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Journal of Mathematics, Computation and Statistics (JMATHCOS)
Published by Universitas Negeri Makassar
ISSN : 24769487     EISSN : 27210863     DOI : https://doi.org/10.35580/jmathcos
Core Subject : Education,
Mathematics
Fokus yang didasarkan tidak hanya untuk penelitian dan juga teori-teori pengetahuan yang tidak menerbitkan plagiarism. Ruang lingkup jurnal ini adalah teori matematika, matematika terapan, program perhitungan, perhitungan matematika, statistik, dan statistik matematika.
Arjuna Subject : Matematika - Matematika Terapan
Articles 210 Documents
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The Comparative Analysis of Integrated Moving Average and Autoregressive Integrated Moving Average Methods for Predicting Bitcoin Returns Brigita Tiara Elgityana Melantika; Kalfin; Siregar, Bakti; Wiwik Wiyanti
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.3788

Abstract

The rise in popularity of cryptocurrencies such as Bitcoin across various platforms has attracted the attention of young investors, making it easier for them to invest. However, due to the volatile nature of Bitcoin, this type of investment carries a high risk. Therefore, this research conducts an analysis of stock return prices to minimize losses and help investors make effective investment decisions through stock price prediction. The focus of this study is on predicting Bitcoin stock returns by analyzing closing price data over the past five years (2019-2024).  The methods used are a comparison between Integrated Moving Average (IMA) and Autoregressive Integrated Moving Average (ARIMA) with a quantitative approach using R Studio software. One of the main focuses of this research is the comparison of error estimation values between the two methods, namely Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The data analyzed comprises the daily closing prices of Bitcoin over the last five years, which is publicly accessible data. The best model for predicting the daily return of Bitcoin stock is the ARIMA (1,0,1) model. The predicted values for the next five days, from May 27, 2024, to May 31, 2024, are 0.0016632438, 0.0007991618, 0.0013415932, 0.0010010794, and 0.0012148386. The ARIMA (1,0,1) model has error measurement values with an MAE of 2.3% and an RMSE of 3.5%. It is hoped that this research will provide a better understanding of the effectiveness and relative advantages of the IMA and ARIMA methods in forecasting cryptocurrency returns, thereby offering more accurate guidance for investors in making investment decisions.
Comparative Analysis of K-Means and K-Medoids Algorithms for Product Sales Clustering and Customer Yosia; Siregar, Bakti
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4053

Abstract

In today's rapidly evolving business landscape, effective product management is crucial for maintaining a company's competitive advantage. Comprehensive analysis is essential for providing insights that inform strategic business development decisions. This study examines the sales data of PT XYZ from July 2020 to May 2024 using the K-Medoids algorithm, with dimensionality reduction applied through Principal Component Analysis (PCA). The clustering results identified three customer segments: Cluster 1 with 46 customers, Cluster 2 with 76 customers, and Cluster 3 with 62 customers. For product segmentation, four clusters were identified: Cluster 1 with 52 products, Cluster 2 with 12 products, Cluster 3 with 20 products, and Cluster 4 with 53 products. The K-Medoids algorithm demonstrated superior performance compared to K-Means in terms of cluster separation and interpretability, with visualizations that enhance the understanding of customer and product distributions. This research aids the company in enhancing customer satisfaction, optimizing inventory, and increasing profitability.
Penerapan Algoritma K-Means Clustering dalam Memetakan Produktivitas Lokasi Perkebunan Nanas PT Great Giant Pineapple Fitriani, Anisa; Arfi, Eristia; Huda, Anwar
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4200

Abstract

Abstrak. PT Great Giant Pineapple (GGP) ialah perusahaan nanas terbesar di Indonesia. PT GGP memiliki tiga Plantation Group (PG) yang berfokus pada nanas proses. Pada PG terdapat lokasi-lokasi yang memiliki luas serta produktivitas yang berbeda-beda. Tujuan penelitian ini adalah untuk mengklaster lokasi pada PG dengan menggunakan algoritma k-means clustering kemudian menganalisis strategi untuk setiap klaster. Dalam menentukan jumlah klaster optimal penulis menerapkan metode elbow dan metode silhouette coefficient. Dari penerapan kedua metode diperoleh jumlah klaster yang optimal ketika . Dengan menggunakan diperoleh anggota untuk masing-masing PG secara berturut-turut, anggota klaster 1 sebanyak 134 lokasi, 166 lokasi, dan 115 lokasi kemudian anggota klaster 2 sebanyak 41 lokasi, 49 lokasi, dan 79 lokasi. Klaster lokasi yang memiliki produktivitas tinggi terdapat di klaster 1 pada PG 1 dan PG 2 kemudian klaster 2 pada PG 3. Kelompok lokasi yang memiliki produktivitas rendah terdapat di klaster 2 pada PG 1 dan PG 2 kemudian klaster 1 pada PG 3. Analisis strategi untuk klaster rendah yakni dengan melakukan manajemen air, pengendalian hama, pemupukan yang lebih efektif serta pengontrolan waktu forcing secara berkala serta pengawasan supaya tidak terjadi pencurian pada klaster yang memiliki produktivitas tinggi. Kata Kunci: Algoritma K-Means, Metode Elbow, Metode Silhouette Coefficient, PT GGP
the Approach Solution Numeric for Mathematical Models Celebrity Worship Behavior Among K-Pop Fans Based Wisdom Local in South Sulawesi Using Runge- Kutta method Order 6: bahasi Inggris Mulyaningrum, Dwidary; minggi, ilham; Side, syafruddin; Yusuf Sainon Andi Pandjajangi, Andi Muhammad Ridho
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4201

