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All Journal AKSIOMA: Jurnal Program Studi Pendidikan Matematika Jurnal Daya Matematis JESS (Journal of Education on Social Science) UNP Journal of Statistics and Data Science Jurnal ISO: Jurnal Ilmu Sosial, Politik dan Humaniora
Syafriandi Syafriandi
Universitas Negeri Padang
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Environmental Science Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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PENGEMBANGAN ALUR BELAJAR BERBASIS REALISTIC MATHEMATICS EDUCATION PADA MATERI BARISAN DAN DERET Yanrizawati Yanrizawati; Armiati Armiati; Edwin Musdi; Syafriandi Syafriandi
AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vol 12, No 1 (2023)
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1700.87 KB) | DOI: 10.24127/ajpm.v12i1.6319

Abstract

Penelitian ini bertujuan untuk mengetahui proses pengembangan produk alur belajar barisan dan deret berbasis Realistic Mathematics Education (RME). Penelitian pengembangan ini menggunakan kombinasi model pengembangan Plomp dan Gravemeijer & Cobb. Penelitian ini dilaksanakan berdasarkan hasil studi pendahuluan dimana masih banyaknya siswa terkendala belajar matematika dan menyelesaikan permasalahan sehari-hari matematika serta masih kurangnya guru membuat alur belajar berbasis masalah yang dekat dengan kehidupan sehari-hari siswa khususnya di Pasaman barat. Pada penelitian ini dilaksanakan uji validasi oleh ahli matematika, ahli bahasa dan ahli teknologi pendidikan serta uji kelayakan produk oleh guru dan siswa. Instrument pengumpulan data berupa lembar validasi, observasi, wawancara, angket dan catatan lapangan. Analisis data yang digunakan adalah statistik deskriptif dan teknik deskriptif. Dari hasil analisis diperoleh data validasi para ahli 0,77 dengan kriteria “valid” dan indeks Intraclass Correlation Coefficient (ICC) 0,54 kategori sedang. Sedangkan untuk buku guru diperoleh data validasi 0,75 kategori “valid” dan indeks ICC 0,72 kategori sedang. Validasi para ahli untuk buku siswa 0,77 dengan kategori “valid” dan indeks ICC 0,68 kategori sedang. Uji kelayakan produk oleh siswa (kelompok kecil) 80,91 % dengan kategori “praktis”dan uji kelayakan kelompok besar 82,71% dengan kriteria kriteria “praktis”. This study aims to determine the product development process for sequences and series based on Realistic Mathematics Education (RME). This development research uses a combination of the Plomp and Gravemeijer & Cobb development models. This research was carried out based on the results of a preliminary study where there were still many students who were constrained by learning mathematics and solving everyday math problems and there was still a lack of teachers making problem-based learning paths that were close to students' daily lives, especially in West Pasaman. In this study, validation tests were carried out by mathematicians, linguists and educational technologists as well as product feasibility tests by teachers and students. Data collection instruments were validation sheets, observations, interviews, questionnaires and field notes. Data analysis used is descriptive statistics and descriptive techniques. From the results of the analysis, the expert validation data was 0.77 with the criteria of "valid" and the Intraclass Correlation Coefficient (ICC) index was 0.54 in the moderate category. As for the teacher's book, the validation data was 0.75 in the "valid" category and the ICC index was 0.72 in the moderate category. Expert validation for student books is 0.77 in the "valid" category and the ICC index is 0.68 in the moderate category. Product feasibility test by students (small group) 80.91% with the "practical" category and large group feasibility test 82.71% with "practical" criteria.
DEVELOPMENT OF ARCS-BASED LEARNING TOOLS CONTAINING HOTS QUESTIONS TO IMPROVE THE CRITICAL THINKING ABILITY OF CLASS VIII SMP/MTS STUDENTS Fauziah Putri Putri; Yerizon Yerizon; I Made Arnawa; Syafriandi Syafriandi
Daya Matematis: Jurnal Inovasi Pendidikan Matematika Vol 11, No 2 (2023): Juli
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/jdm.v11i2.47886

