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All Journal Zeta - Math Journal Journal Focus Action of Research Mathematic (Factor M) JEAS Proceeding International Conference on Education
Dewi, Ardiana Fatma
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Application of binary logistic regression analysis to factors that influence participation in the 2024 presidential election Ahadiyah, Kurnia; Dewi, Ardiana Fatma; Romadewanti, Shinta Hircatanu
Journal Focus Action of Research Mathematic (Factor M) Vol. 7 No. 2 (2024): Vol. 7 No. 2 (2024)
Publisher : Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/f_m.v7i2.3703

Abstract

Social media plays a very influential role, especially in the world of politics and elections. The 2024 elections in Indonesia show how social media can influence political dynamics. This research aims to analyze the influence of social media on the political participation of IAIN Kediri students in the 2024 Presidential Election, as well as understand how social media shapes public opinion and polarizes political views, with a focus on its impact on political participation among students. Data from the Indonesian Internet Service Providers Association (APJII) shows that the majority of the Indonesian population actively uses social media, so political candidates use platforms such as YouTube, Facebook, Instagram, and TikTok to attract support. Social media accelerates the delivery of political messages and has the potential to strengthen polarization and spread misleading information. In this research, a binary logistic regression model is used to analyze the factors that influence student participation in the 2024 presidential election. The findings show that students who actively follow news in mass media have a 7,157 times greater chance of participating in the 2024 presidential election compared to those who do not follow the news. These results emphasize the importance of social media in motivating political participation among students and provide insight into how social media can be utilized to improve the integrity and quality of democracy.
Development of Ethnoscience Based Science Learning Module and Science Literacy for Junior High School Students Anggraini, Atika; Prassastie, Fadilla Eka; Salani, Hana Talia Novia; Fahma, Farisa Aina; Rahman, Àdnan; Dewi, Ardiana Fatma
Proceeding International Conference on Education Volume 03, Agustus Tahun 2025: International Conference on Education
Publisher : Faculty of Tarbiyah, Institut Agama Islam Negeri (IAIN) Kediri, Indonesia

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Abstract

This research aims to develop ethnoscience-based science learning module and science literacy for grade VIII students. This module development uses the Research and Development (R&D) model by adapting the steps of the 4D model, which includes (Define, Design, Develop, Dessimination). In this study, data were collected through observation, interviews, questionnaires, and documentation. The developed module was validated by material experts, media experts, LKPD experts, and readability experts who each provided an assessment of the relevant aspects. The results of validation by material experts, media experts, LKPD experts and readability experts showed 100% feasibility. The results of student responses showed very good results of 88.10%. Students who use this module are better able to connect scientific knowledge with the context of science which is an important indicator in the ability to think critically, analytically, and creatively. The results of this study indicate that ethnoscience and science literacy-based modules are not only effective in improving understanding of material concepts, but also strengthening higher-order thinking skills that are needed in facing the challenges of today. 
Agglomerative Hierarchy Clustering Pada Penentuan Kelompok Kabupaten/Kota di Jawa Timur Berdasarkan Indikator Pendidikan Dewi, Ardiana Fatma; Ahadiyah, Kurnia
Zeta - Math Journal Vol 7 No 2 (2022): November
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/zeta.2022.7.2.57-63

