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Electronic Journal of Education, Social Economics and Technology
Published by SAINTIS Publishing
ISSN : -     EISSN : 27236250     DOI : https://doi.org/10.33122/ejeset
Core Subject : Religion, Economy, Humanities, Health, Science, Education, Art, Social, Engineering,
Religion Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Veterinary Other
Electronic Journal of Education, Social Economics and Technology (eJESET) with ISSN 2723-6250 (online) is a open-access, peer-reviewed multidisciplinary international journal. The journal aims to provide an international platform for researchers, professionals and scientists for solve of problems with multidisciplinary approaches on all topics related to educational, social science, economics and technology to exchange, sharing and disseminate theoretical of current research results as widely as possible. Electronic Journal of Education, Social Economics and Technology (eJESET) publishes the latest research results in multidisciplinary approaches on all topics related to educational, social science, economics and technology. First published in 2020. The Journal is published biannually and is available in open access electronic version.
Arjuna Subject : Ilmu Sosial - Ilmu Sosial (Lain-Lain)
Articles 652 Documents
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Implementation of the Nearest Neighbour Method for Determining Distribution Routes to Enhance Distribution Efficiency Sohriana Pasaribu; M. Sayuti; Defi Irwansyah
Electronic Journal of Education, Social Economics and Technology Vol 7, No 1 (2026)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v7i1.1347

Abstract

Non-optimal determination of distribution routes can lead to excessive travel distances, delivery delays, and increased operational costs. This problem commonly occurs when route planning is conducted manually and without the support of optimization methods. This study was conducted at CV. XYZ, a beverage distribution company located in Batuphat Timur, Muara Satu District, Lhokseumawe City. The company distributes beverage products such as Teh Botol Sosro and Sosro Fruitea to 57 customer outlets across the Lhokseumawe area. Currently, distribution routes are determined based on drivers’ experience, which may result in inefficiencies in travel distance, distribution time, and operational costs. This study aims to determine optimal distribution routes using the Nearest Neighbour method and to analyze its impact on distribution cost efficiency. The research methods include field observation, interviews, and distance measurement using Google Maps, which were subsequently analyzed using the Nearest Neighbour algorithm with the assistance of MATLAB software. The results indicate that the total distribution distance was reduced from 936.25 km to 708.01 km, resulting in a distance saving of 228.24 km (24.38%). Distribution time decreased from 81.65 hours to 77.84 hours, achieving an efficiency improvement of 4.66%. In addition, distribution costs were reduced from IDR 3,161,952 to IDR 2,902,950, yielding a cost saving of IDR 258,131 (8.17%). Based on these findings, it can be concluded that the Nearest Neighbour method is effective in optimizing distribution routes and improving efficiency in terms of distance, time, and operational costs.
The Effect of Zep Quiz-Assisted Physics Learning on Students’ Learning Motivation and Learning Outcomes in the Topic of Energy Sources in Grade X of Madrasah Aliyah Dila Trianasari; Syafrizal Idris; Nurul Fadieny; Syarifah Rita Zahara; Riza Andriani
Electronic Journal of Education, Social Economics and Technology Vol 7, No 1 (2026)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v7i1.1475

Abstract

Students' learning motivation and cognitive learning outcomes in physics, particularly on the topic of energy sources, remain suboptimal. One contributing factor is the tendency for assessment activities to be monotonous and to provide no immediate feedback to students. This study aimed to determine the effect of Zep Quiz-assisted physics instruction on the learning motivation and cognitive learning outcomes of Grade X students studying energy sources. A quasi-experimental method with a nonequivalent pretest-posttest control group design was employed. The sample comprised one experimental class receiving Zep Quiz-assisted instruction and one control class receiving conventional instruction. Data were collected using a cognitive learning-outcomes test and a learning-motivation questionnaire and were analyzed through Multivariate Analysis of Covariance (MANCOVA), with pretest scores as covariates, after all analytical assumptions had been satisfied. The results showed that Zep Quiz-assisted instruction had a significant simultaneous effect on students' learning motivation and learning outcomes, with Wilks' Lambda = 0.157 and p 0.001. The experimental group achieved a mean learning-outcomes posttest score of 86.88, exceeding the control group's score of 66.25. The experimental group also recorded a higher mean learning-motivation score (29.16) than the control group (22.54). Optimizing the gamification features in Zep Quiz stimulated students' emotional engagement, creating a dynamic and enjoyable classroom atmosphere and encouraging active participation throughout instruction. Therefore, Zep Quiz can serve as a gamified digital assessment tool to support improvements in motivation and physics learning outcomes on the topic of energy sources.

Page 66 of 66 | Total Record : 652

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