Abstract

The literature study and preliminary analysis conducted showed that students' critical thinking skills were still low. This study aims to determine the characteristics of Attention, Relevance, Confidence, Satisfaction (ARCS)-based learning tools that contain valid, practical, and effective HOTS questions to improve the critical thinking skills of class VIII students of SMP N 6 Padang Panjang. This research is a development research using the Plomp model. The learning tools developed are in the form of Learning Implementation Plans (RPP) and Student Activity Sheets (LKPD). The research subjects were students of class VIII SMP N 6 Padang Panjang. Data was collected through documentation, observation, interviews, questionnaires, and tests of critical thinking skills. RPP Validity Score: 3.28 and LKPD: 3.21 with a valid category. Practicality of RPP: 92.08% and LKPD: 87.35% with very practical category. The effectiveness of learning tools based on testing the average critical thinking skills of the experimental class was 81.93, control class was 76.63. Based on statistical tests, a significance value of 0.048 <0.05 was obtained, and based on the list of t distribution tables with (????????)=60 and a=0.05, 1.671. Because t_count= 2.108>1.671=t_(table) then H0 is rejected and accepts H1. Based on the test results, it can be concluded that the ARCS-based learning tools contain HOTS questions that meet valid, practical, and effective criteria to improve students' mathematical thinking skills.
LKPD BERBASIS MODEL CREATIVE PROBLEM SOLVING BERBANTUAN SOFTWARE G-SUITE UNTUK MENINGKATKAN KEMAMPUAN PEMECAHAN MASALAH MATEMATIS Yarmaina Yarmaina; Edwin Musdi; Syafriandi Syafriandi; Yerizon Yerizon
AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vol 13, No 2 (2024)
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/ajpm.v13i2.8562

Abstract

 Kurangnya keterampilan pemecahan masalah di kalangan siswa dibuktikan dengan kesulitan mereka dalam menangani masalah matematika secara efektif. Kurangnya akses terhadap materi pembelajaran yang mendukung memperparah masalah ini. Selain itu, integrasi teknologi yang kurang optimal dalam pendidikan matematika berkontribusi terhadap pelepasan siswa dari proses pembelajaran. sehingga diperlukan pendekatan atau model pedagogi yang mampu mengatasi tantangan-tantangan ini. Model yang diusulkan adalah Creative Problem Solving (CPS), yang dilengkapi dengan perangkat lunak G-Suite for Education. Penelitian ini bertujuan untuk meningkatkan kemampuan pemecahan masalah matematis peserta didik. Model penelitian ini mengikuti metodologi Plomp yang meliputi tahapan penyelidikan awal, pengembangan atau prototyping, dan penilaian. Kerangka pembelajaran yang dikembangkan meliputi pemahaman masalah, perencanaan solusi, implementasi, dan evaluasi. Temuan penelitian menunjukkan keefektifan model CPS berbantuan G-Suite, yang mencapai tingkat keberhasilan sebesar 84%. Selanjutnya tanggapan siswa terhadap model ini adalah positif. Kesimpulannya bahwa pemanfaatan Lembar Kerja Siswa (LKPD) berbasis model CPS dengan dukungan G-Suite meningkatkan kemampuan pemecahan masalah matematis siswa dalam ranah pendidikan matematika. The lack of problem solving skills among students is evidenced by their difficulty in dealing with mathematical problems effectively. Lack of access to supportive learning materials exacerbates this problem. In addition, less than optimal integration of technology in mathematics education contributes to student disengagement from the learning process. so a pedagogical approach or model is needed that is able to overcome these challenges. The proposed model is Creative Problem Solving (CPS), which is equipped with G-Suite for Education software. This research aims to improve students' mathematical problem solving abilities. This research model follows the Plomp methodology which includes stages of initial investigation, development or prototyping, and assessment. The learning framework developed includes problem understanding, solution planning, implementation and evaluation. Research findings demonstrate the effectiveness of the G-Suite-assisted CPS model, achieving a success rate of 84%. Furthermore, students' responses to this model were positive. The conclusion is that the use of Student Worksheets (LKPD) based on the CPS model with G-Suite support improves students' mathematical problem solving abilities in the realm of mathematics education.
PRAKTIKALITAS E-MODUL BERBASIS PROBLEM BASED LEARNING UNTUK MENINGKATKAN KEMAMPUAN PEMECAHAN MASALAH MATEMATIS SISWA Nofrinaldi Hendriko; Syafriandi Syafriandi; Armiati Armiati; Elita Zusti Jamaan
AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vol 13, No 3 (2024)
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/ajpm.v13i3.8921

