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Journal : Jurnal Transformatika

Pengembangan E-Modul Berbantuan Flipbook Berbasis Literasi Untuk Mata Kuliah Statistika Kusumaningrum, Yulinda; Utomo, Victor Gayuh; Ellyawati, Hetty Catur; Maulana, Charis
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.10233

Abstract

Statistics is the basis for studying other subjects in the Informatics Engineering Study Program. However, some lecturers have not used teaching materials such as interactive modules to help students learn statistics. For this reason, research is needed which aims to (1) develop literacy-based Flipbook-assisted interactive e-modules in statistics courses that are valid, (2) determine the practicality of literacy-based Flipbook-assisted interactive e-modules in statistics courses for students. This type of research is Research and Development (R&D). The research subjects were 30 Informatics Engineering students taking Statistics courses. The development steps in this research are using ADDIE, namely Analysis, Design, Development, Implementation, and Evaluation. The research results obtained: 1) the literacy-based flipbook-assisted e-module that was developed was declared valid/feasible with an average percentage of material experts of 80% and media experts of 85.41%, 2) the flipbook-assisted interactive e-module that was developed met the criteria practically with a percentage reaching 75%.
Implementasi Data Mining Untuk Estimasi Produktivitas Kacang Hijau Dengan Menggunakan Algoritma Regresi Linier Di Kabupaten Grobogan Kusumaningrum, Yulinda; Asmiatun, Siti; Putri, Astrid Novita
Jurnal Transformatika Vol. 19 No. 1 (2021): July 2021
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i1.9450

Abstract

The Grobogan Regency Agriculture Service is an agency that operates in the agricultural sector. One of the crop commodities in Grobogan Regency is green beans. Judging from the results obtained each year, green bean production in Grobogan Regency is inconsistent. The rise and fall of green bean productivity is influenced by several factors. Factors such as area, production, number of farmers and productivity can be estimated to determine the production of green beans in Grobogan Regency. Therefore, using the Multiple Linear Regression algorithm is expected to help to obtain results on how much green bean production is in Grogoban Regency as a reference for farmers to increase their green bean harvest each year. Based on the calculation results, it was found that the estimated productivity of green beans in Grobogan Regency reached 760.8297302 Tons/Ha, whereas previously the land was 865 Hectares (Ha) Keywords: data mining, linear regression, estimation, productivity, green beans
Analisis Pembelajaran Statistika Berbasis Literasi menggunakan E-Modul Berbantuan Flipbook Kusumaningrum, Yulinda; Maulana, Charis
Jurnal Transformatika Vol. 23 No. 1 (2025): July 2025
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v23i1.12537

Abstract

This research investigates the implementation of literacy-based learning in Statistics through the development of an e-module enhanced with Flipbook technology, aiming to foster student comprehension and active participation. The study employs a Research and Development (R&D) approach, utilizing the 4D model consisting of the phases: Define, Design, Develop, and Disseminate. The main output is a literacy-focused e-module presented in Flipbook format, specifically designed for students in the Informatics Engineering department. Validation from subject matter and media experts confirmed the module’s quality, rating it as “feasible” to “highly feasible.” Feedback from students reflected strong approval, with an overall response score averaging 83.75%, falling into the “very good” category. The use of the module significantly enhanced students’ grasp of statistical concepts, as evident from the improved scores in both pretest and posttest assessments. The recorded average gain score of 0.70, classified as “high,” demonstrates the e-module’s effectiveness in boosting learning outcomes. This integration of technology and literacy within the e-module makes it an appropriate and impactful learning tool to enrich the Statistics learning experience in a more engaging and contextually relevant manner.