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All Journal Journal of Mathematics Education and Application (JMEA) BAREKENG: Jurnal Ilmu Matematika dan Terapan Martabe : Jurnal Pengabdian Kepada Masyarakat MAJAMATH: Jurnal Matematika dan Pendidikan Matematika MES: Journal of Mathematics Education and Science Indonesian Journal of Education and Mathematical Science PHI: Jurnal Pendidikan Matematika Al'adzkiya International of Education and Sosial (AIoES) Journal Journal Mathematics Education Sigma [JMES] JUTECH : Journal Education and Technology Kognitif: Jurnal Riset HOTS Pendidikan Matematika Education Achievement: Journal of Science and Research Jurnal Abdimas Kartika Wijayakusuma Indo-MathEdu Intellectuals Journal MATH-EDU: Jurnal Ilmu Pendidikan Matematika Tsaqila Jurnal Pendidikan dan Teknologi ALSYS : Jurnal Keislaman dan Ilmu Pendidikan ARZUSIN: Jurnal Manajemen dan Pendidikan Dasar OMEGA: Jurnal Keilmuan Pendidikan Matematika Hanif Journal of Information Systems Jurnal Tadris Matematika (JTMT) Jurnal Pengabdiaan Masyarakat Larisma Tsabit
Azis, Zainal
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Pelatihan Penelitian Tindak Kelas Untuk Guru Muhammadiyah Di Kecamatan Binjai Kota Azis, Zainal; Muslihuddin, Rahmat; Irvan, Irvan
Jurnal Pengabdian Masyarakat Larisma Vol. 1 No. 1 (2024): Jurnal Pengabdian Masyarakat Larisma
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/jpml.v1i1.630

Abstract

Salah satu permasalahan yang dihadapi oleh guru yang mengajar di sekolah muhammadiyah di Binjai Kota adalah proses pembelajaran yang kurang maksimal yang akhirnya mengakibatkan kulitas pembelajaran yang kurang maksimal dan akhirnya hasil belajar yang kurang maksimal. Salah satu solusi untuk mengatasi permasalahan tersebut adalah dengan cara mengoptimalkan pelaksanaan pelatihan bagi guru-guru untuk meningkatakan kualitas pembelajaran salah satu nya adalah dengan Pelatihan Penelitian Tindak Kelas. Adapun materi pelatihannya adalah: 1) Hakikat PTK; 2) Pelaksanan PTK; 3) Penyusunan Proposal PTK: 4) Penyusunan Laporan PTK. Lokasi pelaksanaan pengabdian dilaksanakaan di Kota Binjai tepat nya Kompleks Perguruan Muhammadiyah yang beralamat Jl. K. H. Ahmad Dahlan No. 4 Binjai dengan jumlah peserta diperkirakan sebanyak 15 orang. Diharapkannya dengan pelaksanaan kegiatan pelatihan ini dapat mengatasi permasalahan yang dihadapi oleh guru yang mengajar di sekolah muhammadiyah di Binjai Kota.
IMPLEMENTASI DATA MINING DALAM PREDIKSI HARGA SAHAM BBNI DENGAN PEMODELAN MATEMATIKA MENGGUNAKAN METODE LSTM DENGAN OPTIMASI ADAM Rahman, Alrafiful; Istiyowati, Lucia Sri; Valentinus, Valentinus; Ivan, Ivan; Azis, Zainal
JUTECH : Journal Education and Technology Vol 5, No 2 (2024): JUTECH DESEMBER
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jutech.v5i2.4137

