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Sirait, Anisa
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences

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Hubungan antara Dukungan Sosial dengan Student Engagement pada Mahasiswa yang Sedang Menyusun Skripsi Sary, Nurvica; Elvinawaty, Rianda; Lim, Cynthia; Sihombing, Erna Frasiska; Stephany, Wen Wen Winda; Sirait, Anisa; Zendrato, Joseph Brillian F.
JURNAL SOCIAL LIBRARY Vol 4, No 3 (2024): JURNAL SOCIAL LIBRARY NOVEMBER
Publisher : Granada El-Fath

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51849/sl.v4i3.301

Abstract

Penelitian berikut dimaksudkan guna memverifikasi dan mengevaluasi hubungan antara Dukungan Sosial terhadap Student Engagement. Ditentukan bahwa sampel penelitiannya yakni 177 mahasiswa Universitas Prima Indonesia melalui teknik purposive sampling. Perolehan data penelitiannya berasal dari skala Dukungan Sosial yang mencakup 33 aitem serta skala Student Engagement mencakup 33 aitem. Metodelogi korelasi Person Product Moment dipergunakan dalam menganalisi datanya. Penelitian menunjukkan bahwa dukungan sosial mempunyai dampak yang positif serta adanya hubungan signifkan antara Student Engagement yakni korelasi koefisien sejumlah 0.212 yang nilai signifikansinya sejumlah 0.003 (p 0.005) dengan berarti semakin tingginya Dukungan Sosial yang diterima baik dari orangtua, dosen maupun teman-teman maka makin tinggi juga Student Engagement mahasiswa serta berlaku sebaliknya.
IMPLEMENTASI METODE SAW UNTUK REKOMENDASI MENU TERLARIS DI COFFEE SHOP Sirait, Anisa; Sulistyohati, Aprilia; Susanto, Arif
Jurnal Tera Vol 4 No 2 (2024): Jurnal Tera (September 2024)
Publisher : Fakultas Teknik dan Informatika, Universitas Dian Nusantara

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Abstract

In the era of rapid globalization, technological developments and changes in people's lifestyles affect various aspects of life, including the coffee shop business which is experiencing significant growth. Lanaka coffee shop, which focuses on coffee drinks and snacks, faces challenges in recommending best-selling menus due to rapidly changing customer tastes and market trends. To overcome this problem, this research proposes the use of the Simple Additive Weighting (SAW) method as a solution to recommend the best-selling menu at Coffee Shop Lanaka. The SAW method was chosen due to its ability to accurately assess menu criteria by considering predetermined weights. The process involves setting criteria that include taste, price, portion, and number purchased, and assigning fuzzy weights to each criterion. The weighting system is performed dynamically based on sales data and customer feedback, with two types of criteria: benefit and cost. The calculation results from the SAW method are used to rank the menu alternatives and provide the most suitable recommendation. With this approach, it is expected to increase customer satisfaction and profitability of Coffee Shop Lanaka through more efficient and up-to-date data-driven menu management
Co-Authors Arif Susanto Lim, Cynthia Rianda Elvinawaty Sary, Nurvica Sihombing, Erna Frasiska Stephany, Wen Wen Winda Sulistyohati, Aprilia Zendrato, Joseph Brillian F.