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All Journal Pedagogi: Jurnal Ilmu Pendidikan Kontinu: Jurnal Penelitian Didaktik Matematika MUST: Journal of Mathematics Education, Science and Technology Jurnal Administrasi dan Manajemen Pendidikan Jurnal SOLMA BAREKENG: Jurnal Ilmu Matematika dan Terapan Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jurnal Saintika Unpam : Jurnal Sains dan Matematika Unpam Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat JAMP : Jurnal Administrasi dan Manajemen Pendidikan Jurnal Riset Pembelajaran Matematika Sekolah Jurnal Statistika dan Aplikasinya Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Griya Journal of Mathematics Education and Application International Journal of Progressive Mathematics Education MATHunesa: Jurnal Ilmiah Matematika International Journal of Applied Science and Sustainable Development (IJASSD) Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Pattimura International Journal of Mathematics (PIJMath) Parameter: Jurnal Matematika, Statistika dan Terapannya BAKTI : Jurnal Pengabdian Kepada Masyarakat E-Jurnal Matematika
Vera Maya Santi
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Agriculture, Biological Sciences & Forestry Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Profile Of Critical Thinking Errors Of Junior High School Students Based On Facione's Theory In Solving Problems On SLETV Material Janna Sri Bina Br Barus; Makmuri Makmuri; Vera Maya Santi
JURNAL PENDIDIKAN MATEMATIKA Vol. 10, No. 1: May 2026
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/kontinu.10.1.1-17

Abstract

This study aims to describe the profile of mathematical critical thinking errors among junior high school students, based on the components of Facione's Theory (Interpretation, Analysis, Evaluation, and Inference), in the context of solving Systems of Linear Equations in Two Variables (SLETV) problems. Specifically, this study cross-mapped Facione's cognitive failures with observed procedural errors, analysing them using the Newman Error Analysis framework (Reading, Understanding, Transformation, Process Skills, and Final Answer Writing). This study uses a qualitative method. This study found that students' critical thinking skills were generally low, with 42.05% in the low category. The highest cognitive failure point was located in the Analysis, Evaluation, and Inference domain. Triangulation analysis showed that weaknesses in Facione's Analysis Skills were the leading cause of the high frequency of Newman Transformation Errors, reflecting students' inability to model contextual problems as mathematical models. This study provides a more precise diagnostic basis for designing targeted learning interventions to optimise students' higher-order cognitive skills.Keywords: critical thinking; indicators Facione; procedural errors; SLETV.
Peran Academic Resilience dalam Memediasi Pengaruh Dukungan Guru dan Iklim Pembelajaran Terhadap Kepuasan Belajar Siswa SMA IT Al-Madinah Cibinong Vinsensius Crispinus Lemba; Khairunnisa Putri Alif; Vera Maya Santi
JAMP : Jurnal Administrasi dan Manajemen Pendidikan Vol 9, No 1 (2026): Volume 9 No 1 Maret 2026
Publisher : Universitas Negeri Malang