Abstract

Salah satu cara agar dapat meningkatkan kondisi pendidikan di setiap kabupaten/kota di Jawa Timur adalah dengan menggunakan analisis pengelompokan sesuai dengan karakteristik pendidikannya. Analisis Klaster merupakan analisis yang termasuk ke dalam golongan analisis multivariat yang bertujuan untuk mengelompokkan objek berdasarkan karakteristik yang dimilikinya. Penelitian ini menggunakan analisis klaster tipe agglomerative dengan lima metode. Analisis klaster ini disebut dengan “agglomerative hierarchy clustering”. Tujuan penelitian ini adalah membandingkan metode analisis klaster herarki tersebut dengan mencari model terbaik melalui pencarian nilai koefisien korelasi cophenetic terbesar. Data yang digunakan pada penelitian ini merupakan data sekunder yang diperoleh dari Badan Pusat Statistik (BPS) Jawa Timur dan Kementerian Pendidikan Republik Indonesia. Pada pengelompokan Kabupaten/Kota di Provinsi Jawa Timur berdasarkan indikator pendidikan dengan menggunakan metode Agglomerative Hierarchical Clustering dihasilkan bahwa algoritma optimal yang digunakan yaitu pada algoritma average linkage dengan nilai korelasi cophenetic yang diperoleh sebesar 0,807. Berdasarkan indikator pendidikan dari 38 Kabupaten/Kota di Provinsi Jawa Timur terbagi menjadi dua cluster dimana pada cluster pertama beranggotakan 3 Kabupaten/Kota dan cluster kedua 35 Kabupaten Kota. Keywords: Agglomerative, Clustering, Hierarchical, cophenetic
TRANSFORMASI PEMBELAJARAN SAINS MELALUI GAME EDUKATIF “MAGNETIC CHALLENGE” DENGAN CONSTRUCT 2 Putri, Nabila Amelia Kurnia; Nuriyah, Zidah Chotamy; Moryati, Yulisna; Nadzifah Salsabila; Aura Maharani Cahya Krisanti; Laili, Ummiy Fauziyah; Dewi, Ardiana Fatma
JEAS (Journal of Educational and Applied Science) Vol. 3 No. 1 (2025): September 2025
Publisher : Tadris IPA Universitas KH. Mukhtar Syafaat Blokagung Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30739/jeas.v3i1.4205

Abstract

This research develops the educational game Magnetic Challenge based on Construct 2 as a medium for learning magnetism. Using a qualitative descriptive method, the research focuses on needs analysis, media usage, and user feedback. The results show that this game is effective in helping visualize abstract concepts, increasing learning motivation, and deepening student understanding, although there are constraints regarding accessibility, audio, and flexibility of learning styles. Overall, this media is worth using as an innovative and enjoyable alternative for science learning for junior high school students.
Using Photomath Applications on Student Learning Outcomes in Advanced Calculus Courses Dewi, Ardiana Fatma; Ahadiyah, Kurnia
Proceeding International Conference on Education Volume 01, Agustus Tahun 2023: International Conference on Education
Publisher : Faculty of Tarbiyah, Institut Agama Islam Negeri (IAIN) Kediri, Indonesia

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Abstract

Along with the development of the times, the world of education is much influenced by advances, especially in the field of information and communication technology. Many educators use technology as a learning medium to help students learn and solve problems, especially math problems. There are several applications that students use to help them complete lecturer assignments. Photomath is one of the applications used by students in mathematics lessons. This application can be accessed via a smartphone and has features that help students solve math problems. This study aims to determine the effect of using the Photomath application on the learning outcomes of Tadris Mathematics students in semester 4 of the State Islamic Institute (IAIN) Kediri. The number of samples used in this study were 45 students, which were divided into two groups. The experimental group consisted of 24 students and the control group consisted of 21 students. The analysis used in this study is a t-test to compare whether there are differences in student learning outcomes in advanced calculus courses when solving problems using the Photomath application and not using these tools. The results obtained show that there are significant differences between students who use the help of the Photomath application and those who do not. So it can be concluded that the use of the Photomath application has an effect on student learning outcomes at IAIN Kediri's mathematics tadris in advanced calculus courses.
Implementation of STEM (Science Technology Engineering and Mathematics) Learning Model Based on Local Wisdom on Student Learning Outcomes Dewi, Ardiana Fatma; Wakhidah, Fina Alya Nur; Sari, Dwi Ratna; Arifinta, Hasna Nisa; Ni’amahah, Naila Lutfiatun; Ilmia, Siti Mazro’atul; Sholihah, Tri Eva
Proceeding International Conference on Education Volume 02, Agustus Tahun 2024: International Conference on Education
Publisher : Faculty of Tarbiyah, Institut Agama Islam Negeri (IAIN) Kediri, Indonesia

