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All Journal Jurnal Matematika Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi Gamatika JAIS (Journal of Applied Intelligent System) International Journal of Artificial Intelligence Research APOTEMA : Jurnal Program Studi Pendidikan Matematika Jurnal Matematika: MANTIK Indonesian Journal of Applied Statistics BAREKENG: Jurnal Ilmu Matematika dan Terapan Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Variance : Journal of Statistics and Its Applications Jurnal Statistika dan Aplikasinya MOVE: Journal of Community Service and Engagement Jurnal Eurekamatika Pattimura International Journal of Mathematics (PIJMath) JUSTE (Journal of Science and Technology) Jurnal Matematika Integratif
Yopi Andry Lesnussa
Jurusan Matematika Universitas Pattimura
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Application Of Backpropagation Neural Networks In Predicting Rainfall Data In Ambon City Yopi Andry Lesnussa; C. G. Mustamu; F. Kondo Lembang; M. W. Talakua
International Journal of Artificial Intelligence Research Vol 2, No 2 (2018): December 2018
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (612.013 KB) | DOI: 10.29099/ijair.v2i2.59

Abstract

The Artificial Neural Networks is a process of information system on certain traits which as representatives of the human neural networks. The Artificial Neural Networks can be applied in every area of human life, one of them is environment especially about prediction of climate or weather. In this research, the artificial neural network is used to predict the rainfall with Backpropagation method and using MATLAB software. The other meteorology parameters used to predict the rainfall are air temperature, air velocity and air pressure. The result showed less accuracy level is 80% by using alpha 0,7, iteration number (epoch) 10000 and MSE value = 0,0218. Therefore, the result of rainfall prediction system is accurate.
Analysis of Support Vector Machine (SVM) Method and Simple Additive Weighting (SAW) Method in Making Decisions to Choose Specialization Stevanny Tamaela; Yopi Andry Lesnussa; Venn Y.I. Ilwaru; Abdul Malik Balami
Jurnal Matematika MANTIK Vol. 6 No. 2 (2020): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15642/mantik.2020.6.2.104-113

Abstract

The Specialization of students is a learning based on the interests of students according to learning opportunities that exist in educational units. Providing education in high school education units based on the 2013 curriculum there is a program for determining specialization for high school students held in class X. Specialization in the 2013 curriculum in high schools is the specialization group for Natural Sciences and Social Sciences. This study uses the Support Vector Machine (SVM) method and the Simple Additive Weighting (SAW) method which aims to compare the accuracy of each method in Decision Making (SPK) specialization program in the Natural Science and Social Sciences at SMA Negeri 1 Ambon. From the research results, the results of the specialization selection from the SAW method differ from the real data, while the results of the SVM method show the same results as the selection of real specialization in SMA Negeri 1 Ambon
Analisis Stabilitas Model SIR (Susceptibles, Infected, Recovered) Pada Penyebaran Penyakit Demam Berdarah Dengue di Provinsi Maluku Zeth Arthur Leleury; Yopi Andry Lesnussa; Johan Bruiyf Bension; Yulia S. Kakisina
Jurnal Matematika Vol 7 No 2 (2017)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2017.v07.i02.p91

Abstract

Health is an investment to support economic development and has an important role in efforts to reduce poverty and improve the quality of human resources. One of the diseases that often become serious problem in health sector that is Dengue Hemorrhagic Fever (DHF). In Indonesia, many mosquitoes cause dangerous DHF such as Aedes aegypti, Aedes albopictus, Aedes africanus, anopheles and others. In this study, we analyzed and applied SIR (Susceptible, Infection, Recovered) mathematical models and their interpolation to determine whether a contagious disease (DHF) can become endemic or not. Therefore, in this study aimed to determine the a special form of model of SIR to analyze the spread of DHF in Maluku Province and the stability analysis of this model and also interpolating the data of DHF transmission in Maluku Province. Furthermore, it can be obtained the characteristics of equilibrium point of each sub population. Based on the research conducted it can be concluded that from the entire population of Maluku Province is 1.686.469 vulnerable people infected with DHF and endemic disease with the basic reproduction value is 3,44.
Peramalan Cuaca Menggunakan Metode Rantai Markov (Studi Kasus : Cuaca Harian Di Kota Ambon) Set Sasake; Yopi Andry Lesnussa; Abraham Zakaria Wattimena
Jurnal Matematika Vol 11 No 1 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2021.v11.i01.p131