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Abstract

Abstract: This study aims to examine the effects of teacher support and classroom learning climate on students’ learning satisfaction, both directly and indirectly through academic resilience as a mediating variable, among students of SMAIT Al-Madinah Cibinong, Bogor Regency. The research employed a quantitative approach with an explanatory correlational design. A sample of 200 students was selected proportionally from the population. Data were collected using a closed-ended questionnaire with a four-point Likert scale and analyzed through validity and reliability tests, classical assumption tests, and path analysis. The findings indicate that teacher support and learning climate have positive and significant effects on academic resilience (β = 0.516; β = 0.566; p < 0.05), as well as direct and significant effects on learning satisfaction (β = 0.216; β = 0.206; p < 0.05). Academic resilience also demonstrates a strong positive effect on learning satisfaction (β = 0.604; p < 0.05). Furthermore, academic resilience is proven to mediate the effects of teacher support (0.312 > 0.216) and learning climate (0.342 > 0.206) on learning satisfaction. These findings suggest that learning satisfaction is not solely determined by the quality of the learning environment but also by students’ ability to respond adaptively to academic challenges. In this context, academic resilience functions as a key mechanism that bridges learning experiences and students’ evaluative judgments of those experiences. Practically, schools are encouraged to integrate instructional strategies that not only emphasize academic achievement but also strengthen students’ psychological capacities. Therefore, enhancing teacher support and fostering a conducive learning climate should be strategically directed toward developing academic resilience, so that students’ learning satisfaction can be sustained in a more stable, long-term, and meaningful manner. Keywords: Teacher Support; Learning Climate; Academic Resilience; Learning Satisfaction; Path Analysis Abstrak: Studi ini difokuskan untuk menganalisis pengaruh dukungan guru dan iklim pembelajaran terhadap kepuasan belajar siswa, baik secara langsung maupun tidak langsung melalui academic resilience sebagai variabel mediasi pada siswa SMAIT Al-Madinah Cibinong, Kabupaten Bogor. Penelitian menggunakan pendekatan kuantitatif dengan desain eksplanatori korelasional. Sampel berjumlah 200 siswa yang dipilih dari populasi secara proporsional. Data dikumpulkan melalui kuesioner tertutup dengan skala Likert empat tingkat, kemudian dianalisis menggunakan uji validitas, reliabilitas, uji asumsi klasik, serta analisis jalur (path analysis). Hasil penelitian memperlihatkan secara kuat bahwa dukungan guru dan iklim pembelajaran berpengaruh positif dan signifikan terhadap academic resilience (β = 0,516; β = 0,566; p < 0,05), serta berpengaruh langsung dan signifikan terhadap kepuasan belajar (β = 0,216; β = 0,206; p < 0,05). Academic resilience juga menunjukkan pengaruh yang kuat terhadap kepuasan belajar (β = 0,604; p < 0,05). Selain itu, academic resilience terbukti memediasi pengaruh dukungan guru (0,312 > 0,216) dan iklim pembelajaran (0,342 > 0,206) terhadap kepuasan belajar. Temuan ini mengindikasikan bahwa kepuasan belajar tidak hanya ditentukan oleh kualitas lingkungan belajar, tetapi juga oleh kemampuan siswa dalam merespons tekanan akademik secara adaptif. Dalam konteks ini, resiliensi akademik berperan sebagai mekanisme penting yang menjembatani pengalaman belajar dengan penilaian siswa terhadap proses tersebut. Implikasi praktisnya, sekolah perlu mengintegrasikan strategi pembelajaran yang tidak hanya berorientasi pada capaian akademik, tetapi juga pada penguatan aspek psikologis siswa. Oleh karena itu, penguatan dukungan guru dan penciptaan iklim pembelajaran yang kondusif perlu diarahkan secara strategis untuk mengembangkan academic resilience, sehingga kepuasan belajar siswa dapat terbentuk secara lebih stabil, berkelanjutan, dan berorientasi jangka panjang. Kata kunci: Dukungan Guru; Iklim Pembelajaran; Resiliensi Akademik; Kepuasan Belajar; Analisis Jalur
PELATIHAN PENGENALAN ALGORTIMA DAN PEMROGRAMAN VISUAL SISWA SMP DENGAN SCRATH Faroh Ladayya; Dian Handayani; Siti Rohmah Rohimah; Nilam Novita Sari; Vera Maya Santi; Erin Naudy Kemalasari; Zahra Ayu Rahmadani
Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025): PROSIDING SEMINAR NASIONAL PENGABDIAN KEPADA MASYARAKAT - SNPPM2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Negeri Jakarta