Abstract

Stock price prediction plays a crucial role in investment decision-making, allowing investors to maximize profits and minimize risks. This study implements the Long Short-Term Memory (LSTM) method with Adam optimization to predict the stock price of Bank Negara Indonesia (BBNI) based on historical stock price data from the Indonesia Stock Exchange (2001-2023). LSTM is chosen for its ability to handle sequential data and identify long-term patterns in time series. Meanwhile, the Adam optimization algorithm is used to accelerate model convergence and improve prediction accuracy. The data used includes daily stock prices (closing prices), and the research process involves data collection, preprocessing, LSTM model creation, Adam optimization, training, evaluation, and prediction. The experimental results show that the model with a batch size of 64 and 100 epochs yields an R² of 0.9928 and a MAPE of 1.53%, indicating a very high prediction accuracy. With an accuracy of 98.46%, the LSTM model with Adam optimization proves to be effective in predicting stock prices, providing excellent results for applications in investment strategies. This study demonstrates the great potential of applying data mining and machine learning techniques in more informed and data-driven stock market analysis.
PENGEMBANGAN E-MODUL BERBASIS DISCOVERY LEARNING MENGGUNAKAN SOFTWARE EXE-LEARNING PADA MATERI FUNGSI KELAS X SMA Haloho, Elysha Jefirayani; Azis, Zainal; Afnaria, Afnaria; Syahlan, Syahlan
MES: Journal of Mathematics Education and Science Vol 9, No 2 (2024): Edisi April
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v9i2.9755

Abstract

The rapid development of science and technology encourages renewal efforts in the utilization of various technological results in the learning process, such as utilizing digital-based learning media. This research aims to produce e-module learning tools based on discovery learning on quadratic function material for class X SMA students that are valid, practical, and effective. The research method used is Research and Development with Thiagarajan 4-D development model: define, design, develop, and disseminate. The subject of this research is the production of e-modules based on the discovery learning model. The object of this research is the students of SMA Negeri 1 Purba, totaling 33 students. The instruments used in this study were validation questionnaires and student responses to the e-modules developed as well as student learning outcomes tests. The results of this study indicate that the e-Module developed has met the requirements of validity and practicality as stated in the results of the questionnaire given. In addition, the e-module developed was also declared effective based on the student learning outcomes test with an average of 78,79% and included in the good category.
Meningkatkan Pemahaman Siswa pada Mata Pelajaran PPPKn melalui Model Problem Based Learning (PBL) di Kelas 1 SDN 067240 Medan Tembung Nurliana, Maulidya; Azis, Zainal; Purba, Enniy
ALSYS Vol 5 No 5 (2025): SEPTEMBER
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/alsys.v5i5.7131

Abstract

This study is motivated by the often monotonous teaching of Pancasila and Citizenship Education (PPPKn) in elementary schools, which tends to reduce students’ motivation to think critically and solve problems. An innovative learning model is needed to improve students’ understanding and interest. The objective of this research is to enhance the understanding and learning outcomes of Grade I students in PPPKn through the application of the Problem Based Learning (PBL) model at SD Negeri 067240 Medan Tembung. The study employed a Classroom Action Research (CAR) method conducted over two weeks in the even semester of the 2025 academic year, from 7 to 22 March 2025, involving 21 Grade I students. The research object was PPPKn learning outcomes after implementing the PBL model. The results show that a PBL approach designed to be enjoyable for students improved academic performance, with the average score increasing from 71.81 in cycle I to 80.52 in cycle II. The percentage of students achieving mastery also rose from 62% in cycle I to 86% in cycle II, surpassing the success indicator of 80% of students meeting the Minimum Mastery Criteria (Kriteria Ketuntasan Minimal, KKM). These findings demonstrate that the PBL model is effective in improving PPPKn understanding and learning outcomes in elementary school students.
Implementation Draft Programming Oriented Objects in Parking System Application using Language Programming Java Siambaton, Muhammad Zulfansyuri; Azis, Zainal; Harahap, Tua Halomoan
Tsabit Journal of Computer Science Vol. 1 No. 1 (2024): June Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/tsabit24

