluations using the WEBUSE method, the usability score of the website improved from a usability score of 0.657, falling into the "good" range (0.6 - 0.8), to a usability score of 0.829, falling into the "excellent" range (0.8 - 1). This score indicates that the website's usability level is excellent, demonstrating that the design and development efforts have successfully provided an outstanding user experience.
Implementation of Convolutional Neural Network and Long Short-Term Memory Algorithms in Human Activity Recognition Based on Visual Processing Video Rachman, Andi Nur; Mubarok, Husni; Fitriani Dewi, Euis Nur; Edwinda Putra, Rama
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1504

Abstract

Human Activity Recognition (HAR) is an interesting research topic, especially in identifying human movement actions focusing on video-based security surveillance. Symptom of an illness from a movement. The use of HAR in this research is the key to better understanding the various semantics contained in the video to find out the pattern of a human movement, especially in sports movements. In this study, a combination of the CNN and LSTM method algorithms was applied by using several variations of the model parameter values on the dropout layer and batch size to convert the pattern in the video into image form to produce a HAR model. Data processing at the convolution layer is used to extract spatial features in the frame. The extraction results are fed to the LSTM layer on each network for modeling the temporal sequence of human movement. In this way, the network on the model will learn spatiotemporal features directly in end-to-end data training tests to produce a robust model. The test data used are 10 sports activities obtained from related research from the University of Central Florida (UCF). The results showed that the performance was quite good, although there were still errors in the classification of sports activities because they had similarities in the movements of the activities carried out. The classification results show a loss value of 0.4 and an accuracy of 0.94. In further research, what needs to be corrected is the loss value which is still high so that several times the test results show an error in the classification of sports activities that have similarities in the movements of the activities.
Load Testing-Based Performance Evaluation of the SiUKT API System Rachman, Andi Nur; Shofa, Rahmi Nur; Sjamsuddin, Irfan Nafis; Tarempa, Genta Najwar; Julianto, Indri Tri; Athoillah , Bifahmi Ahmad
Journal of Intelligent Systems Technology and Informatics Vol 2 No 1 (2026): JISTICS, March 2026
Publisher : Aliansi Peneliti Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64878/jistics.v2i1.89

Abstract

Software testing is a crucial stage in the system development lifecycle. Previous studies on SiUKT have used only the black-box method, focusing on functionality without providing insights into performance optimization. This study aims to analyze and improve the performance of the SiUKT API using an intelligent load-testing approach with Apache JMeter. The testing measures three key indicators—response time, throughput, and error rate—across 10 API endpoints with concurrent user simulations of 10, 100, 250, and 500 users. The results show that the SiUKT website performs effectively under moderate load conditions, with an average response time of 338 ms and a throughput of 8.2 requests per second for 10 users. Under high load (500 users), performance declines, with response times ranging from 6 to 8 seconds, while throughput remains stable and the error rate stays at 0.00%. Only the register endpoint experienced a 100% error rate due to validation conflicts. These findings demonstrate the system's ability to maintain stability under varying loads and highlight performance degradation patterns as user traffic increases. The research contributes to the optimization of intelligent system performance by establishing quantitative benchmarks for API scalability and providing recommendations for adaptive infrastructure improvements to support automated intelligent load management.
Flood mapping using Res-Q and machine learning on imbalanced data Yuliyanti, Siti; Purwayoga, Vega; Rachman, Andi Nur; Gusnadi, Zakwan
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.10374

Abstract

Flood disaster mapping requires accurate methods to support early warning and mitigation planning. To address common issues such as imbalanced data distribution and limited attribute handling, this study proposes an improved approach. The methodology includes: i) modification of the spatial sort filter skyline method with reverse normalization based on attribute preferences, applied when an attribute has minimal preference to ensure balanced consideration during skyline filtering; ii) data labeling and balancing, where initial flood potential labeling is generated using Res-Q, followed by K-Means clustering to group data into four classes (low, moderate, high, and very high) and SMOTE to further balance the dataset with 558 data points per class; iii) model evaluation using the C5.0 algorithm under three schemes, showing high and consistent accuracy with 89.24% on imbalanced data (Schema 2) and 93.3% on balanced data (Schema 3), while Schema 1 shows overfitting due to extreme imbalance; and iv) the main contribution, integrating reverse normalization with skyline filtering combined with clustering and resampling, enhancing both accuracy and robustness in identifying flood-prone areas. This structured approach highlights methodological improvements, reliable results, and practical contributions for effective flood disaster management.
Co-Authors Acep Irham Gufroni Al Husaini, Muhammad Alam Rahmatulloh Aldya, Aldy Putra Alwin, Muhammad ANWAR, FAHMI Athoillah , Bifahmi Ahmad Azim, Muhammad Fauzan Azzahra, Berliana Dewi , Euis Nur Fitriani Dewi, Euis Nur Fitriani Edwinda Putra, Rama Fiitriani Dewi, Euis Nur Fitriani Dewi, Euis Nur Genta Nazwar Tarempa Gumilah, Dena Surya Guna, Nandana Surya Harahap, Rizky Maulana Hidayat, Eka Wahyu Husni Mubarok Indri Tri Julianto Insani, Muhammad Hanif Irani Hoeronis Iswanto, Muhammad Edi Latifah, Azzahra Putri Lukmana, Hen Hen Mujar Ibnu Syarif Nafis Sjamsuddin, Irfan Noorsyabani, Fauzi Nugraha, Muhammad Bisma Nur Fajar Nur Shofa, Rahmi Purwayoga, Vega Rahmat, Biki Zulfikri Ramdani, Cecep Muhamad Sidik Rindiawan, Selvina Zalfa Shofa, Rahmi Nur Sidik Firmadi, Sidik Sidik Ramdani, Cecep Muhamad Siti Yuliyanti, Siti Sulastri , Heni Sulastri, Heni Tarempa, Genta Najwar Zakwan Gusnadi