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Abstract

Abstrak Perkembangan teknologi di abad ke-21 menuntut generasi muda untuk memiliki keterampilan berpikir komputasional, pemecahan masalah, dan dasar pemrograman. Namun, di daerah pedesaan seperti Kabupaten Sukabumi, pemanfaatan teknologi dalam proses pembelajaran masih terbatas. Kegiatan pengabdian ini bertujuan untuk mengenalkan dasar-dasar algoritma dan pemrograman visual kepada siswa SMP Negeri 1 Kabupaten Sukabumi melalui media Scratch. Scratch adalah software pemrograman berbasis visual yang mudah digunakan bagi pemula, serta mampu menstimulasi kreativitas siswa dalam membuat animasi dan permainan sederhana. Kegiatan ini sejalan dengan Sustainable Development Goals (SDGs) pada poin Quality Education dengan membekali siswa keterampilan algoritma dan pemrograman dasar agar lebih siap menghadapi tantangan era digital. Metode pelaksanaan kegiatan meliputi penyampaian materi, serta praktik langsung menggunakan modul pembelajaran yang telah disusun. Hasil kegiatan menunjukkan bahwa siswa antusias mengikuti pelatihan dan mampu memahami konsep dasar algoritma melalui praktik pemrograman visual. Analisis kuesioner pendahuluan dan akhir menunjukkan adanya peningkatan motivasi, wawasan, serta keterampilan siswa dalam memahami algoritma dan pemrograman visual. Dengan demikian, pelatihan ini berkontribusi positif dalam memberikan bekal awal literasi digital dan pemrograman bagi siswa SMP, yang diharapkan dapat menjadi fondasi untuk pembelajaran teknologi lebih lanjut. Abstract The development of technology in the 21st century requires young generations to possess computational thinking, problem-solving skills, and basic programming literacy. However, in rural areas such as Sukabumi Regency, the integration of technology into the learning process remains limited. This community service activity aims to introduce the fundamentals of algorithms and visual programming to students at SMP Negeri 1 Sukabumi Regency, through the use of Scratch. Scratch is a visual-based programming software that is easy for beginners to use and encourages students’ creativity in creating simple animations and games. This activity aligns with the Sustainable Development Goals (SDGs), particularly Goal 4: Quality Education, by equipping students with basic algorithmic and programming skills to prepare them for the challenges of the digital era. The implementation method included material delivery, and hands-on practice using a specially designed learning module. The results showed that students were enthusiastic during the training and successfully understood basic algorithmic concepts through visual programming practice. Analysis of pre- and post-questionnaires indicated an increase in students’ motivation, knowledge, and skills in understanding algorithms and visual programming. Therefore, this training contributed positively by providing an initial foundation in digital literacy and programming for junior high school students, which is expected to serve as a stepping stone for more advanced technology learning in the future.
The Influence of Artificial Intelligence Usage of ChatGPT and Work Motivation on Teaching Readiness of Educators in Leuwiliang Bogor Sari Febrianti; Alifia Taufika Rahma; Dhioatmaja Megafajari; Vera Maya Santi
Pedagogi: Jurnal Ilmu Pendidikan Vol 26 No 1 (2026): Pedagogi: Jurnal Ilmu Pendidikan
Publisher : Fakultas Ilmu Pendidikan Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pedagogi.v26i1.2854

Abstract

The rapid integration of artificial intelligence, particularly ChatGPT, has reshaped instructional practices and teacher preparation, while raising questions about educators’ readiness to adapt effectively. This study examines the influence of ChatGPT usage and work motivation on the teaching readiness of educators in Madrasah Tsanawiyah in Leuwiliang, Bogor. Employing a quantitative approach, data were collected from 155 teachers using validated questionnaires and analyzed through multiple linear regression. The findings reveal that both ChatGPT usage and work motivation have positive and significant effects on teaching readiness, with work motivation emerging as the strongest predictor. Moreover, the simultaneous impact of both variables explains a substantial proportion of variance in teaching readiness, indicating a synergistic relationship between technological utilization and psychological factors. The study concludes that effective AI integration in education must be accompanied by strong work motivation to enhance teachers’ preparedness. Ultimately, this research invites readers to reflect on how technology and human motivation together shape sustainable teaching readiness in the AI-supported educational landscape.
- ANALISIS FAKTOR-FAKTOR YANG MEMENGARUHI DIABETES MELITUS DI JAWA BARAT MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINES (MARS): - Vera Maya Santi
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 02 (2025)
Publisher : Universitas Negeri Surabaya

