The Role of Consumer Ethnocentrism, Perceived Quality, Perceived Price, and Perceived Brand Image on Willingness to Buy Erigo Clothing

The initial survey findings revealed that Indonesian consumers prefer supporting local brands but are reluctant to purchase them if the prices exceed those of foreign brands. Additionally, they are open to foreign brands effectively marketed in Indonesia. This study examines and analyzes the impact of consumer ethnocentrism, perceived quality, perceived price, and perceived brand image on the willingness to purchase Erigo apparel. Employing a quantitative approach, the study used PLS-SEM as the data analysis method with SmartPLS software. Non-probability purposive sampling was utilized to gather responses from 192 participants via Google Forms. The study uncovered a positive and significant influence of consumer ethnocentrism, perceived price, and perceived brand image on the willingness to buy Erigo apparel. However, perceived quality had a positive but statistically non-significant impact on this willingness. The managerial contribution includes Erigo's leveraging consumer ethnocentrism by promoting local craftsmanship and cultural diversity, enhancing its pricing strategy to reflect value, and strategically building a positive brand image to stand out against foreign competitors. Focused campaigns, fair pricing, and active social media engagement can significantly boost consumer interest in purchasing Erigo clothing

Peran Quality Assurance pada PT Infomedia Nusantara

PT Infomedia Nusantara merupakan subsidiary company dari Telkom Group yang berfokus pada layanan Business Process Outsourcing. Adapun sebagian besar dari proyek IT yang dikembangkan oleh PT Infomedia Nusantara berkaitan dengan proses perancangan dan pengembangan aplikasi baik aplikasi berbasis website maupun mobile. Tentunya, proses perancangan dan pengembangan tersebut tidak terlepas dari peranan fundamental dari Quality Assurance dimana peranan Quality Assurance juga berpengaruh pada keberhasilan proyek. Quality Assurance bertanggung jawab dalam melakukan analisa sistem, melakukan pengujian terhadap sistem, dan pembuatan dokumen sebagai pendukung proses bisnis dan proses pengembangan aplikasi. Program kerja magang dilakukan secara online di PT Infomedia Nusantara. Dalam periode 40 hari kerja, tepatnya dari tanggal 30 Agustus 2021 hingga tanggal 24 Oktober 2021, waktu kerja magang berlangsung selama 9 jam kerja per harinya. Praktik kerja magang sebagai Quality Assurance Intern tersebut dilaksanakan di divisi IT Application and Development, tepatnya pada departemen IT SSO. Selama proses kerja magang, mahasiswa bertanggung jawab dalam melakukan pembuatan dokumen User Acceptance Testing (UAT), Business Requirement Document (BRD), dan dokumen user manual. Pembuatan dokumen tersebut dilakukan guna menunjang sejumlah proyek pengembangan aplikasi seperti proyek pengembangan aplikasi TokoPerhutani, Dashboard PDAM, Portal Diana, dan Portal FCBP01. Hasil yang diperoleh selama proses kerja magang berlangsung adalah meningkatkan pengetahuan terkait dengan flow sistem aplikasi dan meningkatkan pengetahuan terkait ruang lingkup kerja Quality Assurance secara nyata

Analisis Keputusan Pembelian Konsumen Frozen Food Berdasarkan Kontribusi Brand Image, Harga dan Promosi (Studi Kasus pada Produk Frozen Food So Good)

Penting untuk mengetahui faktor apa yang dipertimbangkan oleh konsumen dalam memutuskan pembelian. Terdapat tiga faktor atau variabel yang diteliti dalam penelitian ini yakni brand image, harga dan promosi yang secara teoritis merupakan variabel yang dipertimbangkan konsumen. Untuk itu dilakukan penelitian dengan teknik pengambilan sampel menggunakan probability sampling dengan pendekatan accidental sampling. Sedangkan jumlah sampel ditentukan rumus lemeshow (p = 50% dan d = 8%) diperoleh sejumlah 150 sampal. Metode analisis data menggunakan analisis regresi linier berganda. Pengumpulan data utama dilakukan dengan kuesioner skala likert. Adapun hasil penelitian yang diperoleh menunjukkan bahwa brand image, harga, dan promosi masing-masing memberikan pengaruh secara positif dan signifikan terhadap keputusan pembelian. Pengaruh bersama atau secara simultan dari ketiga variabel tersebut cukup rendah yaitu 40,40% atau dengan perkataan lain, masih lebih banyak pengaruh faktor lain terhadap keputusan pembelian konsumen untuk membeli produk frozen food So Good. Â

