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Jose Rizal
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diophantine@unib.ac.id
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FMIPA Universitas Bengkulu JLWR Supratman Kelurahan Kandang Limun Kecamatan Muara Bangkahulu Kota Bengkulu
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Diophantine Journal of Mathematics and Its Applications
Published by Universitas Bengkulu
ISSN : -     EISSN : 2987906X     DOI : https://doi.org/10.33369/diophantine
Core Subject : Economy, Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering
The DJMA is published twice a year in June and December. This journal is managed by the Mathematics Department of Bengkulu University. The scope of this journal includes the fields of: 1. Mathematics 2. Applied Mathematics 3. Statistics 4. Applied Statistics 5. Computer Science.
Arjuna Subject : Matematika - Matematika Terapan
Articles 8 Documents
 1 
Search results for , issue "Vol. 3 No. 1 (2024)" : 8 Documents clear
Implementasi Data Mining dengan Algoritma Naïve Bayes untuk Klasifikasi Kelayakan Penerima Bantuan Zakat Fitrah Salsabila, Nanda; Ramury, Feli
Diophantine Journal of Mathematics and Its Applications Vol. 3 No. 1 (2024)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v3i1.28374

Abstract

In life there are many commands of Allah SWT. that must be carried out, one of which is the order to pay zakat. The purpose of this study was to classify the feasibility of receiving zakat fitrah at the mosque. The type of research used is quantitative research with quantitative descriptive research types. The classification that has been carried out assists the aid manager in making decisions regarding the classification of determining the recipients of zakat fitrah assistance. In this study, the Naive Bayes algorithm was implemented and analyzed using a web-based developed application. The results of the research show that the classification of zakat fitrah recipients is correct or valid.
Perbandingan Penerapan Metode VBEOQ dan Metode Persediaan Multi Item Periode Pemesanan Tunggal untuk Meningkatkan Economic Value Added (EVA) Pada Usaha Mikro Hadi, Muthia Nurul; Triska, Anita
Diophantine Journal of Mathematics and Its Applications Vol. 3 No. 1 (2024)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v3i1.31120

Abstract

Every company requires minimum costs in controlling inventory and maximizing the company value. The company value is an investor's perception of the company success level. Therefore, the inventory management system have to contribute to realize these goals. Besides influencing the company value, inventory control is also useful to expedite the company activities. An alternative solution to maximize the company value is by increasing the economic value added (EVA). The change of EVA ΔEVA) can be analyzed using the Value Based Economic Order Quantity (VBEOQ) method which each item is ordered separately. However, in a company may manage many items. In order to overcome this problem, ΔEVA can be analyzed using the multi-item inventory method of a single order period. These two methods are used to analyze EVA in the micro enterprise Depot Tutup Galon X. Based on the analysis, it is found that by using the VBEOQ method and multi item inventory for a single order period increase the ΔEVA as Rp12,629,947,00 and Rp14,355,057,00, respectively. These results indicate that applying the multi-item inventory method for a single order period at Depot Tutup Galon X is better since it increases the ΔEVA larger.
Perbandingan Metode Arima (Box Jenkins), Multiscale Autoregressive (MAR), dan Singular Spectrum Analysis (SSA) untuk Data Non-Stationer dalam Peramalan Data Nilai Ekspor Provinsi Bengkulu FOB (Free On Board) Pelabuhan Baai Januari 2019 - September 2023 Shidigie, A A; Yurike, L; Puspita, D; Julieta, A; Hidayati, N; Putri, M H C
Diophantine Journal of Mathematics and Its Applications Vol. 3 No. 1 (2024)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v3i1.32051

Abstract

This research presents a comparison of the performance of three forecasting methods, namely ARIMA (Box Jenkins), Multiscale Autoregressive (MAR), and Singular Spectrum Analysis (SSA), in dealing with non-stationary export data challenges. The focus of the study is on forecasting the export value of Bengkulu Province FOB (Free on Board) Pelabuhan Baai from January 2019 to September 2023. By using ARIMA as a classical approach, MAR and SSA as representations of multiscale and signal decomposition approaches, this study aims to provide a comprehensive understanding of the effectiveness of each method in dealing with dynamic export data characteristics. Performance evaluation is carried out using criteria such as Mean Absolute Percentage Error (MAPE), with the hope of providing valuable insights for selecting the optimal forecasting method in the context of Bengkulu Province's exports.
Analisis Algoritma Greedy untuk Mewarnai Graf Pernanda Putra, Hazel; Sylviani, Sisilia; Candra Permana, Fahmi
Diophantine Journal of Mathematics and Its Applications Vol. 3 No. 1 (2024)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v3i1.32261

