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All Journal Jurnal Matematika Sains dan Teknologi JURNAL ILMIAH MATEMATIKA DAN TERAPAN BAREKENG: Jurnal Ilmu Matematika dan Terapan Dinamisia: Jurnal Pengabdian Kepada Masyarakat JTAM (Jurnal Teori dan Aplikasi Matematika) Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jambura Journal of Mathematics Jurnal Matematika UNAND Variance : Journal of Statistics and Its Applications Mandalika Mathematics and Educations Journal Jurnal Statistika dan Aplikasinya Indonesian Journal of Applied Research (IJAR) JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Jurnal Diferensial Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Griya Journal of Mathematics Education and Application FARABI: Jurnal Matematika dan Pendidikan Matematika Journal of Science and Technology Journal of Mathematics: Theory and Applications Research Review: Jurnal Ilmiah Multidisiplin Pattimura International Journal of Mathematics (PIJMath) Jurnal Riset Mahasiswa Matematika Indonesian Journal of Computational and Applied Mathematics
La Ode Nashar
Prodi Statistika, Fakultas Matematika Dan IPA, Universitas Negeri Gorontalo
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Perbandingan Jackknife Ridge Regression dan Principal Component Regression dalam Penanganan Kasus Multikolinearitas (Studi Kasus: Indeks Pembangunan Manusia di Indonesia) Nur’ain Manoppo; La Ode Nashar; Djihad Wungguli; Muhammad Rezky F. Payu; Siti Nurmardia Abdussamad; Salmun K. Nasib
Research Review: Jurnal Ilmiah Multidisiplin Vol. 4 No. 1 (2025): Research Review: Jurnal Ilmiah Multidisiplin (Februari 2025 - Juli 2025)
Publisher : Transbahasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54923/researchreview.v4i1.181

Abstract

According to data from Statistics Indonesia, the Human Development Index (HDI) in 2022 reached 72.91, increasing from 72.29 in the previous year. Although Indonesia’s HDI continues to improve, disparities remain among provinces, indicating that HDI distribution is still uneven. Given the importance of HDI in aregion, it is necessary to conduct statistical analysis to identify the factors that significantly influence HDI using regression analysis. In applying multiple linear regression, several classical statistical assumptions must be met, one of which is the central focus of this analysis-addressing the issue of multicollinearity. Several methods have been identified to address multicollinearity, including Jackknife Ridge Regreesion (JRR) and Principal Component Regression (PCR). This study aims to compare the effectiveness of both methods in handling multicollinearity based on Adjusted R2 and Mean Square Error (MSE) and to analyze the factors that significantly influence the HDI level in Indonesia. The data used in this study are secondary data comprising HDI and its related factors for each province in Indonesia in 2022, obtained from bps.go.id. Based on the analysis, the best model uses the JRR method, with an Adjusted R2 value of 96.7% and MSE of 0.033.
Analisis Regresi Ordinal untuk Mengetahui Faktor-Faktor yang Mempengaruhi Kepuasan Nasabah Bank BRI Pogogul Buol terhadap Kualitas Pelayanan Teller Yulianti Arbie; Djihad Wungguli; La Ode Nashar
Research Review: Jurnal Ilmiah Multidisiplin Vol. 4 No. 2 (2025): Research Review: Jurnal Ilmiah Multidisiplin (Agustus 2025 - Januari 2026)
Publisher : Transbahasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54923/researchreview.v4i2.274

Abstract

Banking is a service industry that depends heavily on customers’ trust in the services provided. Service quality is a key factor in business success, especially as technological advances continue to drive rapid innovation in banking products and services. Therefore, banks must consistently pay attention to customers’ needs and expectations and strive to fulfill them more effectively and satisfactorily than their competitors. Customer satisfaction represents an individual’s feelings after comparing the perceived performance of a service with their expectations. High levels of satisfaction are essential for maintaining a company’s market position, improving service effectiveness, and strengthening customer loyalty. This study aims (1) to determine the level of customer satisfaction with teller service quality at BRI Pogogul Buol Branch, and (2) to identify the factors that significantly influence satisfaction with teller services. A quantitative research method was applied using a questionnaire as the primary instrument. Data were collected through a Likert scale questionnaire consisting of four response options scored from 1 to 4. The instrument consisted of 27 validated items adapted from earlier instruments, and its reliability was assessed using Cronbach’s Alpha, with values above 0.70 indicating acceptable reliability. The results show that overall customer satisfaction with teller service quality at BRI Pogogul Buol is at a low or dissatisfied level. Furthermore, the analysis identifies empathy as the factor that significantly influences customers’ satisfaction with teller services. The findings highlight the importance of improving interpersonal and empathetic interactions to enhance service quality and strengthen customer trust.
Analisis Dinamik Model Penularan Kolera dengan Mempertimbangkan Risiko Individu dan Intervensi Karantina Feni Elliyin; Agusyarif Rezka Nuha; La Ode Nashar
Research Review: Jurnal Ilmiah Multidisiplin Vol. 5 No. 1 (2026): Research Review: Jurnal Ilmiah Multidisiplin (Februari 2026 - Juli 2026)
Publisher : Transbahasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54923/researchreview.v5i1.325

