Article Per Year (5 Year)
p-Index From 2021 - 2026
1.745
P-Index
This Author published in this journals
All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Tensor: Pure and Applied Mathematics Journal MOVE: Journal of Community Service and Engagement Pattimura International Journal of Mathematics (PIJMath) Jurnal Matematika Integratif Indonesian Journal of Statistics and Its Applications
RUMLAWANG, FRANCIS YUNITO
MATHEMATIC DEPARTMENT FACULTY OF MATHEMATICS AND NATURAL SCIENCES UNIVERSITY OF PATTIMURA
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Mathematics Mechanical Engineering Physics Transportation Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
Application of Fuzzy Logic Mamdani Method to Determine the Amount of Ayudes Production (Case Study: CV. Abadi Tiga Mandiri Ambon) Rumalowak, Diana; Lesnussa, Yopi Andry; Rumlawang, Francis Yunito
Pattimura International Journal of Mathematics (PIJMath) Vol 2 No 1 (2023): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol2iss1pp25-32

Abstract

A company does not see a problem, namely level competition. This competition is for companies to be able to provide a marketing or productivity strategy in order to survive and even have to increase their production volume. Because the estimated number of products produced is less than the number of requests, the company will lose the opportunity to get maximum and somewhat profit. Therefore, what needs to be considered in deciding the total of production is the total of demand and supply date. Writing and discussion in this study is about the application of the Logic Fuzzy Method Mamdani (Min-Max) to determine the total of production based on the total of demand and supply where the data is taken from CV. Abadi Tiga Mandiri Ambon and by applying the fuzzy logic method mamdani and Matlab assistance obtained results with a truth level of 93,238%. So that the application of Mamdani's Fuzzy Logic Method can help companies determine the number of items that must be made.
Aplikasi Metode Adams Bashforth Moulton Dalam Memprediksi Pertumbuhan Penduduk Di Kota Ambon Radjab, Fikram; Rumlawang, Francis Yunito
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): Vol 6 No 2 (2025): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol6iss2pp121-130

Abstract

The increasing population in Ambon City can cause various problems both social and environmental problems such as lack of residential land, clean water needs, transportation problems to health. This study is to examine the increasing population of Ambon City, this study will also predict the population in Ambon City in the following year using historical data using the fourth-order Adams Bashforth Moulton method approach from Verhulst modeling. This research produces accurate forecasting with a very small relative error value, with an area of 377km2 and a predicted population of 372,725 in 2030. The Adams Bashforth Moulton method as a Verhulst model is very effective for decision making in predicting population growth in Ambon City.
PEMODELAN PENGARUH IKLIM TERHADAP ANGKA KEJADIAN DEMAM BERDARAH DI KOTA AMBON MENGGUNAKAN METODE REGRESI GENERALIZED POISSON Kondo Lembang, Ferry; Nara, Eysye Alchi; Rumlawang, Francis Yunito; Talakua, Mozart Winston
Indonesian Journal of Statistics and Applications Vol 3 No 3 (2019)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v3i3.474

Abstract

Dengue Hemorrhagic Fever (DHF) is one of the dreaded diseases of the transition season. DHF is a disease found in tropical and subtropical regions that caused by Dengue virus which is transmitted through Aedes mosquitoes. According to the World Health Organization (WHO) data, it is stated that Indonesia is the country with the highest dengue fever case in Southeast Asia. The incidence of dengue fever in Indonesia tends to increase in the middle of the rainy season, and one of the regions in Indonesia with the high level of rainfall intensity is Ambon City. DHF cases in Ambon city increase from year to year due to the last five years the intensity of rainfall is very high. Therefore, this study aims to identify climate factors that affect the incidence of DHF in Ambon City by using Generalized Poisson Regression method. Generalized Poisson Regression is appropriately considered to analyze the causing factors DHF incidence because the rating case of DHF is usually the count data that following the Poisson distribution. The results showed that the smallest AIC value for the Generalized Poisson Regression model was 75.842 with significant variables is DHF in the city of Ambon were one month earlier, air humidity, rainfall, and air humidity two months earlier.
Klasifikasi Citra Tekstur Daging Sapi, Kambing, dan Babi Menggunakan Ekstraksi Fitur Wavelet Haar dan Symlet Berbasis Support Vector Machine Green Kenny Sarimanella; Francis Yunito Rumlawang; Harmanus Batkunde; Meilin Imelda Tilukay; A. Z. Wattimena
Tensor: Pure and Applied Mathematics Journal Vol 7 No 1 (2026): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol7iss1pp59-66

Abstract

Meat is one of the animal protein sources widely consumed by the public; however, distinguishing different types of meat visually is often difficult because they have very similar textures. This study applies the Support Vector Machine (SVM) method with feature extraction based on Haar Wavelet and Symlet Wavelet (Sym4) to classify texture images of beef, goat meat, and pork. The dataset consisted of 1200 digital images processed through resizing, grayscale conversion, and normalization stages. Feature extraction was performed using the Discrete Wavelet Transform (DWT) to obtain statistical texture features. The classification process employed the Radial Basis Function (RBF) kernel with a multiclass classification approach. The results showed that the Haar Wavelet achieved an accuracy of 96.67%, while the Symlet Wavelet (Sym4) achieved 94.17%. These findings indicate that the combination of wavelet methods and SVM is effective for automatic and objective meat type identification
Co-Authors A. Z. Wattimena Abraham Zakharia Wattimena Alva Grace Naraha Batkunde, Harmanus Charlita Fhilya Citra Fathia Palembang Endro Risamasu Eysye Alchi Nara Fandy Sanudin Ferry Kondo Lembang Green Kenny Sarimanella H. W. M. Patty Hernita, Hernita Jefri Esna Thomas Radjabaycolle Meilin Imelda Tilukay Nanang Ondi Nara, Eysye Alchi Ondi, Nanang Patty, Dyana Patty, Henry Willyam Michel Radjab, Fikram Rijoly, Monalisa E. Rumalowak, Diana SAMPELILING, TRIFENA Talakua, Mozart Winston Tomasouw, Berny Pebo Yopi Andry Lesnussa Zeth Arthur Leleury, Zeth Arthur