Abstract

Salah satu standar kemampuan matematika yang berperan besar bagi siswa adalah kemampuan pemecahan masalah. Namun dalam kenyataannya Kemampuan siswa dalam menyelesaikan masalah matematika masih kurang baik. Hal ini dikarenakan siswa kurang berlatih dalam menyelesaikan soal-soal yang memuat kemampuan pemecahan masalah dan soal-soal non rutin, pembelajaran di kelas masih berfokus kepada guru, secara umum, materi pembelajaran yang digunakan terbatas pada buku pelajaran. Oleh karena itu, e-modul berbasis Pembelajaran Berbasis Masalah (PBL) dikembangkan dengan tujuan untuk meningkatkan kemampuan siswa dalam memecahkan masalah. Prosedur pengembangan menggunakan model Plomp yang terdiri dari tiga fase, yaitu fase investigasi awal, fase pengembangan atau pembuatan prototipe serta fase penilaian. Subjek Uji coba adalah siswa Kelas VIII SMPN 1 Painan. Instrumen penelitian yang digunakan yaitu angket validitas dan angket praktikalitas. Uji validitas dilakukan oleh 3 orang ahli matematika, 1 orang ahli bahasa dan 1 orang ahli teknologi guruan. Uji praktikalitas dibatasi pada tahap Small group dengan 6 orang siswa. Penelitian menggunakan teknik deskriptif dan statistik deskriptif dalam analisis data. Selanjutnya, hasil penelitian menunjukkan bahwa e-modul berbais PBL sudah valid dengan skor 90,51% dan praktis digunakan dengan skor pada tahap small group 81,15% . Berdasarkan hasil penelitian disimpulkan bahwa e-modul berbasis PBL praktis dalam hal keterbacaan dan kejelasan materi, keterpakaian dan kemudahan penggunaan, daya tarik dan kesesuaian alokasi waktu serta praktis digunakan dalam meningkatkan kemampuan pemecahan masalah matematis siswa.One of the significant standards for students' mathematical abilities is problem-solving skills. However, in reality, students' mathematical problem-solving skills are still low. This is due to the need for more practice in solving problems that involve problem-solving skills and non-routine questions. Classroom learning is still teacher-focused, and instructional materials rely solely on textbooks. Therefore, an e-module based on Problem-Based Learning (PBL) has been developed to enhance students' problem-solving abilities. The development procedure follows the Plomp model, consisting of three phases: the initial investigation phase, the development or prototype creation phase, and the assessment phase. The trial subjects are eighth-grade students from SMPN 1 Painan. Research instruments used include validity questionnaires and practicality questionnaires. Validity testing involves three mathematics experts, one language expert, and one educational technology expert. Practicality testing is limited to the small group stage with six students. Research utilizes descriptive and descriptive statistical techniques in data analysis. The research results indicate that the PBL-based e-module is valid, with a score of 90.51%, and practical for use in the Small group stage, with a score of 81.15%. Based on the research findings, the PBL-based e-module is practical regarding readability and clarity of content, usability and ease of use, attractiveness and suitability of time allocation, and practical for enhancing students' mathematical problem-solving abilities.
Peran Budaya Organisasi dalam Mendorong Inovasi Birokrasi Sektor Publik Syafriandi Syafriandi; Aldri Frinaldi
Jurnal ISO: Jurnal Ilmu Sosial, Politik dan Humaniora Vol. 6 No. 1 (2026): June
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/iso.v6i1.3582

