Analisa Perbedaan Persepsi Antara Konsumen Perokok Dan Non Perokok Terhadap Ketersediaan Fasilitas Smoking Area Di Food Court

Pada saat ini jumlah perokok di Indonesia meningkat dilihat dari data WHO. Penelitian ini dilakukan untuk mengetahui perbedaan persepsi mengenai ketersedian fasilitas smoking area di food court dari konsumen perokok maupun konsumen non perokok. Data penelitian ini sudah memenuhi syarat uji validitas, uji reliabilitas, analisis deskriptif, uji beda, uji normalitas dan uji hipotesis. Hasil penelitian ini menunjukan bahwa faktor psikologi, image, dan fisik memiliki perbedaan yang signifikan terhadap setuju atau tidak setujunya konsumen perokok dan konsumen non perokok jika food court menyediakan fasilitas smoking area.At this time the number of smokers in Indonesian increased base on WHO data. This study was conducted to determine differences in perceptions about the availability smoking area facilities on the food court from smoker consumers and non smokers consumers. This research data has been qualified by validity test, reliability test, descriptive analysis, different test, normality test and hypothesis test. The results of these studies show that psychological factors, image, and physical have a significant differences to agree or disagree from smokers consumers and non smokers consumers if food court provide the smoking area facilitie

Modifikasi Teknik Discrete Shear Gap Pada Elemen Balok Timoshenko Berbasis Kriging

Metode elemen hingga berbasis Kriging (MEH-K) yang dikembangkan oleh Plengkhom & Kanok-Nukulchai adalah salah satu pengembangan dari metode elemen hingga (MEH). Seperti yang diperkirakan tenyata dalam analisis MEH-K untuk balok dan pelat lentur, fenomena shear locking masih terjadi. Adapun kesimpulan dari pengujian elemen balok Timoshenko yang menggunakan MEH-K dengan teknik discrete shear gap (DSG) berhasil mengeliminasi fenomena shear locking, tetapi hanya berlaku untuk shape function cubic. Adanya penelitian ini adalah untuk memodifikasi teknik DSG pada elemen balok Timoshenko berbasis Kriging agar bebas dari fenomena shear locking. Dari penelitian ini, didapatkan bahwa dengan memodifikasi teknik DSG, elemen balok Timoshenko berbasis Kriging dengan orde berapapun bebas dari fenomena shear locking yaitu menghasilkan nilai deformasi yang akurat dan nilai gaya geser yang berbentuk piecewise constant

Pengujian Elemen Cangkang Yang Terdapat Dalam Program Komersial Dengan Analisis Linier Dan Nonlinier Geometri

Penelitian ini bertujuan menguji keakuratan dan konvergensi elemen shell dalam analisa linier dan nonlinier geometri dalam program komersial dengan berbagai benchmark problem linier dan nonlinier geometri yang biasa di pakai oleh para pengembang elemen shell. Benchmark problem tersebut dimodelkan dengan menggunakan elemen shell S4, S4R, S4R5, S8R dan S8R5yang berdasarkan teori cangkang tipis (thin shell theory) dan teori cangkang tebal (thick shell theory).Output yang diukur dalam pengujian ini adalah displacement, tegangan permukaan dan gaya dalam yang terjadi. Hasil penelitian dengan analisa linier secara umum menunjukkan bahwa elemen cangkang S4 dan S8R5 menghasilkan nilai yang mendekati solusi referensi dibandingkan elemen cangkang yang lain. Sedangkan hasil penelitian dengan analisa nonlinier secara umum menunjukkan bahwa semua elemen cangkang menghasilkan nilai yang mendekati solusi referensi, tetapi elemen cangkang S4 dan S4R yang paling mudah mencapai konvergensi. Hal ini merupakan suatu usulan untuk melakukan pengetesan menggunakan program lain dalam penelitian ini, untuk mendapatkan hasil yang lebih akurat mengenai kinerja elemen

APLIKASI PEMESANAN RUANGAN DI PRESIDENT UNIVERSITY

President University merupakan salah satu instansi pendidikan yang sedang mengalami perkembangan yang pesat, perkembangan yang terjadi berdampak pada semakin banyaknya aktifitas yang terjadi di President University dan naiknya tingkat penggunaan ruangan yang ada di President University, baik untuk aktifitas belajar mengajar maupun aktifitas pendukungnya. Prosedur peminjaman ruangan yang masih manual menyebabkan beberapa permasalahan diantarnya kesulitan yang dialami oleh peminjam ruangan pada saat akan melakukan peminjaman ruangan dan kesulitan yang dihadapi oleh petugas ruangan didalam mengelola dan memantau penggunaan ruangan. Penelitian ini akan menjelaskan bagaimana merancang sebuah aplikasi yang digunakan untuk dapat membantu proses pemesanan ruangan, mengelola dan memantau penggunaan ruangan. Hasil yang diharapkan dari aplikasi pemesanan ruangan berbasis web ini dibuat untuk memudahkan peminjam ruangan, dan memudahkan petugas ruangan didalam memonitor pekerjaannya dengan menyimpan dan menampilkan data pemesanan ruangan secara praktis dan sistematis

