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Desimal: Jurnal Matematika
Published by Universitas Islam Negeri Raden Intan Lampung
ISSN : 26139073     EISSN : 26139081     DOI : -
Core Subject : Education, Social,
Education Mathematics Social Sciences
Desimal: Jurnal Matematika, particularly focuses on the main issues in the development of the sciences of mathematics education, mathematics education, and applied mathematics. Desimal: Jurnal Matematika published three times a year, the period from January to April, May to Augustus, and September to December. This publication is available online via open access.
Arjuna Subject : -
Articles 310 Documents
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The effectiveness of the learning models and students’ critical thinking skills on mathematics learning outcomes in tangent lines to a circle Ropang, Marlita; Mustamin Idris
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202528708

Abstract

Discovery learning was a learning model that encouraged students to actively construct their own knowledge, while critical thinking skills were essential for analyzing, reasoning, and solving mathematical problems. This study aimed to (1) determine whether there was a difference in mathematics learning outcomes between students taught using the discovery learning model and those taught using a conventional learning model and (2) determine whether there was a difference in mathematics learning outcomes between students with high and low critical thinking skills. The results showed that: (1) the discovery learning model was more effective than the conventional model in improving students’ mathematics learning outcomes (p = 0.019 < 0.05); (2) critical thinking skills had a significant effect on students’ mathematics learning outcomes (p = 0.040 < 0.05); (3) the combination of discovery learning and critical thinking skills provided better effectiveness, as students with both high and low critical thinking skills in the experimental class achieved relatively higher learning outcomes compared to those in the control class.
Uncovering the potential of mining stocks: Analysis of price prediction and fundamental performance using double exponential smoothing and discounted cash flow Kamila, Isti; Mushliha; Indrawan; Azka, Muhammad; Sembiring, Brema
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202528611

Abstract

The purpose of this research was to forecast the stock prices of the mining sector using the Double Exponential Smoothing method and to determine the intrinsic value of stocks using the Discounted Cash Flow method as a recommendation for investment decisions in stocks. The data used was secondary data consisting of closing prices and financial reports from 2022 to 2024 for 10 mining stocks listed on the Main Board of the Energy sector on the IDX website. Based on the results of determining the intrinsic value of the stocks using the DCF method, seven mining stock issuers were categorized as undervalued, namely ABMM, BUMI, BYAN, DEWA, GEMS, HRUM, and INDY, while three other stock issuers were categorized as overvalued, namely ADRO, DSSA, and ITMG. Based on the forecasting results using the Double Exponential Smoothing method, from the seven issuers in the undervalued category, there were two issuers, BYAN and DEWA, that have the potential to experience a price increase. The results of the stock price forecasting evaluation using MAPE show that it was categorized as very accurate with a MAPE value range of 0.6% to 3.5%.
Performance evaluation of clustering algorithms for protein sequence data Ardaneswari, Gianinna; Aminah, Siti; Awang, Mohd Khalid; Laksmitara, Anindya; Azkiya, Azkal; Razi, Fakhrur; Joshua Situmeang, Jason Nimrod
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202528462

Abstract

Protein sequence data analysis is a fundamental task in bioinformatics, supporting the exploration of biological variations and the identification of functional relationships among proteins. This study presents a performance analysis of four clustering algorithms, which include Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Agglomerative Hierarchical Clustering, and Spectral Clustering, applied to protein sequence datasets. Feature extraction was conducted using the Discere package in Python, generating 27 numerical attributes from protein sequences. The optimal number of clusters for BIRCH, Agglomerative, and Spectral Clustering was determined using the Elbow method, while DBSCAN parameters (MinPts, Eps) were tuned using the sorted k-distance plot. Clustering performance was assessed using the Silhouette Score. Among the algorithms, DBSCAN produced the highest silhouette score of 0.8105, whereas BIRCH achieved a strong balance between clustering quality, with a score of 0.7405, and computational efficiency. Agglomerative clustering provided moderate results with a score of 0.6779, while Spectral clustering yielded the lowest score of 0.6310 but demonstrated flexibility in capturing complex structures. These findings provide a benchmark comparison of clustering methods for protein sequence data, offering practical insights into algorithm selection based on data characteristics and performance trade-offs.
Dynamics of predator–prey populations with allee effects under the influence of two generalist predators Pratama, Rian Ade; Suryani, Dessy Rizki; Ruslau, Maria F V
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202528849