Abstract

The development of Information Technology has become increasingly rapid. Many agencies or companies that have used information systems for operations processes that manually become an automated and integrated system. One of which is a parking system. In Indonesia there are still many vehicle day care stations that use a parking system manually. This makes the parking attendant unfamiliar with the price set and the lengths of time parked the vehicle and make it difficult in the process of calculating the report of parked vehicles. For this reason, an integrated parking system is needed so that it can be applied to manual vehicle storage. So in making the parking system uses the concept of programming. The concept of the program to be used is the concept of Object Oriented Programming with the Java programming language and the editor uses Netbeans 8.2 to run the program. The method in conducting this research is to use 2 methods, namely the method for collecting data with the description method and the method for developing a waterfall system. With the parking system will provide convenience for parking users and also make efficient parking attendant performance. So expect speed, and accuracy in collecting vehicle parking at a vehicle storage in Indonesia.
Development of Learning Materials Based on the MURDER Collaborative Learning Model to Enhance Students’ Conceptual Understanding of Mathematics Rahmayani, Sri; Afnaria, Afnaria; Azis, Zainal
Kognitif: Jurnal Riset HOTS Pendidikan Matematika Vol. 5 No. 4 (2025): October - December 2025
Publisher : Education and Talent Development Center Indonesia (ETDC Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51574/kognitif.v5i4.2422

Abstract

The low level of students’ conceptual understanding in mathematics highlights the need for innovative and structured learning approaches. This study aims to develop mathematics learning materials based on the MURDER collaborative learning model (Mood, Understand, Recall, Digest, Expand, and Review) to enhance students’ conceptual understanding. The research employed a Research and Development (R&D) design involving expert validation, limited trials, and classroom implementation to evaluate the validity, practicality, and effectiveness of the developed module. The model helps students recall and comprehend mathematical concepts more effectively, supporting both teaching and learning processes in the classroom. The product was validated by three expert groups. Content validation produced an average score of 88.2%, media validation 92.5%, and language validation 85.5%, with an overall mean of 88.7%, indicating that the module is highly feasible. Practicality testing, based on student response questionnaires, yielded an average score of 82%, classified as highly practical. Effectiveness testing in a Grade 10 science class involving 30 students resulted in a mean score of 83.6%, categorized as highly effective. Furthermore, the N-Gain value of 0.81demonstrates a high improvement in students’ conceptual understanding after using the module. These results confirm that the MURDER-based mathematics learning module is valid, practical, and effective for improving students’ conceptual understanding, particularly in learning the sine and cosine rules. The developed module can serve as a reference for schools and educators seeking to implement collaborative and conceptually oriented mathematics learning.
PELATIHAN DAN PENDAMPINGAN PEMBUATAN PERANCAH INTERAKTIF BERBASIS WEB DAN PENERAPANNYA DALAM MODEL CONTEXTUAL TEACHING AND LEARNING DI SMP MUHAMMADIYAH 01 MEDAN Azis, Zainal; Harahap, Tua Halomoan; Dachi, Surya Wisada
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 5, No 2 (2022): Martabe : Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v5i2.604-608

Abstract

The proposed partnership program is intended to solve two partner problems (SMP Muhammadiyah 01 Medan), namely: (1) lack of partner teacher skills in the design and implementation of online teaching where the learning structure is dominated by assignments, unavailability of scaffolding, and only a small part of the time. Meetings are used for explanations, and (2) teachers do not understand how to choose an appropriate learning model for the topic being taught. In the context of online learning, such difficulties will increase. The solutions offered to overcome the first problem are training in a web-based interactive scaffolding development workshop using Articulate Storyline 3 software, an online class development workshop using Google Classroom, and an online teaching design workshop including learning tools. The solution offered to overcome the second problem is assistance in applying web-based interactive scaffolding in the CTL model. The program implementation method refers to the Learn-Teach-Evaluate-Acknowledge method proposed by Buckenmeyer et al. (2013), which has been modified and agreed upon by the Proposing Team and partners to resolve specific problems faced by partners. The modifications made are: (1) Adding a Fostering phase (coaching) for the sustainability of activities; and (2) the adjustment of each phase to the principles of adult learning, as proposed by Alamdari et al. (2017), which focuses on experiential learning and self-motivation to encourage participants and instructors to participate actively.
An Optimization Approach Goal Programming to Improve the Academic and Administrative Quality of Postgraduate Programs Azis, Zainal; Al-Khowarizmi, Al-Khowarizmi; Harahap, Tua Halomoan; Firdaus, Muliawan; Irvan, Irvan
Indonesian Journal of Education and Mathematical Science Vol 7, No 1 (2026)
Publisher : Universitas Muhammadiyah Sumatera Utara (UMSU)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ijems.v7i1.28873