Abstract

Artikel ini bertujuan untuk menganalisis tren penelitian serta perkembangan konsep inovasi pelayanan publik dan tata kelola pemerintahan di Indonesia melalui pendekatan kajian literatur berbantuan analisis bibliometrik. Penelitian ini menggunakan metode literature review naratif yang dipadukan dengan analisis bibliometrik terhadap 548 artikel ilmiah yang diterbitkan pada periode 2020–2025, diperoleh dari basis data jurnal nasional dan internasional. Analisis bibliometrik dilakukan menggunakan perangkat lunak VOSviewer untuk memetakan pola publikasi, jaringan kolaborasi penulis, serta klaster tema penelitian. Hasil penelitian menunjukkan bahwa fokus kajian didominasi oleh isu digitalisasi pelayanan publik, inovasi birokrasi, tata kelola pemerintahan berbasis teknologi, serta partisipasi dan kolaborasi multipihak. Meskipun demikian, temuan juga mengindikasikan masih terbatasnya integrasi antar kebijakan, ketimpangan kapasitas sumber daya manusia, serta kesenjangan infrastruktur digital sebagai tantangan utama dalam implementasi inovasi. Artikel ini menegaskan pentingnya penguatan kepemimpinan birokrasi, sinergi kebijakan, dan pelibatan masyarakat untuk mewujudkan tata kelola pemerintahan yang adaptif dan berkelanjutan.
Implementasi Kebijakan Penanganan Perlintasan Sebidang Tidak Terdaftar dalam Rangka Keselamatan Kereta Api dan Masyarakat di Sumatera Barat Syafriandi Syafriandi; Aldri Frinaldi
Journal of Education on Social Science (JESS) Vol 10 No 2 (2026): Public Participation in Public Service
Publisher : Faculty of Social Science, Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jess.v10i2.678

Abstract

This study analyzes the implementation of policies for handling unregistered level crossings to improve railway and public safety in West Sumatra. The issue is significant because unregistered level crossings remain dominant, with 189 of 310 active crossings, and accident data from 2021–2025 show continuing safety risks involving road users, fatalities, serious injuries, and minor injuries. This research employed a descriptive qualitative approach using grounded theory analysis. Data were collected through in-depth interviews, field observations, and documentation involving 37 informants from railway regulators, operators, local governments, law enforcement agencies, field officers, and road users. Data analysis was conducted through open coding, axial coding, and selective coding. The findings indicate that policy implementation is influenced by institutional authority, cross-sector coordination, resource limitations, technical risks at crossings, public access needs, road user behavior, and community acceptance. The study found that handling unregistered level crossings cannot rely solely on physical closure, as many crossings function as daily access routes for communities. Therefore, effective policy implementation requires risk-based data collection, clarification of authority, inter-agency coordination, improvement of safety facilities, continuous public education, law enforcement, and provision of alternative access routes. The core finding shows that the handling of unregistered level crossings must be based on institutional synergy, safety considerations, and community acceptance. This study contributes to public administration and transport safety governance by emphasizing a collaborative, data-driven, and socially responsive model for managing unregistered level crossings.
Classification of Stroke Desease Using the Learning Vector Quantization Algorithm Andriarmi Andriarmi; Chairina Wirdiastuti; Syafriandi Syafriandi
UNP Journal of Statistics and Data Science Vol. 4 No. 2 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss2/499

Abstract

Stroke is one of the leading causes of death and disability worldwide, thereby making early detection crucial for timely and appropriate medical treatment. In clinical practice, stroke diagnosis is generally carried out through medical examinations and patient history analysis, but this process is time-consuming and depends on the subjective judgment of medical personnel. Therefore, machine learning approaches can be utilized to support disease classification more quickly and objectively. This study aims to analyze the performance of the Learning Vector Quantization (LVQ) method in classifying stroke disease using a dataset obtained from Kaggle. The dataset used in this study is imbalanced;therefore, the SMOTE (Synthetic Minority Over-sampling Technique) method was applied to handle class imbalance. The research stages included data preprocessing, splitting data into training and testing sets, LVQ model training, parameter optimization using learning rate and maximum epoch, and model evaluation using accuracy and sensitivity. The results show that the LVQ model trained on the original dataset achieved an accuracy of 95,72%, but failed to detect stroke cases with a sensitivity of 0%. After applying SMOTE, the best model achived a stroke sensitivity of 90%, although the accuracy decreased to 49,49% due to the high number of false positives. These findings indicate that LVQ is highly sensitive to data distribution and model parameters, making its performance on this dataset less optimal for stroke classification and more suitable as an initial screening tool.
Classification of Dropout Rates in West Sumatra Using the Random Forest Algorithm with Synthetic Minority Oversampling Technique Anita Fadila; Syafriandi Syafriandi; Yenni Kurniawati; Admi Salma
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss3/183