Abstract

Studies This explore the mathematical model of SFR with use run kutta order 6 that catches rate Behavior Worship Celebrities among​ fan loyal K-Pop. Main data obtained through direct questionnaire​ taken from communities in South Sulawesi Province , provide outlook about rhythm Behavior Worship Celebrities among​ K-Pop lovers . Research This aiming For to study phenomenon idolization K-Pop celebrities among fans in South Sulawesi through approach solution numerical . Using the SFR mathematical model and the Runge- Kutta method Order 6, results simulation show that K-Pop idolization in the region This Enough significant , influenced by social media as well as factor culture and social local . Data shows existence decline amount vulnerable fans​ to addicted to K-Pop, but fluctuation behavior addiction and decline number recovery still become attention . Research This highlight importance more intervention​ effective , such as therapy and support social , for overcome impact negative from idolization celebrity . Findings This also provides outlook valuable for development strategy in handle phenomenon idolization celebrities who continue develop in the future.
Analisis Spasial Bayesian dengan Metode CAR Leroux (Studi Kasus: Stunting di Indonesia) Muthahharah, Isma; Mar’ah, Zakiyah
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4203

Abstract

Stunting has become a problem that has received special attention and is an urgent priority for the international community. Stunting or chronic malnutrition is a nutritional problem caused by malnutrition from food that lasts for a long time. The purpose of this study is to map the relative risk (RR) of stunting cases in Indonesia. This type of research is quantitative research. The data used are stunting cases that occurred in 2023 in Indonesia. The method used is Spatial Bayesian with the CAR Leroux Method. The selection of the best model is based on model suitability criteria, such as Watanabe Akaike Information Criterion (WAIC) and Deviance Information Criterion (DIC). The results of the analysis show that the best model obtained in the RR model of stunting cases in Indonesia shows that the CAR Leroux model with a higher GI (0.1; 0.1) is suitable for modeling the growth rate pattern of confirmed stunting cases in Indonesia. The three provinces with the highest RR values ​​are West Sulawesi Province, West Kalimantan Province, and East Nusa Tenggara Province. While the three provinces with the lowest RR values ​​are DKI Jakarta Province, South Sumatra Province, and North Sulawesi Province.
Comparison of Holt Winter's and SARIMA Methods on the data of the Number of Foreign Tourist Visits in Bali Province Evania, Clara Della; Siregar, Bakti
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4211

Abstract

The tourism sector is a critical component of a country’s economy, including in Indonesia, where its impact is felt both nationally and regionally, such as in provinces and cities. This research focuses on Bali Province and aims to conduct a comparative analysis of the Holt-Winter’s and Seasonal Auto-regressive Integrated Moving Average (SARIMA) methods for forecasting foreign tourist arrivals. The analysis centers on two primary entry points: Ngurah-Rai Airport and the seaport. The primary objective is to forecast the number of foreign tourist arrivals from February 2024 to January 2025. The results indicate that the Holt-Winter’s model has a Mean Absolute Percentage Error (MAPE) of 5.2631%, which is lower than the MAPE of 5.8920% for the SARIMA model. Additionally, the Mean Absolute Error (MAE) for the Holt-Winter’s model is 19,149.18, compared to 20,883.20 for the SARIMA model. Consequently, this study concludes that the Holt-Winter’s model provides more accurate predictions and is closer to the actual values than the SARIMA model. Bali, Holt-Winter’s, forecasting, SARIMA, tourism.
Determining Tourist Destination Priorities Using Website-Based Particle Swarm Optimization Methods (Case Study : North Padang Lawas Regency) Salsabila, Aqila; Molliq Rangkuti, Yulita; Muslim Karo Karo, Ichwanul; Iskandar Al-Idrus , Said
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4233

