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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) SEEIJ (Social Economics and Ecology International Journal) Entrepreneurship Bisnis Manajemen Akuntansi (E-BISMA) Priviet Social Sciences Journal
Rahayu, Cindy
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Digital Marketing Strategy to Enhance the Competitiveness of Muslim Fashion SMEs: : A Case Study of Yabunaya Muslim Store Rahayu, Cindy; Christanti, Yunitasari; widjaja, Nathanael
SEEIJ (Social Economics and Ecology International Journal) Vol. 8 No. 1 (2024): March
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/seeij.v8i1.11375

Abstract

Tenun Ikat Troso, an indigenous weaving craft originating from Jepara, specifically Troso village, involves the intricate process of weaving fabric from warp and weft threads that are initially tied and dyed using natural pigments. The weaving apparatus employed for this task is the automated power loom (ATBM) (Ismanto, Tamrin, & Pebruary, 2018). The enterprising Mrs. Rahayu, who owns UMKM Yabunaya Muslim Store, embarked on her business journey in 2017. She ventured into both selling and personally manufacturing modest dresses, utilizing an assortment of Indonesian textiles, including batik prints, stamped batik (batik cap), hand-drawn batik (batik tulis), a fusion of stamped and hand-drawn batik, and handwoven fabrics created using traditional weaving tools. Mrs. Rahayu, equipped with skills acquired through private fashion courses under the guidance of industry experts at the Susan Budiharjo School (Cikini), financed her endeavors independently without any business partners. Notably, her designs remain authentically original, with no replication of other designer products. UMKM Yabunaya Muslim Store has diversified its fabric sourcing, encompassing batik fabrics from Solo, Riau, Madura, Pekalongan, Kebumen, woven fabrics from Troso, Jepara, and sasirangan fabrics from Kalimantan. The store has successfully produced approximately 60 sets of batik, Troso woven fabrics, and sasirangan dresses. Mrs. Rahayu has actively participated in exhibitions and bazaars, maintaining a strong online presence through Google My Business, while also effectively marketing her products on platforms like Instagram, Facebook, and various other social media channels.
Pneumonia prediction on chest x-ray images using deep learning approach Puspita, Rani; Rahayu, Cindy
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i1.pp467-474

Abstract

Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. In many cases, this disease causes pneumonia. Since pulmonary infections can be observed through radiography images, this paper investigates deep learning methods for automatically analyzing query chest x-ray images. In deep learning, computers can automatically identify useful features for the model, directly from the raw data, bypassing the difficult step of manual information refinement. The main part of the deep learning method is the focus on automatically learning data representations. Visual geometry group 16 (VGG16) and DenseNet121 are methods in deep learning. The data used is a chest x-ray of pneumonia. Data is divided into training, testing, and validation. The best method for this research case is VGG16 with 93% accuracy training and 90% accuracy testing. In this study, DenseNet121 obtained accuracy below VGG16, with 92% accuracy in training and 88% for accuracy testing. Parameters have a significant influence on the accuracy of each model, and with the parameters that have been used, the VGG16 is a method that has high accuracy and can be used to predict chest x-ray images aimed at checking pneumonia in patients. 
Implementing brain tumor detection using various machine learning techniques Puspita, Rani; Rahayu, Cindy
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp3309-3318

Abstract

The brain is a very complex organ of the human body. One of the brain diseases is a tumor. Brain tumors are caused by uncontrolled cell growth. Early recognition, classification and analysis of brain tumors is very important to find out whether there is a tumor in a person's brain so it is important for us to do this in order to treat the tumor thoroughly. Machine learning (ML) techniques that have the highest accuracy in detecting the health sector are extreme gradient boosting (XGBoost), logistic regression, random forest, k-nearest neighbor (KNN), naive Bayes, and support vector machine (SVM). In this research, data collection and exploration were carried out, data training using six methods, and evaluation using a confusion matrix. After conducting the experiment, it was obtained that random forest had the highest accuracy, namely 98.41%. Where XGBoost obtained an accuracy of 98.14%, logistic regression obtained an accuracy of 97.34%, KNN and naive Bayes of 97.34%, and SVM of 97.88%.
Mewujudkan pendidikan berkualitas pasca pandemi Covid-19: praktek kepemimpinan digital dan kinerja tenaga pengajar Lestari, Indah Ria; Rumangkit, Stefanus; Larasati, Hasna; Rahayu, Cindy
Entrepreneurship Bisnis Manajemen Akuntansi (E-BISMA) Vol.5, No.1 (2024): June 2024
Publisher : Universitas Widya Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37631/ebisma.v5i1.1222

Abstract

The Covid-19 pandemic has forced educational institutions to transform teaching through digital-based learning. This is a big challenge for educational institutions and the government in realizing quality education. The aim of this research is to analyze the application of visionary leadership, digital-based learning culture, digital citizenship, innovation skills, communication, digital leadership, digital-based knowledge sharing, and the performance of teaching staff in Indonesia. Primary data was obtained from the results of a questionnaire survey of 100 active teachers and lecturers spread across eight provinces in Indonesia. The survey was conducted directly and online using a quantitative approach and analyzed descriptively. The sampling technique was carried out using the convenience sampling method. The research results showed that the application of visionary leadership, digital-based learning culture, digital citizenship, innovation skills and communication in the workplace has gone well even though there are still a number of schools that do not have digital learning facilities. The strategy that schools and universities must implement to improve the performance of teaching staff in the digital era is to fulfill the physical and non-physical facilities in schools.
The influence of work ethic, organizational commitment, and self-actualization on employee performance at PT. Dipo Internasional Pahala Otomotif Hutagalung, Calvin; Rahayu, Cindy; Thedora, Hanny; Cenneth, Reynard Nathaniel; Rostina, Cut Fitri; Fauzi, Fauzi
Priviet Social Sciences Journal Vol. 4 No. 8 (2024): August 2024
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v4i8.328

Abstract

This study aims to evaluate the impact of work ethic, organizational commitment, and self-actualization on employee performance. The research adopts a descriptive quantitative approach, with data collection conducted through questionnaires distributed to company employees. The study sample comprises 40 employees, while validity and reliability tests were conducted with 30 respondents. The validity and reliability tests, along with the plot test involving 30 respondents, met the criteria, with values exceeding 0.05 and Cronbach's alpha above 0.60. Data analysis was performed using multiple linear regression. The results of the simultaneous determination coefficient test (F-test) revealed an F-value of 11.178, which is higher than the F-table value of 2.87, with a significance value (Sig) of 0.000, indicating a positive and significant influence of work ethic, organizational commitment, and self-actualization on employee performance. Partially (t-test), work ethic and organizational commitment were found to have a positive and significant effect on employee performance, while self-actualization did not show a significant impact. Additionally, the determination coefficient test results indicated that the influence of work ethic, organizational commitment, and self-actualization on employee performance accounts for only 43.9%, with the remaining 56.1% influenced by other variables.
Co-Authors Cenneth, Reynard Nathaniel Christanti, Yunitasari Fauzi Fauzi Hutagalung, Calvin Indah Ria Lestari, Indah Ria Larasati, Hasna Rani Puspita Rostina, Cut Fitri Rumangkit, Stefanus Thedora, Hanny widjaja, Nathanael