Article Per Year (5 Year)
p-Index From 2021 - 2026
3.37
P-Index
This Author published in this journals
All Journal Jurnal S2 Pendidikan Matematika JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA AKSIOMA: Jurnal Program Studi Pendidikan Matematika Delta-Pi : Jurnal Matematika dan Pendidikan Matematika Jurnal Terapan Abdimas JPPM (JURNAL PENELITIAN DAN PEMBELAJARAN MATEMATIKA) Jurnal Matematika Sains dan Teknologi MAJAMATH: Jurnal Matematika dan Pendidikan Matematika Arithmetic : Academic Journal of Math Community Development Journal: Jurnal Pengabdian Masyarakat EPSILON Jurnal Pendidikan Matematika Pedagogy : Jurnal Pendidikan Matematika Teknologika Journal of Fundamental Mathematics and Applications (JFMA) Edumatica: Jurnal Pendidikan Matematika PROCEEDING AL GHAZALI International Conference International Journal of Research in Mathematics Education Jurnal Pendidikan MIPA
Riski Aspriyani
Universitas Nahdlatul Ulama Al Ghazali Cilacap
Religion Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Other

Published : 24 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 24 Documents
Search

 1   2   3 
Teachers’ Experiences with Students’ Learning Obstacles in Geometric Thinking: Insights from the van Hiele Framework Muhassanah, Nur'aini; Muhammad 'Azmi Nuha; Riski Aspriyani
International Journal of Research in Mathematics Education Vol. 3 No. 2 (2025)
Publisher : Faculty of Tarbiya and Teacher Trainning, Universitas Islam Negeri Prof. K.H. Saifuddin Zuhri Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24090/ijrme.v3i2.15429

Abstract

Understanding geometric concepts is often a challenge for students because it requires spatial thinking and deductive reasoning skills that develop gradually. This study aims to describe the barriers to student learning in geometric thinking based on teacher perceptions using van Hiele's theoretical framework. The research approach used was qualitative with a phenomenological design, involving 49 junior high school mathematics teachers from 35 schools across seven districts. Data were collected through questionnaires and in-depth interviews, then analyzed thematically. Interview data was collected from only six teachers selected through purposive sampling. The results of the study showed that students' learning barriers increased as their geometric thinking level increased. At level 0 (Visualization), the barriers were low (58.63%) because students were still able to recognize shapes visually. At level 1 (Analysis), the barriers increased to 64.61% (high category) because students had difficulty finding relationships between the properties of shapes. At level 2 (Informal Deduction), the barriers reached 72.48% (high category), especially in the use of formal mathematical language and the preparation of logical arguments. In addition, the results showed that epistemological barriers were related to weak mastery of basic concepts, ontological barriers were related to misclassification of geometric objects, and didactic barriers stemmed from external factors such as learning strategies and learning motivation. Overall, these results emphasize the need for contextual, tiered, and exploratory geometry learning designs to reduce learning barriers at every level of student thinking.
Prediksi Jumlah Siswa Baru Menggunakan Least Square Method Aspriyani, Riski; Ahmad, Mizan
MAJAMATH: Jurnal Matematika dan Pendidikan Matematika Vol. 6 No. 1 (2023): Vol 6 No 1 Maret 2023
Publisher : Prodi Pendidikan matematika Universitas Islam Majapahit (UNIM), Mojokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36815/majamath.v6i1.2517

Abstract

In the process of admitting new students, each school has a different strategy to increase the number of applicants and the number of students accepted. The publication strategy is structured to achieve the expected goals or to get the number of students according to the quota. The publication strategy will work well if the school has predictive data on the number of students that will come. Therefore, researchers do research with the purpose to predict the number of new students at SMA Ya Bakii 1 Kesugihan using the Trend Linear model with the Least Square to the number of new students from 2002/2003 to 2022/2023. The results of the analysis show that the Least Square Method prediction model in the form of y =49.424+4.463x gives accurate or good results with a MAPE value of 11.996%. While the prediction results for the next five years, namely 2023/2024, 2024/2025, 2025/2026, 2027/2028, and 2029/2030 are 148 students, 152 students, 157 students, 161 students, and 165 students.
Prediksi Banyaknya Gangguan Keamanan Ketertiban Masyarakat Menggunakan Model ARIMA Aspriyani, Riski; Fadhilla, Widya Rizky
MAJAMATH: Jurnal Matematika dan Pendidikan Matematika Vol. 8 No. 1 (2025): Vol. 8 No. 1 Maret 2025
Publisher : Prodi Pendidikan matematika Universitas Islam Majapahit (UNIM), Mojokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36815/majamath.v8i1.3822