Abstract

. Optimization of tourist routes is very important to minimize travel time and reduce travel costs. This study focuses on optimizing tourist routes in North Padang Lawas Regency using Multi Attribute Utility Theory (MAUT), and Particle Swarm Optimization (PSO) in the context of the Traveling Salesman Problem (TSP). This study discusses problems such as the lack of priority of tourist destinations and the need for shorter travel times. The research process includes problem identification, literature review, data collection through field observations and interviews, and data processing with MAUT to prioritize destinations. The identified priority destinations are Hotel Sapadia Gunung Tua, Barumun Nagari, Batik Sekar Najogi, Durian and Manggis Agrotourism, Rumah Makan Holat Alhamdulillah, Waterboom Gunung Tua, and Candi Bahal I, II, III. Furthermore, PSO is applied to determine the optimal travel route. PSO finds a route with a total travel time of 351 minutes, although the three-day travel time is extended to 375 minutes.
Analisis Regresi Logistik Ordinal pada Pengaruh Pelayanan Terhadap Kepuasan Pasien Rawat Inap di Rumah Sakit Murni Teguh Medan Simangungsong, Monalisa; Pane, Rahmawati; Manurung, Asima; Tarigan, Enita Dewi br.
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4240

Abstract

Abstract. Hospitals play an important role in supporting public healt by providing high quality services, especially in providing optimal services for inpatients. Patient satisfaction is the main indicators to assess the quality of services in the hospital. This research aims to determine the effect of services on the level of satisfaction of inpatients at Murni Teguh Hospital using the ordinal logistic regression method. The results showed 44% of respondents were satisfied and 29% of respondents were very satisfied. Variables that have a significant effect on patient satisfaction are food service, medical facilities and medicines, and administrative services. The Negelkerke’s coefficient of determination of 0.825 indicates that 82.5% of the predictor variables affect the overall assessment of impatient satisfaction. The results of the model interpretation show that the highest chance of patients to feel very satisfied is in the medical facilities and medicines variable with an odds ratio of 2.959.
Deciphering Celebrity Worship Phenomenon: Simulation and Analysis using SFR Mathematical Model with Time Delay among Fans in South Sulawesi Arsita, Asriani; Minggi, Ilham; Pandjajangi, Andi Muhammad Ridho Yusuf Sainon Andi; Side, Syafruddin; Arwadi, Fajar
Journal of Mathematics, Computations and Statistics Vol. 7 No. 1 (2024): Volume 07 Nomor 01 (April 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i1.4251

Abstract

This study explores the mathematical SFR model to analyze Celebrity Worship Behavior among devoted K-Pop fans. Primary data were collected through questionnaires distributed within the South Sulawesi Province, providing insights into the dynamics of Celebrity Worship Behavior among K-Pop enthusiasts. The research involves developing an SFR model with time delays, followed by a series of analyses and simulations related to Celebrity Worship Behavior in the K-Pop community. This comprehensive approach includes identifying equilibrium points, evaluating model stability, calculating the basic reproduction number (R0), conducting simulations using Maple software, and interpreting the simulation results. The SFR mathematical model reveals two equilibrium points: one representing the baseline level of Celebrity Worship Behavior among K-Pop fans and the other specific to this behavior. The calculated R0 value of 0.425 suggests a potential decrease in the prevalence of Celebrity Worship Behavior within the K-Pop community.
UNVEILING AMMOTERE ABBAJI: EXPLORING SILARIANG PERPETRATORS WITH SER MATHEMATICAL MODELING AMONG THE BUGIS COMMUNITY IN SOUTH SULAWESI Rudi; Annas, Suwardi; Side, Syafruddin; Pandjajangi, Andi Muhammad Ridho Yusuf Sainon Andi; Irwan
Journal of Mathematics, Computations and Statistics Vol. 7 No. 1 (2024): Volume 07 Nomor 01 (April 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i1.4252

Abstract

This study focuses on the mathematical SER model capturing the rate of Ammotere Abbaji Case Behavior among individuals associated with Silariang. Primary data is gathered through questionnaires administered directly to the community in South Sulawesi Province, shedding light on the pace of Ammotere Abbaji Case Behavior among those involved with Silariang. The research journey starts with the construction of the SER model, followed by an analysis and simulation of the Ammotere Abbaji Case Behavior among Silariang participants. This encompasses identifying equilibrium points, evaluating model stability, computing the basic reproduction number (R0), conducting model simulations using Maple software, and interpreting the simulation results. Within this article, the mathematical SER model emerges through the analytical lens and simulation of Ammotere Abbaji Case Behavior among Silariang participants. Two equilibrium points are discovered: the free equilibrium point of Ammotere Abbaji Case Behavior among Silariang participants, and the equilibrium point specific to this behavior. The calculated basic reproduction number R0=0.045 indicates a decrease in the population engaged in Ammotere Abbaji Case Behavior among Silariang participants.

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