Abstract

In this study, we analyze a predator–prey model incorporating a Holling type II functional response, an Allee effect in the prey population, and generalist predator species. The proposed interaction model is formulated as a nonlinear differential system involving three species: one prey species and two generalist predator species. The research methodology combines literature review and analytical investigation. The objectives are to examine the equilibrium points, assess stability using the Routh–Hurwitz criteria, and perform numerical simulations to illustrate population growth trajectories. The analysis reveals eleven equilibrium points, consisting of trivial, semi-trivial, and coexistence equilibria. Among the coexistence equilibria, only one satisfies the local stability conditions, as determined by the characteristic equation associated with the Routh–Hurwitz criteria. The characteristic equation of the model is a complex quartic polynomial. Ecologically, such local stability conditions ensure the persistence of all species within the ecosystem. Numerical simulations are also provided for the proposed model, demonstrating stable conditions for all three populations. However, the population growth patterns of the three species differ significantly. The prey population exhibits pronounced fluctuations: initially showing a gradual change, followed by a rapid increase once predation occurs, eventually reaching a stable state. Interestingly, during predation events, the overall prey population size experiences substantial growth. When predation proceeds without significant hindrance, predator populations also increase simultaneously. The interplay between the Allee effect and the Holling type II functional response plays a critical role in determining the numerical dynamics of the predator–prey system.
Enhancing public service quality in border regions through fuzzy time series forecasting: A case study of the Timor Tengah Utara regional library Humoen, Oktovianus; Binsasi, Eva; Mada, Grandianus Seda; Blegur, Fried Markus Allung; Bano, Elinora Naikteas
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202528958

Abstract

Forecasting the demand for public services is often overlooked in border regions, where data-driven management remains limited. However, accurate forecasts are essential for improving service quality and optimizing the use of public facilities. This study aims to predict the number of university student visits to the Regional Library of Timor Tengah Utara (TTU) Regency, an Indonesian border area, using Chen’s fuzzy time series (FTS) model. The dataset consists of monthly records of university student visits from April 2022 to September 2025. The forecasting process involves fuzzification, the establishment of fuzzy logical relationships, and defuzzification to obtain predicted values. The results show that the number of student visits decreased from 240 in April 2022 to 213 in October 2025. The model achieved a Mean Absolute Percentage Error (MAPE) of 35.15%, indicating a fairly good forecasting accuracy. This study extends the application of Chen’s FTS model to library management forecasting in developing and border regions. In the long term, improved forecasting and service planning are expected to enhance library management efficiency and encourage greater student interest in visiting and reading at regional libraries.
Cracking sletv mysteries: Enhancing 8th graders problem-solving abilities through polya’s approach, reviewed by initial math proficiency Maria Megawati Putri; Muhamad Toyib
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202529096

Abstract

Despite the importance of problem-solving skills in mathematics, many students struggle due to conventional teaching methods that do not consider differences in initial abilities. This study addresses this gap by examining the effectiveness of the Polya problem-solving approach on eighth-grade students’ mathematical problem-solving skills. A quasi-experimental design was conducted at MTs Negeri 1 Wonogiri in the 2024/2025 academic year, with class VIII A2 as the experimental group (Polya approach) and class VIII A1 as the control group (conventional approach). Students’ performance was assessed using a validated test on Two-Variable Linear Equation Systems. Data analysis using two-way ANOVA showed that students in the Polya group achieved an average score of 83.42, higher than the control group (71.24). Initial ability significantly influenced outcomes (high: 96.56, medium: 78.28, low: 63.63), and a significant interaction was observed between teaching method and initial ability, indicating that Polya’s approach benefits students across all ability levels. These results highlight the importance of structured problem-solving methods in improving mathematics learning outcomes.
A comparative study of poisson and negative binomial regression models on economic growth in Bali Province Safitri Pratiwi, Luh Putu; I Made Pasek Pradnyana Wijaya
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202529212