Abstract

Graph coloring is one of the problems in graph theory. In graph theory, a greedy algorithm is a common algorithms in solving a problem. Greedy algorithms can be used for graph coloring; however, not all of the graph coloring problems that this algorithm uses can optimum outcomes globally. The selection of node sequencing used during the search also affects the success of the greedy algorithm in dealing with graph coloring cases. However, the use of greedy algorithms still helps reduce the number of colors used in non-directed graph coloring.
Implementasi Model Goal Programming untuk Menganalisis Kinerja Keuangan Perusahaan Marsyanda, Meifa Putri; Novianingsih, Khusnul; Kustiawan, Cece
Diophantine Journal of Mathematics and Its Applications Vol. 3 No. 1 (2024)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v3i1.33146

Abstract

Company financial reports can be used to analyze a company's financial performance. This research discusses financial performance analysis to determine the company's financial weaknesses and strengths. Using the analysis results, the company can be determined financial policies for the next period, so the company can achieve the optimal financial performance. The financial performing model can be modelled as a multi-objective problem. The model is solved by converting the multi-objective model into a goal programming model. Then, it is solved using the Modified Simplex Method. We implemented the model to analyze the financial report of a big company. The results show that the company has a good financial performance.
Analisa Kestabilan Bebas Penyakit Model SITRS pada Penyebaran Diare Widayati, Ratna; Hamim Muntoha, Renal; Ma'rifah, Umi; Yulianti, Nita
Diophantine Journal of Mathematics and Its Applications Vol. 3 No. 1 (2024)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v3i1.33908

Abstract

This study discusses the spread of diarrhea accompanied by complications resulting in death among sufferers. It is assumed that people with diarrhea can transmit the disease to susceptible individuals. Additionally, deaths occurred due to diarrhea when treatment was not administered. Individuals who have contracted diarrhea may acquire temporary immunity and then become susceptible again. The model used is SITRS. Based on the model, disease-free equilibrium points and endemic equilibrium points are obtained. The analysis was conducted around the disease-free equilibrium point, and it was concluded that the disease-free equilibrium point is locally asymptotically stable if R0<1. Furthermore, based on the simulation results, it is shown that the model's solution tends towards a disease-free equilibrium point if R0<1. . This implies that diarrhea will disappear from the population at some point if the infection level R0<1. is met.
Klasifikasi Produktivitas Buah Nanas Menggunakan Algoritma Classification and Regression Tree (CART) Aprihartha, Moch. Anjas; Putrawan, Zulhandi; Zulhan , Dicky; Ahardika Nurfaizal, Fatma
Diophantine Journal of Mathematics and Its Applications Vol. 3 No. 1 (2024)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v3i1.34193

Abstract

Indonesia is one of the countries that has a variety of fruits cultivated. One of them is the pineapple fruit. Various pineapple-based products such as pineapple juice, canned foods, pineapple jam, etc. The high demand for pineapples presents an opportunity for companies to increase pineapple product processing. The increase in pineapple productivity is influenced by several factors, one of which is the extent of land and the type of pineapple produced. To improve pineapple productivity, it can be done by classifying the types of pineapples based on productive and non-productive categories. The purpose of this classification is to enable farmers or plantation managers to allocate resources more efficiently by providing more intensive care for productive category pineapples. The classification method that can be used to classify productive and non-productive pineapples is the Classification and Regression Tree (CART) algorithm. The CART method is a method that produces decision tree models that are used to solve classification and regression problems. This research uses the CART method to classify pineapple productivity. The research results obtained accuracies, sensitivities, specificities, and precisions of 97.06%; 92.31%; 100%; 100% respectively. Meanwhile, the AUC obtained is 0.962 which indicates that the model is very good at predicting pineapple productivity correctly.
Pemodelan Berat Badan Lahir Rendah (BBLR) di Kabupaten Buton Tengah Menggunakan Regresi Logistik Makkulau; Baharuddin; Ampa, A T; Ihwal, M; Ningtyas, R A; Salam, A; Afiani, N
Diophantine Journal of Mathematics and Its Applications Vol. 3 No. 1 (2024)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v3i1.35873

Abstract

Low Birth Weight (LBW) is a baby's weight at birth less than 2,500 grams. The birth of LBW babies is a major contributor to both short and long term neonatal morbidity and death. The number of LBW in Central Buton Regency reported in 2021 is getting worse than in 2020. Therefore, Logistic Regression Analysis in needed to identify and model the factors that influence LBW cases in Central Buton district. The data used in this study is secondary data on the population of birth weight in infants during the period January – June 2022. Data was obtained from the Medical Record of Puskesmas in Central Buton district, Mawasangka district area and Gu district area. The number of samples in the study was 327 infants. The model produced in this study is ĝ(x) = -37535 + 2,3562X1 + 1,2097X2 + 1,4590X4. From this model, it is known that the factors that significantly affect LBW in Buton Tengah Regency are gestational age (X1), Hb levels (X2) and pregnancy complications (X4) with an accuracy value of 90,51%.

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