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Abstract

Diabetes mellitus is a metabolic disorder characterized by chronically elevated blood sugar levels due to impaired insulin secretion or action. West Java ranks second among Indonesian provinces with the highest number of diabetes mellitus cases based on medical diagnoses. In 2022, the number of diabetes mellitus cases in this province reached its lowest point in the past five years, suggesting the influence of significant factors contributing to this decline. Therefore, identifying the factors affecting diabetes mellitus prevalence in West Java in 2022 is essential. However, the data exhibit no clear pattern, necessitating a nonparametric regression approach for modeling these factors. This study employs Multivariate Adaptive Regression Splines (MARS), a flexible method that partitions data into segments and applies linear regression within each segment. Model selection criteria include Generalized Cross Validation (GCV) and Akaike Information Criterion (AIC). Based on GCV, seven significant variables were identified, whereas AIC indicated eight significant variables influencing diabetes mellitus prevalence in West Java. Structural differences between models are also observed in the number of basis functions: the GCV model utilizes 13 basis functions, while the AIC model employs 14. In terms of model performance, the GCV model achieves an R² value of 0.994, whereas the AIC model attains an R² value of 0.995.
ANALYZING OPEN UNEMPLOYMENT RATE IN JAVA USING PENALIZED SPLINE NONPARAMETRIC REGRESSION Vera Maya Santi; Nia Rahayu Ningsih; Faroh Ladayya
International Journal of Applied Science and Sustainable Development (IJASSD) Vol. 4 No. 2 (2022): International Journal of Applied Science and Sustainable Development (IJASSD)
Publisher : Lembaga Penelitian dan `Pengabdian Kepada Masyarakat (LPPM)

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Abstract

In regression analysis, there are three regression curve approach methods: parametric approach, semiparametric approach, and nonparametric approach. One of the estimation methods in nonparametric regression is spline regression with parameter estimation methods, namely smoothing, truncated, and penalized. Penalized spline estimation controls the smoothness of the curve so that the curve avoids stiffness and overfitting and does not require assumptions. This study aims to analyze the open unemployment rate in Java, which has the highest open unemployment rate in Indonesia, where studies using this approach have never been conducted. The study's results resulted in an additive Mean Square Error (MSE) of 4.137 with a coefficient of determination of 44.58%, indicating that explanatory variables of 44.58% could explain the open unemployment rate. Based on the parameter significance test, the factors that significantly effect the open unemployment rate are the dependency ratio, the GDP growth rate, senior high school gross enrollment, percentage of the poor population, and population growth rate.
Analisis Kemampuan Mathematical Problem-Solving Dalam Pembelajaran Matematika: Systematic Literature Review Marweli Yusuf; Lukita Ambarwati; Vera Maya Santi
Griya Journal of Mathematics Education and Application Vol. 6 No. 2 (2026): Juni 2026
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v6i2.985