Abstract

Economic growth is the main indicator of regional development success and is measured through Gross Regional Domestic Product (GDP). This study aims to determine the best model in explaining the factors that affect economic growth in Bali Province in 2023 using Poisson regression and Negative Binomial regression. Secondary data were obtained from the Central Statistics Agency (BPS) and the Investment Coordinating Board (BKPM), with GDP response variables and predictor variables including labor force participation rate, open unemployment rate, foreign investment, population density, and literacy rate. The results of the analysis showed that the Poisson model was over dispersed, so the Negative Binomial model gave results that were more in line with the Akaike Information Criterion (AIC) value of 174.572. Economically, increasing labor force participation and foreign investment have a positive effect on GDP, while increasing unemployment and low literacy rates reduce economic growth. Thus, the Negative Binomial regression model is considered more appropriate to explain the variation in economic growth in Bali Province because it is able to handle overdispersion and provide more stable estimation results.
Forecasting passport application demand using the chen average-based FTS method at the Medan immigration office Laila Agustin Pohan; Aprilia, Rima
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202529274

Abstract

The rising demand for passport services in Medan reflects increasing public mobility and highlights the need for accurate forecasting. This study aims to predict the number of passport applications at the Class I Special Immigration Office (TPI) Medan using the Chen Average-Based Fuzzy Time Series method. The research applies a quantitative approach using secondary monthly data from January 2020 to September 2025. The forecasting procedure involves defining the universe of discourse, forming intervals, conducting fuzzification, developing fuzzy logical relationships and groups (FLR/FLRG), and performing defuzzification to produce forecast values. The results indicate that the model effectively captures fluctuations in actual data, achieving a Mean Absolute Percentage Error (MAPE) of 38.61%. These findings classify the model’s accuracy as fairly good for forecasting administrative time series data. Therefore, the Chen Average-Based Fuzzy Time Series method provides a reliable analytical tool for predicting future passport demand and supports improved planning and policy development in immigration services.
Sequence modeling of batik dyeing with RNN–LSTM: An AI approach to automated color design Muhammad Muhajir; Rahmadi Yotenka; Prihanto Edy Sanjaya; Ismail B Mustapha; Pandri Ferdias
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202529320

Abstract

Traditional Batik production relies on skilled artisans to plan multistage dyeing sequences that yield culturally meaningful and visually harmonious color combinations. This manual practice is time-consuming, difficult to document, and hard to scale to novice designers, and prior work on Batik color design has rarely treated the dyeing process explicitly as a learnable temporal sequence. This study addresses that gap by modeling Batik dyeing as a sequence learning problem and applying a Recurrent Neural Network with Long Short-Term Memory (RNN–LSTM) to support automated color design. We construct a dataset of 72 fabric samples obtained from single- and two-color dyeing procedures that follow traditional Batik wax–dye–dewax workflows. For each sample, RGB values are extracted at each dyeing stage and encoded as time-ordered inputs, while the final fabric colors are used as target outputs. The proposed RNN–LSTM learns to predict harmonious color sequences that are consistent with examples in the dataset. It achieves a prediction accuracy of 0.869 on held-out data, outperforming several feedforward and recurrent neural network baselines under the same training protocol. An interactive simulation interface then integrates the trained model, allowing users to explore and visualize predicted color outcomes step-by-step. The results show how AI-based sequence modeling can help preserve Batik color traditions while making expert color design strategies more accessible.
The influence of numeracy skills on students’ mathematics learning outcomes in the area of plane shapes material at elementary schools in labuan district Maisaroh; Mustamin Idris; Fajriani; Bakri M
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202529343

Abstract

This study investigated the effect of numeracy skills on mathematics learning outcomes, specifically in the area of 2 plane figures, among 61 fifth-grade students in Labuan Regency. Using a quantitative correlational design, descriptive results showed that students' numeracy skills were in the good category (average 75.90) and learning outcomes were in the fair category (average 70.33). The Spearman rank correlation test showed a positive and significant effect, but the relationship was weak (r = 0.292; p = 0.023 < 0.05). These findings confirm that better numeracy skills contribute to higher learning outcomes, but the weak correlation underscores the important role of other factors (e.g., teaching methods, motivation). This study implies that teachers should optimize contextual numeracy-based learning to improve achievement, especially for complex concepts such as the area of a trapezoid.

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