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  • Implementation of the K-Means Clustering Technique Using RFM Attributes to Enhance Donor Retention at Masjid Nusantara

    Authors: Iqbal Muhammad Farisi, Sri Supatmi

    DOI: 10.1109/INCITEST64888.2024.11121472

    Abstract

    The efforts aimed at donor retention are a fundamental aspect of Customer Relationship Management (CRM) strategies that enhance organizational effectiveness. This research concentrated on entities that have traditionally emphasized the acquisition of new donors over the retention of current donors, a methodology that can hinder long-term viability. By categorizing donors and formulating targeted retention strategies, this research seeks to redirect the emphases from donor acquisition to retention, by using the K -Means clustering methodology along with the RFM (Recency, Frequency, Monetary) framework. The descriptive research adopting a quantitative paradigm followed the CRISP-DM process, which included the data selection, preprocessing, transformation, processing, and analysis stages. The data analysis found four distinct clusters of donors, each of which is equipped with customized retention strategies based on their respective RFM scores. These strategies of retention contribute to pragmatic outcomes by empowering organizations to increase donor loyalty, improve donor engagement, and ultimately, facilitate their mission of building and maintaining mosques. This study demonstrates that prioritizing donor retention, which is supported by an empirically based methodology, has potential to enhance an organization’s performance and sustainable success. © 2024 IEEE.

    Author keywords

    CRISP-DM; CRM; Data Analysis; Donor Retention; K-Means Clustering; RFM

    This article can be accessed at https://www.scopus.com/pages/publications/105015849404

  • A Spherical Fuzzy TOPSIS Entropy Weighted for Failure Mode and Effects Analysis

    Authors: Gabriel Sianturi; Agus Riyanto; M. Yani Syafei; Julian Robecca; Alam Santosa

    DOI: 10.1109/INCITEST59455.2023.10396868

    Abstract

    The aim of this paper is to implement a Spherical Fuzzy Sets (SFS) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach in the Failure Mode and Effects Analysis (FMEA) process. The SFS can provide a larger domain for decision-makers to assign independent membership degrees, non-membership degrees, and hesitancy degrees. The SFS are combined with TOPSIS to obtain the rank all of the failure modes with respect to their distances to ideal solutions and relative closeness ratios. In addition, the entropy objective weight for SFS is integrated into SFS TOPSIS for determining the risk factors weights. The proposed approach is utilized to prioritize and rank the potential failure of an injection molding machine. The implementation of SFS-TOPSIS and entropy objective weight approach can overcome the vagueness and uncertainty of data during FMEA evaluation process and improve FMEA to be more flexible and reasonable. © 2023 IEEE.

    Author keywords

    entropy; fmea; injection molding; spherical fuzzy sets; topsis

    This article can be accessed at: https://www.scopus.com/pages/publications/85185197336

  • Innovative Batik NFTs Using Deep Neural Networks

    by Redefine Digital Art and Photography

    Authors: Yeffry Handoko Putra; Rahma Wahdiniwaty; Rini Maulina; Noorihan Abdul Rahman; Zuriani Ahmad Zukarnain; Wan Fariza Abdul Rahman

    DOI: 10.1109/INCITEST64888.2024.11121421

    Abstract

    Batik is an important part of Indonesia’s culture. It is known for its detailed repeating designs. Repeating designs are tough for designers, especially when they to mix in modern styles. Still, more people online are getting excited about making unique batik patterns. With new tech, like deep learning, things have changed. These models are doing better than the old ways for tasks like classifying images and recognizing objects. One cool tech, called pix2pix, helps turn one image into another using a method called Conditional Generative Adversarial Networks (cGAN). It uses data sets with images along with their edge maps that get pulled using techniques like Canny Edge Detection in OpenCV. This means that it can help create complex batik designs. This study also looks at Non-Fungible Tokens (NFTs) and how they can help sell and keep batik art safe. By turning batik designs into NFTs, artists can prove their work is accurate and connect with fans all over the world. This fresh idea not only keeps Indonesia’s rich culture alive but also lets people on the internet and batik lovers join in the creative fun. More chances exist for people to work together and explore digital art while saving their cultural heritage. Looking ahead, the Batik patterns created can become NFTs. This means that each Batik pattern’s uniqueness and ownership can be clearly shown through blockchain tech. It opens up a digital marketplace where folks can buy, sell, or collect these digital art pieces. Adding NFTs gives more value and realness to the Batik patterns made using advanced deep-learning methods. This broadens how this research could be used and its effect in the digital world. © 2024 IEEE.