Abstract

Penelitian ini bertujuan menganalisis kemampuan mathematical problem-solving (MPS) dalam pembelajaran matematika melalui pendekatan Systematic Literature Review (SLR). MPS dipahami sebagai kemampuan siswa dalam memahami, merumuskan, merencanakan, dan menyelesaikan permasalahan matematis yang tidak memiliki prosedur penyelesaian langsung. Kajian dilakukan dengan mengikuti tahapan SLR, mulai dari perumusan pertanyaan penelitian, strategi dan metode pencarian, penetapan cakupan, hingga penyusunan search string. Pencarian artikel dilakukan melalui Google Scholar dan ERIC dengan kriteria inklusi enam tahun terakhir. Dari 50 artikel yang teridentifikasi, 15 artikel memenuhi kriteria final dan dianalisis secara mendalam. Hasil telaah menunjukkan bahwa sebagian besar penelitian menggunakan strategi pemecahan masalah Polya, sementara strategi Sumarmo, NCTM, serta Krulik dan Rudnick digunakan dalam frekuensi lebih rendah. Temuan juga mengungkap bahwa kemampuan MPS siswa masih tergolong rendah akibat keterbatasan penguasaan konsep, fleksibilitas kognitif, serta kapasitas memori kerja. Secara keseluruhan, SLR ini memberikan gambaran komprehensif mengenai definisi, tahapan, dan karakteristik soal MPS, serta menawarkan rekomendasi untuk meningkatkan implementasinya dalam pembelajaran matematika.
Zero Inflated Poisson Regression Analysis in Maternal Death Cases on Java Island Vera Maya Santi; Defina Ambarwati; Bagus Sumargo
Pattimura International Journal of Mathematics (PIJMath) Vol 1 No 2 (2022): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (442.104 KB) | DOI: 10.30598/pijmathvol1iss2pp59-68

Abstract

The basic regression model used to analyze the count data is the Poisson regression.. However, applying the Poisson regression model is unsuitable for excess zero data because it can cause overdispersion where the variance data is greater than its mean. One of the developments of the Poisson regression model can overcome this condition, Zero Inflated Poisson Regression (ZIP). In the health sector, the death of pregnant women on the Java island is an event that still rarely occurs and forms an excess zero data structure. However, the analysis of cases of maternal mortality using ZIP regression has never been studied in more depth. In this article, the maternal mortality cases in Java were modelled using ZIP regression to specify the variables that had a significant effect. The initial analysis results indicated the occurrence of overdispersion due to excess zero where there are 52% zero values in the data. The ZIP regression applied in this research provides enhancements to the Poisson regression based on the Vuong test. The results showed that the variables that had a significant effect on the maternal death cases in Java in the count model are the percentage of maternal health service coverage and the percentage of coverage of postpartum visit coverage, while in the zero-inflation model, the percentage of deliveries in health facilities and the percentage of obstetric complications treatment
Negative Binomial Regression in Overcoming Overdispersion in Extreme Poverty Data in Indonesia Vera Maya Santi; Yuliana Rahayuningsih
Pattimura International Journal of Mathematics (PIJMath) Vol 2 No 2 (2023): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol2iss2pp43-52

Abstract

Indonesia's extreme poverty status in 2021 was recorded to be high at 4% or 10.86 million people. One of the efforts in poverty alleviation is to analyze the factors influencing extreme poverty. Although the number of studies on poverty in Indonesia continues to grow, the findings are inconclusive because they are often discussed qualitatively. This study aimed to analyze the factors that influence extreme poverty in Indonesia using negative binomial regression. The data used was the amount of extreme poverty in 34 provinces of Indonesia as the response variable. Then, the explanatory variables used consist of 8 from the Central Bureau of Statistics. The analysis stage sought data exploration, the correlation between variables, Poisson regression model specification and assumption test, handling overdispersion with negative binomial regression, and model feasibility test. Based on the AIC value and dispersion ratio, the negative binomial model obtained an AIC value of 920.03 with a dispersion ratio 1.372. It shows that the negative binomial regression model is good enough to model extreme poverty in Indonesia. Furthermore, the factors significantly influencing extreme poverty in Indonesia are households with proper drinking water, housing status, and families with access to appropriate sanitation.
Damped Trend Exponential Smoothing and Holt-Winters in Forecasting the Number of Airplane Passengers at Kualanamu Airport Rustham Michael Binoto; Sudarwanto Sudarwanto; Vera Maya Santi
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 1 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss1pp29-40