Abstract

Abstrak Prediksi data sangat penting dalam mengantisipasi terjadinya gangguan keamanan dan ketertiban masyarakat. Dengan adanya prediksi data yang dilakukan dapat mendeteksi gangguan yang akan muncul dan data prediksi yang diperolah dapat dijadikan bahan pertimbangan pemerintah dalam pengambilan keputusan kebijakan serta penetapan strategi pencegahan. Untuk itu, urgensi penelitian ini menjadi penting dalam upaya mendapatkan data prediksi gangguan keamanan dan ketertiban masyarakat sehingga pemerintah dapat bertindak lebih proaktif dalam pencegahannya. Model yang digunakan dalam prediksi banyakanya gangguan keamanan dan ketertiban masyarakat adalah model ARIMA yang berbentuk ARIMA (p,d,q) dengan p menyatakan ordo dari unsur Autoregressive (AR), d ialah ordo dari unsur Integrated (I), dan q dari ordo Moving Average (MA). Model terbaik dipilih jika memenuhi uji signifikansi parameter, uji white noise, uji normalitas dan melihat nilai error RMSE, MAPE. Pengujian dilakukan dengan bantuan SPSS, diperoleh bahwa model ARIMA terbaik adalah Model ARIMA (0,1,1) dengan nilai RMSE 4.938 dan MAPE sebesar 37.141. ARIMA (0,1,1) merupakan model yang mampu meramalkan dengan baik untuk dapat digunakan selanjutnya pada prediksi atau peramalan beberapa periode ke depan. Dihasilkan bahwa, banyaknya gangguan keamanan dan ketertiban masyarakat di wilayah Batang dari bulan April 2025 sampai dengan Desember 2025 yaitu sebanyak 17.89 , 17.92, 17.96, 17.99, 18.02, 18.05, 18.09, 18.12, 18.15. Kata Kunci: Peramalan, ARIMA (p,d,q), Gangguan Keamanan Abstract Data prediction is very important in anticipating the occurrence of disturbances in public order and security. With the data prediction that is carried out, disturbances that will arise can be detected and the prediction data obtained can be used as a consideration by the government in making policy decisions and determining prevention strategies. For this reason, the urgency of this research is essential to obtain data on predictions of disturbances in public order and security so that the government can act more proactively in preventing them. The model used in predicting the number of disturbances in public order and security is the ARIMA model in the form of ARIMA (p,d,q) with p stating the order of the Autoregressive (AR) element, d being the order of the Integrated (I) element, and q from the Moving Average (MA) order. The best model is chosen if it meets the parameter significance test, white noise test, and normality test and sees the error values ??RMSE, and MAPE. Testing was carried out with the help of SPSS, it was obtained that the best ARIMA model was the ARIMA Model (0,1,1) with an RMSE value of 4,938 and a MAPE of 37,141. ARIMA (0,1,1) is a model that can predict well and can be used further in predictions or forecasts for several periods ahead. It was found that the number of disturbances to public order and security in the Batang area from April 2025 to December 2025 was 17.89, 17.92, 17.96, 17.99, 18.02, 18.05, 18.09, 18.12, and 18.15. Keywords: Forecasting, ARIMA (p,d,q), Disturbance of Public
PENGARUH SELF EFFICACY TERHADAP PENALARAN STATISTIS MAHASISWA Riski Aspriyani; Muhassanah, Nur'aini
Pedagogy: Jurnal Pendidikan Matematika Vol. 11 No. 1 (2026): Pedagogy : Jurnal Pendidikan Matematika
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/tej2hc49

Abstract

Penelitian Ex Post Facto  ini bertujuan untuk mengetahui pengaruh self-efficacy terhadap penalaran statistis dan bagaimana hubungan antara kedua variabel tersebut. Populasi dalam penelitian ini adalah sebanyak 576 mahasiswa angkatan 2024/2025 diambil sampel menggunakan teknik purposive sampling sebanyak 40 mahasiswa. Data induk penelitian diambil menggunakan instrumen angket untuk self-efficacy dan instrumen tes untuk penalaran statistis yang sebelumnya telah dilakukan uji kelayakan instrumen validitas dan reliabilitas. Uji hipotesis menggunakan uji regresi linear sederhana dengan prasyarat uji normalitas dan uji linearitas terpenuhi. Hasil analisis regresi linear sederhana diperoleh baha nilai sig. 0.043<0.05 atau nilai Fh= 4.385 > 4.091 akibatnya H0 ditolak, sehingga diperoleh kesimpulan bahwa terdapat pengaruh signifikan antara self-efficacy terhadap penalaran statistis mahasiswa. Besaran self efficacy mempengaruhi penalarn statistis sebesar (R2) 10.3%. Persamaan regresi linear diketahui bahwa . Persamaan ini memiliki arti bahwa setiap penambahan satu self-efficacy akan bertambah sebanyak 0.285 penalaran statistis. Kekuatan hubungan (Rxy) sebesar 0.332 yang berarti semakin tinggi nilai self-efficacy akan semakin tinggi pula nilai penalaran statistis, begitu juga semakin rendah self-efficacy yang dimiliki akan semakin rendah penalaran statistisnya.
Co-Authors Ahmad, Mizan Andriani Suzana Andriani Suzana Bryan Pudji Hartono Dasaprawira, M Noviarsyah Dewi Retno Sari S Eka Susilowati Eka Susilowati Eka Susilowati, Eka Fadhilla, Widya Rizky Hana Yulia Anggraeni Hartono, Bryan Pudji Mardiyana Mardiyana Mizan Ahmad Muhammad 'Azmi Nuha Muhassanah, Nur'aini Mutia Mutia Nadzifah Najmah Istikaanah Nuraini Muhassanah Nurkholis Makhfudz Umi Ma’rifah