Abstract

This study develops an SIQRB mathematical model to analyze the transmission dynamics of cholera by incorporating individual risk stratification and quarantine interventions. The model consists of six human compartments, including high- and low-risk susceptible individuals, infected individuals from each risk group, quarantined individuals, and recovered individuals, along with one environmental compartment representing the concentration of Vibrio cholerae. This framework allows a comprehensive analysis of the interaction between human populations and environmental factors in disease transmission. The stability analysis shows that the disease-free equilibrium is locally asymptotically stable when the basic reproduction number (R₀) is less than one (R₀ < 1), and becomes unstable when R₀ exceeds one (R₀ > 1), indicating the potential for endemic conditions. Sensitivity analysis identifies the most influential parameters affecting R₀, namely the immigration rate (Λ), the environmental transmission rate (βb), and the bacterial shedding rate (ξ). These parameters significantly contribute to the increase in disease transmission. Numerical simulations confirm the analytical findings, showing that higher values of these parameters lead to increased numbers of infected individuals and higher environmental bacterial concentrations. Conversely, environmental-based control strategies—such as mobility restrictions, improved sanitation, and water disinfection—are effective in reducing R₀ below one. Therefore, this study highlights the critical importance of environmental interventions in controlling cholera transmission and preventing long-term endemicity.
Model Aljabar Max-Plus pada Sistem Distribusi Produk Bakery dengan Representasi Petri Net Siti Nurlaila Mustapa; Nurwan Nurwan; La Ode Nashar
FARABI: Jurnal Matematika dan Pendidikan Matematika Vol 9 No 1 (2026): FARABI: Jurnal Matematika dan Pendidikan Matematika
Publisher : Program Studi Pendidikan Matematika FKIP UNIVA Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47662/farabi.v9i1.1397

Abstract

Distribution efficiency is a critical aspect of bakery product distribution systems, as delivery delays affect product freshness, operational costs, and service reliability to customers. This study aims to develop a mathematical model to analyze product distribution time at UD. Win Win Bakery by integrating Petri Nets and Max-Plus Algebra. Petri Nets are used to represent the sequential, event-based distribution process, including vehicle preparation, goods loading, distribution travel, goods unloading, and the return trip to the factory. The Petri Net structure is then transformed into a Max-Plus Algebra model and matrix to calculate the total distribution time for each team. Data were collected through observations and interviews regarding distribution schedules, routes, number of vehicles, loading time, unloading time, and travel duration. The results show significant variations in distribution times among the nine delivery teams. The longest durations were found on the Toboli–Parigi, Ampibabo, and Kotamobagu routes, indicating workload imbalance and potential bottlenecks in the distribution system. The main contribution of this study lies in the application of Max-Plus Algebra supported by Petri Nets as a structured framework to identify time inefficiencies in regional-scale distribution. The implications of this study suggest that Max-Plus Algebra can be effectively used in discrete event-based distribution systems and supports route evaluation, workload balancing, and operational decision-making in perishable product logistics.
Determination of Premium Price for Rice Crop Insurance in Gorontalo Province Based on Rainfall Index with Black Scholes Method Ana Nadiyyah; Emli Rahmi; Salmun K. Nasib; Agusyarif Rezka Nuha; Nisky Imansyah Yahya; La Ode Nashar
Pattimura International Journal of Mathematics (PIJMath) Vol 3 No 2 (2024): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol3iss2pp51-62

Abstract

With its complex topography, Gorontalo Province experiences significant rainfall variations that impact the agricultural sector, particularly rice crops. These variations can cause substantial losses for farmers. One way to address uncertain probabilities caused by rainfall is through agricultural insurance. This research aims to calculate the value of agricultural insurance premiums based on the rainfall index. The Black- Scholes method is used to calculate the premiums, while the Burn Analysis method is employed to determine the rainfall index. The research results classify the rainfall index values in Gorontalo Province into 7 (seven) percentiles. The lowest is at the 20th percentile, with 17.37 mm and a premium value of IDR 1,574,190, while the highest is at the 80th percentile, with 17.65 mm and a premium value of IDR 2,154,574. This indicates that the higher the rainfall, the greater the premium to be paid.
Analisis Peramalan Harga Saham PT Unilever Indonesia Menggunakan Pemodelan LSTM dengan Optimasi PSO Dewinto Burhan; Isran K. Hasan; La Ode Nashar
Jurnal Riset Mahasiswa Matematika Vol 5, No 3 (2026): Jurnal Riset Mahasiswa Matematika
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/jrmm.v5i3.40090