Abstract

Airplanes are one of the most frequently chosen modes of transportation by Indonesians today. Kualanamu Airport is one of the busiest airports in terms of the number of passengers. The number of airplane passengers often fluctuates, increasing and decreasing, so an analysis method is required to predict the number of passengers. This study uses the Double Exponential Smoothing Damped Trend and Multiplicative Holt-Winters models. The number of Kualanamu Airport domestic airplane passengers from January 2006 to December 2023 was used as research data. The best model is then used to forecast the number of Kualanamu Airport domestic airplane passengers for 12 periods from the last data used. The results showed that the Multiplicative Holt-Winters model with smoothing parameters and obtained smaller (Mean Absolute Error) MAE and (Mean Square Error) MSE values of 21415.556 and 961525264.508, compared to the Double Exponential Smoothing Damped Trend model with smoothing parameters,, and which obtained MAE and MSE values of 23612.461 and 1061042411.507 in predicting the number of domestic aircraft passengers at Kualanamu Airport. Forecasting accuracy for the next 12 periods using Holt-Winters Exponential Smoothing produces a MAPE value of 9.2%. It shows the accuracy of forecasting in the very good category.
Co-Authors Abi Wiyono Adzima, Khaola Rachma Afifah Nur Mutia Alifia Taufika Rahma Ambarwati, Lukita Auria Yusrin Fathya Bagus Sartono Bagus Sumargo Bagus Sumargo Bagus Sumargo Bagus Sumargo, Bagus Baihaqi, Aulia Contillo, Gerry Dania Siregar Dania Siregar Defina Ambarwati Devi Eka Wardani Dhioatmaja Megafajari Dian Handayani Dian Handayani Dwi Antari Wijayanti Ellis Salsabila, Ellis Erin Naudy Kemalasari Fadya, Khansa Salsabil Fanya Izmi Hawa Faoza Saaroh Fariani Hermin Faroh Ladayya Gatri Eka Kusumawardhani Gusnia, Farida Herlina Nofita Ibnu Hadi Indahwati Indiyah, Fariani Hermin Jadid Irtakhoiri Jaisy Aulia Janna Sri Bina Br Barus Kamil, Adine Ihsan Kamilia, Rifa Khairunnisa Putri Alif Khoirunnisa Koeshella, Ajeng Ladayya, Faroh Lina Nafisah Lukman El Hakim Mahardika, Baihaqy Mahatma, Yudi Makmuri Marweli Yusuf Maulida Audia Firdaus Meidianingsih, Qorry Meila Nadya MUHAMAD RIFAN Muhammad Alief Ghifari Muhammad Rafli Muzakki Tamami NATALIE EFRATA SUSANTI Nia Rahayu Ningsih Nilam Novita Sari Nilam Novita Sari Novia Sucy Aristawidya Pinta Deniyanti Sampoerno Pinta Deniyanti Sampoerno Prima Riyani Rahayuningsih, Yuliana Rahfa Qur’aniyatin Dhuha Ria Arafiyah Riam Nurussilmah Rianiati Monica Rifqy Marwah Akhsanti Riska Agustin Riyantobi, Ariq Muammar Rustham Michael Binoto Safira Datu Sahila, Sahiba Sari Febrianti Sinta Rahmadani Siregar, Dania Siti Rohmah Rohimah Siti Rohmah Rohimah Sudarwanto Sudarwanto Sudarwanto SUYONO Suyono Suyono Suyono Suyono Syarifah Ayu Angela Syifa Azzahra Tamami, Muzakki Tian Abdul Aziz Tiara Husnul Khotimah Tri Murdiyanto Vinsensius Crispinus Lemba Wahyu, Rahadian Wardani Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Wilsen Wilsen Yuliana Rahayuningsih Zahra Ayu Rahmadani Zahrah Hashifah