Abstract

The main objective of this article is to implement the GP approach to improve academic and administrative performance at UMSU postgraduates. In the context of expected results, this article is intended so that UMSU postgraduates can establish strategies to achieve higher academic standards and create a more conducive educational environment through achieving predetermined targets, which include improving the quality of teaching and learning, effectiveness of program administration, and student and lecturer satisfaction with the academic process. The article can make a significant contribution to the academic literature in the field of educational management and operations by offering a new perspective on the application of GP and AHP in a higher education context. Specifically, this article shows how quantitative approaches can be used to improve decision making in the management of academic programs and administration, thereby providing valuable practical and theoretical insights for the development of educational policy and managerial practice in the higher education sector. It can be seen from the results that the parameters in this paper contribute to the weight of the objective (w_1), target (T_1), and the budget constraint (B), all of which play an important role in determining the optimal solution produced by the model
Comparison of Logistic Regression and K-Nearest Neighbor (KNN) Algorithms in a Heart Failure Prediction Dataset Nasution, Julia Namira; Azis, Zainal
Hanif Journal of Information Systems Vol. 3 No. 1 (2025): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v3i1.53

Abstract

Heart failure is one of the leading causes of death worldwide. Early detection of heart failure risk is crucial to minimize its serious consequences. This study aims to compare the performance of two machine learning algorithms, namely Logistic Regression and K-Nearest Neighbor (KNN), in predicting heart failure using a dataset from the Kaggle platform. The research stages include data preprocessing, normalization, splitting into training and testing data, model implementation, and evaluation using a confusion matrix. Evaluation is based on accuracy, precision, recall, and F1-score metrics. The results show that Logistic Regression achieved an accuracy of 88.04% with an execution time of 0.022 seconds, while KNN achieved an accuracy of 85.51% with an execution time of 0.158 seconds. Logistic Regression outperformed in recall and F1-score, making it more effective for early detection of heart failure. Therefore, Logistic Regression is considered more optimal than KNN in the context of this study. However, Logistic Regression is not always superior to K-Nearest Neighbor, as prediction results highly depend on the characteristics of the specific case.
Co-Authors Afnaria, Afnaria Akbar, Rahmat Al Khowarizmi Ammy, Putri Maisyarah Annisa, Dewi Sry Ardiningtyas, Mesayu Azmi, Muhammad Bima Darmawati Darmawati Dedy Kiswanto Fajar, Maulana Haloho, Elysha Jefirayani Hasibuan, Ahmad Riady Ikhlas Hamzani Irvan Irvan Irvan, Irvan Ivan Ivan Khoiruddin Matondang Lubis, Tri Resti Andini Lubis, Ulfa Annisa Lucia Sri Istiyowati Marah Doly Nasution Muslihuddin, Rahmat Nasution, Asrindah Nasution, Julia Namira Nurhayati Nurhayati Nurliana, Maulidya Nurlinda, Epi Nurul Maulida Surbakti Panggabean, Suvriadi Pasha, Leony Ayu Diah Purba, Enniy purba, oktaviana nirmala Puspita, Ananda Putri, Linda Syah Rahim, Rani Rahman, Alrafiful rahmayani, sri Risna Mira Bella Saragih Rizka Fahruza Siregar RR. Ella Evrita Hestiandari Siambaton, Muhammad Zulfansyuri Siregar, Rosliana Siswadi Siswadi Surya Wisada Dachi Syahlan, Syahlan Tua Halomoan Harahap, Tua Halomoan Valentinus, Valentinus Yusma, Ira Zega, Lipur Ju Priman