Abstract

Pergerakan harga saham cenderung tidak stabil dan sulit diprediksi karena memiliki pola yang kompleks serta berubah-ubah dari waktu ke waktu. Untuk mengatasi hal tersebut, penelitian ini menggunakan model Long Short-Term Memory (LSTM) dalam melakukan peramalan harga saham. Agar model yang dihasilkan memiliki kinerja yang optimal, dilakukan optimasi hyperparameter menggunakan metode Particle Swarm Optimization (PSO). Optimasi dilakukan pada tiga parameter utama LSTM yaitu LSTM units, dropout rate, dense units. Dari proses optimasi diperoleh enam konfigurasi model terbaik. Hasil pengujian menunjukkan model ke-5 memberikan hasil optimasi paling baik dengan nilai RMSE 120,3320 dan MAPE sebesar 3,53% dengan menggunakan kombinasi hyperparameter LSTM units = 137, dropout rate = 0,498, dan dense units = 32. Hasil ini menunjukkan bahwa optimasi hyperparameter memberikan peningkatan akurasi peramalan dibandingkan LSTM tanpa optimasi. Dengan demikian, kombinasi model LSTM dengan optimasi PSO mampu menghasilkan peramalan harga saham yang lebih akurat dan stabil. Pendekatan ini dapat digunakan sebagai alternatif dalam analisis pergerakan harga saham dan mendukung pengambilan keputusan investasi.
The Implementation of Random Under-Sampling and Synthetic Minority Oevrsampling Techniques to Evaluate the Performance of the Classification and Regression Tree Method Rifandi Pratama Putra Kasadi; Nurwan Nurwan; La Ode Nashar; Djihad Wungguli; Siti Nurmardia Abdussamad
Jurnal Matematika Sains dan Teknologi Vol. 26 No. 1 (2025)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v26i1.11381.2025

Abstract

Class imbalance in datasets poses a significant challenge in the application of classification models, including the Classification and Regression Tree (CART) method. This study aims to evaluate the performance of CART combined with two data balancing techniques: Random Under Sampling (RUS) and Synthetic Minority Oversampling Technique (SMOTE). The data set used in this research is the Heart Failure Clinical Records from Kaggle.com, which exhibits an imbalance where the number of deceased patients is 1,568 records (minority class) and the number of survivors is 3,432 records (majority class), with a total of 5,000 records. The RUS technique reduced the total number of records to 2,526, with each class containing 1,263 records. Conversely, after applying SMOTE, the total number of records increased to 5,474, with each class containing 2,737 records. Model performance evaluation was conducted using precision, recall, and F1-score metrics, both before and after implementing data balancing techniques. The results of the study showed that combining CART with SMOTE produced better performance in recognizing the minority class compared to RUS, achieving accuracy and F1-score of 88.203% and 88.195%, respectively. Meanwhile, RUS achieved an accuracy of 86.345% and an F1-score of 86.332%. Therefore, the use of SMOTE improved model accuracy by approximately 1.85% and F1-score by 1.86% compared to RUS. This study makes a significant contribution to improving prediction accuracy on imbalanced datasets and enriches scientific references related to the application of the CART method and data balancing techniques.
Co-Authors Agusyarif Rezka Nuha Ahmad, Rindawati Akor, Umar D. Ana Nadiyyah Andi Agung Armayani Arsal Asriadi Asriadi Asriadi Asriadi Bertu Rianto Takaendengan Brahim, Annisa Maharani Chasanah, Sri Istiyarti Uswatun Dewi Rahmawaty Isa Dewinto Burhan Dina Fakhriyana Djihad Wungguli Fadilah Istiqomah Pammus Feni Elliyin Gani, Friansyah Hasan S. Panigoro Hasan, Riyanto Hasibuan, Lilis Harianti Herlina Jusuf Ipal Rahmat Jaya Ismail Djakaria Isran K Hasan Iyohu, Lisa Rianti K. Hasan, Isran Karina Anselia Mamonto La Ode Sabran Ladjali, Sri Indriani Lailany Yahya Latif, Sintia Abdul LIHAWA, SRIRAPI H Lindrawati Abdjul Loleh, Linda Purnama Sari Mahmud, Sri Lestari Marukai, Nur Amalia Muhammad Rezky F. Payu Muhammad Rezky F. Payu Nisky Imansyah Yahya NISKY IMANSYAH YAHYA Novianita Achmad Nur Miftah Muhammad Nurafni, Firda Nurwan Nurwan Nurwan Nurwan NURWAN NURWAN Nurwan Nurwan Nurwan, Nurwan Nur’ain Manoppo Rahman, Gusti Arviana Rahmi, Emli Rasyid, Kamelia Resmawan Resmawan Rianjaya, Ilham Dangu Rifandi Pratama Putra Kasadi Salmun K. Nasib Sartika Sari Dewi Siti Nurlaila Mustapa Siti Nurmardia Abdussamad Sugito Mahendra Imran Syarif Abdullah Tedy Machmud Ulopo, Asrul S Valentika, Nina Widyastutifajri Nuha Yulianti Arbie Zian Bula