    Author keywords

    batik; cultural preservation; deep learning; non-fungible tokens (NFTS)

    Indexed keywords

    Engineering controlled terms

    Arts computing; Edge detection; Electronic commerce; Historic preservation; Learning systems; Photography

    Engineering uncontrolled terms

    Adversarial networks; Batik; Cultural preservation; Data set; Deep learning; Digital art; Digital photography; Indonesia; Neural-networks; Non-fungible token

    Engineering main heading

    Deep neural networks

  • K-Means Clustering for Crime Cluster Analysis in District Prosecution Office of Indramayu

    K-Means Clustering for Crime Cluster Analysis in District Prosecution Office of Indramayu

    Author: Aditya Erlangga, Rizky Bani Asmara E.M., Raudatussholihat Amalia, Estiko Rijanto

    DOI: 10.1109/INCITEST59455.2023.10396984

    Abstract

    Crime is a criminal behavior that often causes problems in society with a variety of crimes that often occur such as murder, assault, rape, theft, fraud, embezzlement, narcotics and. In Article 35 paragraph (1) letter K of Law No. 16 of 2004 concerning the Attorney General of the Republic of Indonesia as amended in Law No. 11 of 2021 states that the Prosecution Office is a government institution whose function is related to judicial power to prosecute and other power abide by law. K-Algorithm Means is a non-hierarchical clustering algorithm that has capability to group data in large quantity, quickly and efficiently. In this paper, data from 217 cases tested from Indramayu District Attorney during January 2022 until December 2022. K-Means algorithm was successful to classify relationship between criminal cases and which prosecutors whom handling them. The result using optimal K=3 formed three cluster which consists of Cluster C1 = 9 types of cases, Cluster C2 = 9 types of cases Cluster C3 = 9 types cases with members C2 and C3 have the Global Unique, Domination, and Share characteristics within each cluster. © 2023 IEEE.

    Keywords: clustering; crime; K-Means; prosecutor

    This article can be accessed at https://www.scopus.com/pages/publications/85185198398

  • Presentation of Strategic Information in the Agriculture Domain at the Agriculture Office of Garut Regency using Data Visualization

    Authors: Muhammad Jafar Shidik; Eddy Soeryanto Soegoto; Dian Dharmayanti; Lia Warlina

    Abstract

    The purpose of this research is to produce the right visualization to help the Food Crops Sector obtain the information needed more quickly. The form of information presentation uses tables in Microsoft Excel, resulting in the field of food crops taking longer to get information. So that it hampers the understanding of information and policymaking. The method used in this research is data visualization. Based on research on data visualization, it is stated that effective data presentation is by transforming data into visual form. This research produces a visualization design and is implemented in the form of a prototype. The next stage is to test the results of the prototype using the usability testing method for food crop staff. Based on the test results, it can be concluded that the prototype of food crop data visualization can help the food crop field understand the information needed more quickly. © 2023 IEEE.

    Author keywords

    agriculture; data visualization; food crops; usabillity test; visualization

    This article can be accessed at: https://www.scopus.com/pages/publications/85185200989

  • Web-Based Information System of Mail Archiving

    Authors: Rizky Jumansyah, Nizar Rabbi Radilya, Eddy Soeryanto Soegoto, Brandon Nathanael Meliala

    DOI: 10.1109/INCITEST64888.2024.11121430

    Abstract

    Archives have an important role so that administrative processes in the company can run effectively and efficiently. The process of finding and saving documents will not run well and create difficulties that can hinder the work process if the archives are not running optimally. The research aims at creating a web-based filing system that can help and prevent a very long process of processing the required documents. Data collection methods used in this research are interviews, observation, and documents. The results show that this system can help support the process of filing letters at Kesbangpol Kutai Barat. This study concludes that a web-based mail archiving information system can help and simplify the process of storing, searching for letters, so they are not easily damaged and lost. This research is expected to improve the performance of human resources. © 2024 IEEE.

    Author keywords

    administrative processes; information system; web-based

    This article can be accessed at https://www.scopus.com/pages/publications/105015815046

  • Enhancing Aspect Detection Using BLSTM and Random Oversampling in Marketplace Application Review

    Authors: Nelly Indriani Widiastuti; Bagus Perdana Yusuf; Kania Evita Dewi

    DOI: 10.1109/INCITEST59455.2023.10396931

    Abstract

    Aspect-based sentiment Analysis (ABSA) has been contributing to a more nuanced understanding of sentiment-related issues and offering enhanced opportunities for sentiment analysis. The number of aspects in data sets are often unbalanced. This causes results that tend towards the majority class and ignore the minority class This research uses Bi-LSTM to classify the aspects and sentiments because Bi-LSTM is able to handle problems in LSTM. The primary objective of this research was to assess the efficacy of the Bidirectional Long Short-Term Memory method in the context of Aspect-Based Sentiment Analysis applied to reviews of Marketplace applications and common problems in machine learning in unbalanced datasets. The preprocessing of input data involved word embedding through Word2Vec Continuous Bag of Words (CBOW). Primarily, the training dataset encompassed 2250 instances, while the test dataset comprised 750. The evaluation enclosed a comparative analysis involving the proposed method (Bi-LSTM+CBOW+ROS), on Bi-LSTM+CBOW, Bi- LSTM+CBOW+RUS and Bi-LSTM+CBOW+SMOTE. The test results show that the proposed method is superior to all comparison methods. Bi-LSTM+CBOW+ROS produces the highest accuracy, namely the usability aspect of 92.40%, the maximum precision is 98.03%, the maximum recall is 100% and the maximum f1-score is 98.68%. The Usability aspect got the best results for all the methods tested. © 2023 IEEE.