Analisis Komparatif Convolutional Neural Network dan Bidirectional Long Short-Term Memory dalam Mendeteksi Hoaks COVID-19 pada Twitter

Pesatnya perkembangan internet dan sosial media tidak hanya memberikan dampak positif, melainkan juga dampak negatif. Salah satunya ialah adanya potensi penyebaran hoaks. Sulit terdeteksinya hoaks menjadi tantangan tersendiri bagi masyarakat. Permasalahan hoaks menjadi semakin krusial terutama ketika dikaitkan dengan bidang kesehatan seperti COVID-19. Hoaks terkait COVID-19 tidak hanya dapat membahayakan kesehatan fisik, tetapi juga kesehatan mental masyarakat. Guna menghadapi permasalahan tersebut, dilakukan penelitian analisis komparatif untuk membandingkan kinerja Convolutional Neural Network dan Bidirectional Long Short-Term Memory dalam mendeteksi hoaks COVID-19. Penelitian dilakukan dengan bertitik tolak pada CRISP-DM framework. Deteksi hoaks dilakukan dengan menggunakan dataset CTF yang dikumpulkan melalui metode pengumpulan data sekunder dimana dataset tersebut memuat data berlabel "fake" dan data berlabel "genuine" dalam jumlah yang seimbang. Hasil penelitian menunjukkan bahwa penggunaan algoritma Convolutional Neural Network mengungguli algoritma Bidirectional Long Short-Term Memory dengan nilai accuracy sebesar 93.75%, precision sebesar 93.10%, recall sebesar 94.50%, dan f1-score sebesar 93.80% dengan waktu training selama 6 menit 22 detik. Dengan adanya penelitian ini, diharapkan dapat digunakan untuk mendeteksi hoaks sedini mungkin sehingga penyebaran hoaks COVID-19 dalam masyarakat dapat diminimalkan

Scalar-on-Function Regression: Estimation and Inference Under Complex Survey Designs

Increasingly, large, nationally representative health and behavioral surveys conducted under a multistage stratified sampling scheme collect high dimensional data with correlation structured along some domain (eg, wearable sensor data measured continuously and correlated over time, imaging data with spatiotemporal correlation) with the goal of associating these data with health outcomes. Analysis of this sort requires novel methodologic work at the intersection of survey statistics and functional data analysis. Here, we address this crucial gap in the literature by proposing an estimation and inferential framework for generalizable scalar-on-function regression models for data collected under a complex survey design. We propose to: (1) estimate functional regression coefficients using weighted score equations; and (2) perform inference using novel functional balanced repeated replication and survey-weighted bootstrap for multistage survey designs. This is the first frequentist study to discuss the estimation of scalar-on-function regression models in the context of complex survey studies and to assess the validity of various inferential techniques based on re-sampling methods via a comprehensive simulation study. We implement our methods to predict mortality using diurnal activity profiles measured via wearable accelerometers using the National Health and Nutrition Examination Survey 2003-2006 data. The proposed computationally efficient methods are implemented in R software package surveySoFR

Logistic Regression Prediction Model for Cardiovascular Disease

It is undeniable that cardiovascular disease is the number one cause of death in the world. Various factors such as age, cholesterol level, and unhealthy lifestyle can trigger cardiovascular disease. The symptoms of cardiovascular disease are also challenging to identify. It takes careful understanding and analysis related to patient medical record data and identification of the parameters that cause this disease. This study was conducted to predict the main factors causing cardiovascular disease. In this study, a dataset consisting of 14 attributes with class labels was used as the basis for identification as a link between factors that cause cardiovascular disease. The research area used is the area of analysis data where the analyzed data are on factors that influence the presence of cardiovascular disease in the State of Cleveland. In predicting cardiovascular disease, a logistic regression algorithm will be used to see the interrelation between the dependent variable and the independent variables involved. With this research, it is expected to be able to increase readers' knowledge and insight related to how to analyze cardiovascular disease using logistic regression algorithms and the main factors that cause cardiovascular disease

Study on the Level of Strenght Development in Vocational Training Students

The present work is a study that tracks the level of development of the force of the lower limbs, upper limbs, abdominal muscles but also posterior muscles of the trunk. The research started at the beginning of the current school year and was carried out on the students of the ninth and tenth grades from the Technological High School I. C. Bratianu, from the vocational education. The students from the X-th grade who expressed their agreement to participate in our study were 22, who participated in the 3 modules of school activity in the two hours of physical education weekly. The subjects in the ninth grade who participated in the physical tests were 30 in number