Navigating Stories in Times of Transition

Introduction: In this paper, we present the project Navigating Stories in Times of Transition, a collaboration between the University of Twente and the Netherlands eScience Center. The project aims to make state-of-the-art tools for natural language processing available to researchers in the social sciences and humanities (SSH). The tools we develop advance multidisciplinary approaches to analyzing stories across different media and time. We are particularly interested in further developing digital story grammar, a computational method for narrative analysis (Andrade & Andersen, 2020). We want to show how an analysis of personal narratives collected in the times of COVID-19 pandemic with our computerized narrative tools will help researchers to chart how people make sense of the pandemic and respond to its socio-political framings in uncertain times (Murray & Sools, 2014). We will embed our tools in relevant infrastructures to make them sustainable for future use (such as CLARIAH or the SSH Open Marketplace). As a platform for integrating the tools, we use Orange, a modular data mining toolkit (Demšar et al., 2013).Current practices: Narrative researchers already use several software programs, such as Atlas.ti and NVivo for qualitative data analysis, LIWC for automatic text analysis, and Excel, R, SPSS, and Stata for statistical analysis. In the past decade, automated natural language analysis tools have become available that could be useful for narrative analysis. Whereas several methods for natural language analysis (e.g., named entity recognition and sentiment analysis) have already been integrated into various tools used for narrative research studying textual data in English, the situation is direr for other languages. In addition, the application of more advanced approaches such as semantic role labelling and digital story grammar requires programming ability, which prevents broad application.Goals: We aim at making digital story grammar available for other languages than English. In our initial work, we have developed crude versions of digital story grammar based on semantic role labelling for Dutch, Danish and German. Our next work has two objectives. First, inspired by narrative methodology, we want to extend our tools to advance the analysis from the level of sentences to the story level. Second, to register changes in narratives in response to societal events, we intend to enable comparative analyses across time and space with computational methods. Initially, we will focus on analyzing the dynamic relationship between narratives and societal conditions during the COVID-19 pandemic.Concluding remarks: Our project aims at making state-of-the-art tools for natural language processing and data visualization available to SSH researchers. In our initial work, we have developed a new version of digital story grammar for the languages of Dutch, Danish and German. Our project will extend the digital toolbox for narrative analysis and thus support researchers in studying larger volumes of digital texts. All software produced by the project will be open source and we strive to balance usability and complexity when developing our tools for narrative research

Preparation and characterization of in situ polymerized cyclic butylene terephthalate/graphene nanocomposites

Graphene reinforced cyclic butylene terephthalate (CBT) matrix nanocomposites were prepared and characterized by mechanical and thermal methods. These nanocomposites containing different amounts of graphene (up to 5 wt%) were prepared by melt mixing with CBT that was polymerized in situ during a subsequent hot pressing. The nanocomposites and the neat polymerized CBT (pCBT) as reference material were subjected to differential scanning calorimetry (DSC), dynamical mechanical analysis (DMA), thermogravimetrical analysis (TGA) and heat conductivity measurements. The dispersion of the grapheme nanoplatelets was characterized by transmission electron microscopy (TEM). It was established that the partly exfoliated graphene worked as nucleating agent for crystallization, acted as very efficient reinforcing agent (the storage modulus at room temperature was increased by 39 and 89% by incorporating 1 and 5 wt.% graphene, respectively). Graphene incorporation markedly enhanced the heat conductivity but did not influence the TGA behaviour due to the not proper exfoliation except the ash content

A meta-analysis of state-of-the-art electoral prediction from Twitter data

Electoral prediction from Twitter data is an appealing research topic. It seems relatively straightforward and the prevailing view is overly optimistic. This is problematic because while simple approaches are assumed to be good enough, core problems are not addressed. Thus, this paper aims to (1) provide a balanced and critical review of the state of the art; (2) cast light on the presume predictive power of Twitter data; and (3) depict a roadmap to push forward the field. Hence, a scheme to characterize Twitter prediction methods is proposed. It covers every aspect from data collection to performance evaluation, through data processing and vote inference. Using that scheme, prior research is analyzed and organized to explain the main approaches taken up to date but also their weaknesses. This is the first meta-analysis of the whole body of research regarding electoral prediction from Twitter data. It reveals that its presumed predictive power regarding electoral prediction has been rather exaggerated: although social media may provide a glimpse on electoral outcomes current research does not provide strong evidence to support it can replace traditional polls. Finally, future lines of research along with a set of requirements they must fulfill are provided.Comment: 19 pages, 3 table

Analysis of the Emails From the Dutch Web-Based Intervention “Alcohol de Baas”:Assessment of Early Indications of Drop-Out in an Online Alcohol Abuse Intervention

Nowadays, traditional forms of psychotherapy are increasingly complemented by online interactions between client and counselor. In (some) web-based psychotherapeutic interventions, meetings are exclusively online through asynchronous messages. As the active ingredients of therapy are included in the exchange of several emails, this verbal exchange contains a wealth of information about the psychotherapeutic change process. Unfortunately, drop-out-related issues are exacerbated online. We employed several machine learning models to find (early) signs of drop-out in the email data from the “Alcohol de Baas” intervention by Tactus. Our analyses indicate that the email texts contain information about drop-out, but as drop-out is a multidimensional construct, it remains a complex task to accurately predict who will drop out. Nevertheless, by taking this approach, we present insight into the possibilities of working with email data and present some preliminary findings (which stress the importance of a good working alliance between client and counselor, distinguish between formal and informal language, and highlight the importance of Tactus' internet forum)