    Author keywords

    Aspect-based sentiment analysis; Bidirectional Long Short-term Memory; Random Oversampling; Word2Vec CBOW

    This article can be accessed at: https://www.scopus.com/pages/publications/85185201670

  • Designing High School Academic Information System Based on Android

    Authors: Agus Supandi Soegoto ; Yudistira Soegoto ; D S Soeikromo ; Candra Herdiana ; Seka Diasnoriga Koswara ; Mamed Seonggono Adji ; Agis Abhi Rafdhi ; Muhammad Nizar Nur Ikhsan

    DOI: 10.1109/INCITEST64888.2024.11121432

    Abstract

    This research aims to design mobile application for student academic development that can assist parents in monitoring their children. This research used a descriptive method. This android application is designed with an objectoriented approach, using the Prototype method. Then this application is made using Android Studio software, using the Java programming language, and the database using firebase. The results showed that the parents of students had difficulty in monitoring the academic development of their children. The parents of students can only see their children’s academic development when the report cards are distributed. An academic information system’s existence makes it easier for students’ parents to monitor their children’s academic development. © 2024 IEEE.

    Author keywords

    Android; high school academic; information system

    Indexed keywords

    Engineering controlled terms

    Application programs; Information systems; Information use; Mobile applications; Students

    Engineering uncontrolled terms

    Android; Android applications; High school academic; Higher School; Java programming; Mobile applications; Object oriented approach; Report cards

    Engineering main heading

    Android (operating system)

    This article can be accessed at https://www.scopus.com/pages/publications/105015859732

  • Designing High School Academic Information System Based on Android

    Authors: Agus Supandi Soegoto ; Yudistira Soegoto ; D S Soeikromo ; Candra Herdiana ; Seka Diasnoriga Koswara ; Mamed Seonggono Adji ; Agis Abhi Rafdhi ; Muhammad Nizar Nur Ikhsan

    DOI: 10.1109/INCITEST64888.2024.11121432

    Abstract

    This research aims to design mobile application for student academic development that can assist parents in monitoring their children. This research used a descriptive method. This android application is designed with an objectoriented approach, using the Prototype method. Then this application is made using Android Studio software, using the Java programming language, and the database using firebase. The results showed that the parents of students had difficulty in monitoring the academic development of their children. The parents of students can only see their children’s academic development when the report cards are distributed. An academic information system’s existence makes it easier for students’ parents to monitor their children’s academic development. © 2024 IEEE.

    Author keywords

    Android; high school academic; information system

    Indexed keywords

    Engineering controlled terms

    Application programs; Information systems; Information use; Mobile applications; Students

    Engineering uncontrolled terms

    Android; Android applications; High school academic; Higher School; Java programming; Mobile applications; Object oriented approach; Report cards

    Engineering main heading

    Android (operating system)

    This article can be accessed at https://www.scopus.com/pages/publications/105015859732

  • Design and Implementation of Virtual Laboratory Infrastructure for Indonesia Skill Competition using Cloud Computing

    Authors: Angga Friyanto; Susmini Indriani Lestariningati

    DOI: 10.1109/INCITEST59455.2023.10397061

    Abstract

    Indonesia Skill Competition, also known as “Lomba Kompetensi Siswa (LKS)”, is a vocational student skill competition program for students in 10th-12th grade. Students competes in a variety of competition categories. In the 2020 to 2022 academic year, due to the COVID-19 Pandemic, Committee designed an innovative and novel IT Network System Administration using Cloud Computing rather than cancelling the National Competition. The purpose of this paper is to show how to designed, implemented Virtual Laboratory using Cloud implementation. Competitor from their respective regions is connected via the Internet with Virtual Private Network access to Computer and Server Infrastructure that has been prepared by the committee according to the needs of the Test Project. During the competition, the competitor made configurations or settings directly on all servers and computers in Cloud Computing. Thus, even though the competition is held from their respective provinces, they can still maintain honesty and fairness because the competitor completes their work on a centralized cloud infrastructure under the supervision of the central committee. © 2023 IEEE.

    Author keywords

    Cloud Computing; IaaS; Virtual Lab

    This article can be accessed at: https://www.scopus.com/pages/publications/85185199477