Abstract

This study aims to classify school dropout rates in West Sumatra Province using the Random Forest algorithm with the Synthetic Minority Oversampling Technique (SMOTE). Based on 2021 data from the Ministry of Education, Culture, Research, and Technology (Kemdikbudristek), the dropout rate in West Sumatra is above the national average. Despite efforts to reduce dropout rates, results remain suboptimal. Therefore, this study seeks to identify the causes of student dropouts and compare the performance of the Random Forest algorithm with and without SMOTE. The study uses the 2021 dropout data from West Sumatra, which has a significant class imbalance. SMOTE is applied to balance the data. The dataset is split into training and testing sets in an 80%:20% ratio, and parameter tuning is performed to optimize mtry and the number of trees (ntree). The model is evaluated using a confusion matrix to compare performance. The results show that Random Forest with SMOTE outperforms the version without SMOTE, with improvements in precision, recall, and F1-score. The presence of the biological mother ( ) is identified as the most significant factor influencing student dropouts, based on the Mean Decrease Gini value. The study concludes that using SMOTE in the Random Forest algorithm helps reduce classification bias and enhances the model's ability to detect students at risk of dropping out.
Application of Extreme Learning Machine Algorithm (ELM) in Forecasting Inflation Rate in Indonesia Yonggi Septa Pramadia Yonggi; Zamahsary Martha; Syafriandi Syafriandi; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss3/194

Abstract

One indicator to determine the economic stability of a country can be seen from the inflation rate of a country. Inflation is an economic symptom in the form of a general increase in prices or a tendency to increase the prices of goods and services in general and continuously. In an effort to anticipate the impact of inflation in the future, an analysis is needed to find out how the development of the inflation rate is by forecasting. Extreme Learning Machine (ELM) is a feed-forward artificial neural network (ANN) algorithm with one hidden layer called Single Hidden Layer Neural Networks (SLFNs). Based on the research, forecasting the inflation rate in Indonesia using the Extreme Learning Machine algorithm obtained the best architecture  (12,48,1) with a MAPE value of 11%. These results show good forecasting because the resulting MAPE is relatively low.
Mixed Geographically Weighted Regression Modeling of Gender Development Index in Indonesia Nikma Hasanah; Dodi Vionanda; Syafriandi Syafriandi; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss3/207

Abstract

The Gender Development Index (GDI) is one of the primary measures of gender equality in the field of human development. Indonesia's GDI statistics for 2023 show the development gap between men and women. Using Mixed Geographically Weighted Regression (MGWR), a blend of regression and Geographically Weighted Regression (GWR) models, to identify the factors influencing GDI is one approach to closing the gap. The results showed that when it came to value selection using the Akaike Information Criterion (AIC), the MGWR model outperformed the GWR model. Population with health complaints and adjusted per capita expenditure were found to be globally influential factors, while female participation in parliament, open unemployment rate, and labor force participation rate were found to be locally influential factors by the MGWR model with Adaptive Kernel Bisquare weights.
Co-Authors Aldri Frinaldi Andriarmi Andriarmi anice kartika Anita Fadila Armiati Chairina Wirdiastuti Dina Fitria Dodi Vionanda Edwin Musdi Elita Zusti Jamaan Eujeniatul Jannah Eujeniatul Jannah Eujenniatul Jannah Fadhilah Fitri Fadhira Vitasya Putri Fauziah Putri Putri I Made Arnawa Laksono Trisnantoro Nabila Husni Nikma Hasanah Nofrinaldi Hendriko Nur Leli Rheizma Dewi Adiningtiyas Salma, Admi Siti Nurhaliza Tessy Octavia Mukhti Winda Fariza Winda Fariza Wita Resfi Ananta Wita Yanrizawati Yanrizawati Yarmaina Yarmaina Yerizon Yerizon Yonggi Septa Pramadia Yonggi Zamahsary Martha