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Abstract

The rapid development of science and technology has given rise to various innovations in the field of technology that are created to facilitate activities, especially in the field of education. Creative thinking and critical thinking skills are very much needed following the demands of 21st-century skills, namely so that students have various abilities, including critical thinking, creative thinking, communication and collaboration. STEM is an integrative learning approach that combines Knowledge (Science), Technology (Technology), Engineering (Engineering), and Mathematics (Mathematics). Several studies have shown that the STEM approach positively affects student learning, so this study tries to implement STEM based on local wisdom on learning outcomes. This study aims to determine how student learning outcomes are before and after providing a STEM learning model based on local wisdom. The type of research used is quantitative with an experimental method. Sample selection uses a simple random sampling technique, with research subjects being grade IX students of SMP Muhammadiyah Kediri. The results of the study showed that the average student learning outcomes before the action were relatively low; after being given treatment, the average student learning outcomes increased. The results obtained using the paired t-test were that the significance value of learning outcomes was 0.000 <0.05, meaning that there was a difference in the average learning outcomes of students before and after the local wisdom-based STEM learning model provision.
Perbandingan Model Generalized Ammi (Gammi) dengan Row Column Interaction Model pada Interaksi Genotipe dan Lingkungan Ahadiyah, Kurnia; Dewi, Ardiana Fatma
Journal Focus Action of Research Mathematic (Factor M) Vol. 4 No. 2 (2022)
Publisher : Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/factor_m.v4i2.4189

Abstract

Model Generalized AMMI (GAMMI) merupakan perluasan dari model AMMI (Additive Main Effect and Multiplicative Interaction). Model GAMMI melibatkan konsep Generalized Linear Model (GLM) pada variabel responnya. Pada penelitian ini, model GAMMI digunakan untuk data interaksi antara genotipe dan lingkungan yang mempunyai distribusi poisson. Sama halnya dengan model AMMI, model GAMMI juga digunakan untuk menganalisis kestabilan genotipe pada lingkungan yang beragam dengan pengaruh utama perlakuan dimodelkan dengan model aditif sedangkan pengaruh interaksi dimodelkan dengan model multiplikatif (bilinier). Metode lain yang memiliki kemiripan dengan model GAMMI adalah Row Column Interaction Model (RCIM). Model ini juga dapat digunakan untuk data yang berdistribusi poisson. Kedua model ini akan dibandingkan nilai analisis devian dan biplotnya. Interpretasi kedua model ditunjukkan melalui biplot dengan penguraian Singular Value Decompotition (SVD) pada matriks interaksi. Data yang digunakan untuk membandingkan kedua metode tersebut adalah data hama kedelai yang berisi empat genotipe dan lima jenis hama kedelai. Penelitian ini lebih ditekankan pada perbandingan hasil pemodelan dengan cara yang berbeda. Kedua metode menunjukan nilai peluang yang hampir sama yaitu untuk model GAMMI dengan regresi bolak-balik sebesar 0,0541, sedangkan model RCIM sebesar 0,0548. Keduanya sama-sama signifikan pada model GAMMI2 karena nilai peluang <0,06.   Generalized AMMI (GAMMI) model is a development of the AMMI (Additive Main Effect and Multiplicative Interaction) model. Model GAMMI involves the concept of Generalized Linear Model (GLM) on the response variable. In this research, GAMMI model used for interaction of genotype and environment data that have poisson distribution. Similar to the AMMI model, GAMMI model also used to analyze the stability of the genotype in any different environment with the main effect of treatment is modeled by additive model, while the effect of the interaction is modeled by multiplicative model (bilinear). Another method which is similar to GAMMI model is Row Column Interaction Model (RCIM). This model also can used for the data that have poisson distribution. These two models will be compared with the analysis value of the deviance and biplot. Interpretation of the model is shown through the biplot with Singular Value Decompotition (SVD) toward interaction matrix. The data used to compare the two methods is soybean pest data which contains four genotypes and five of soybean pests. This research emphasizes on comparing the results of modeling in different ways. The results of the analysis of the two methods show that the probability value is almost the same, for the GAMMI model with alternating regression is 0.0541, while the RCIM model is 0.0548. Both are equally significant in the GAMMI2 model because the probability value is <0.06.
Co-Authors Ahadiyah, Kurnia Anggraini, Atika Arifinta, Hasna Nisa Aura Maharani Cahya Krisanti Dwi Ratna Sari, Dwi Ratna Fahma, Farisa Aina Ilmia, Siti Mazro’atul Laili, Ummiy Fauziyah Moryati, Yulisna Nadzifah Salsabila Ni’amahah, Naila Lutfiatun Nuriyah, Zidah Chotamy Prassastie, Fadilla Eka Putri, Nabila Amelia Kurnia Rahman, Àdnan Romadewanti, Shinta Hircatanu Salani, Hana Talia Novia Sholihah, Tri Eva Wakhidah, Fina Alya Nur