Abstract

Weather is a state of the air at certain times in certain areas that are relatively narrow and in a short period of time. Weather forecasting is an activity carried out to produce a collection of information about upcoming weather conditions. One method used to predict these conditions is by using the Markov chain method. The Markov chain is a random process in which all information about the future is contained in the present state. The purpose of this study is to model and predict daily weather that will occur over the next week with the Markov Chain model. The data used in this study are Ambon City daily weather data from December 1, 2019, to January 31, 2020, by the Meteorology, Climatology, and Geophysics Agency (BMKG), Ambon City Meteorological Station. Daily weather forecasting results that occur are quite varied but the most dominant weather occurs during the next week that is Cloudy and Light Rain.
Pemodelan Spatial Error Model (SEM) Untuk Mengidentifikasi Indeks Pembangunan Manusia di Provinsi Maluku Tahun 2016 Fauzan Samallo; Yopi Andry Lesnussa; Abraham Z. Wattimena; Muhammad Yahya Matdoan
Jurnal Matematika Vol 8 No 1 (2018)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2018.v08.i01.p99

Abstract

Human Development Index (HDI) is a quality measure that can be used to determine the quality of human development that has been achieved. HDI is a composite index that composed of 3 components, such as: Length of life measured by life expectancy at birth, Education measured by average school duration and expectations school duration and standard of living measured by Purchasing Power Parity (PPP) in rupiah. The model used in this research is Spatial Error Model (SEM) to identify Influence of Variables X on IPM value and pattern of HDI distribution in a region with Ordinary Linear Square (OLS) parameter estimates. From the map thematic data that obtained, it can be seen that the pattern of the spread of Human Development Index (HDI) in Maluku Province has no effect on the distance of a region. There is a correlation between the components of HDI compilers to the HDI value in Maluku Province, because there is a spatial dependency on the dependent variable. Lambda value coefficient which is negative and significant at ? = 10% indicates that there is no correlation of HDI value in a region with other adjacent area. Also indicated by spatial residuals in adjacent areas do not have the same characteristics.
Cataract Disease Diagnosis System Using Artificial Neural Network Learning Vector Quantization Method Chrisani Waas; D. L. Rahakbauw; Yopi Andry Lesnussa
Journal of Applied Intelligent System Vol 4, No 2 (2019): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v4i2.3089

Abstract

Artificial Neural Network (ANN) is an information processing system that has certain performance characteristics that are artificial representatives based on human neural networks. ANN method has been widely applied to help human performance, one of which is health. In this research, ANN will be used to diagnose cataracts, especially Congenital Cataracts, Juvenile Cataracts, Senile Cataracts and Traumatic Cataracts based on the symptoms of the disease. The ANN method used is the Learning Vector Quantization (LVQ) method. The data used in this research were 146 data taken from the medical record data of RSUD Dr. M. Haulussy, Ambon. The data consists of 109 data as training data and 37 data as testing data. By using learning rate (α) = 0.1, decrease in learning rate (dec α) = 0.0001 and maximum epoch (max epoch) = 5, the accuracy rate obtained is 100%.
Aplikasi Analisis Korespondensi Berganda Terhadap Pemetaan Perkembangan Pembangunan Kota Ambon Yopi Andry Lesnussa; H. Kelian; E. R. Persulessy; R. J. Djami; M. W. Talakua
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 17, No 2 (2017)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v17i2.3100

Abstract

Penelitian ini bertujuan untuk mengetahui peta persepsi indikator pembangunan di kota Ambon dengan menggunakan Analisis Korespondensi Berganda. Dimana metode ini menganalisis kategori dari beberapa indikator pembangunan antara lain, banyaknya fasilitas Pendidikan, banyaknya fasilitas Kesehatan, penduduk miskin dan banyaknya Objek Wisata yang ada di kota Ambon. Dari hasil penelitian diperoleh kesimpulan bahwa kecamatan yang melalui jalan pusat kota Ambon menunjukan adanya peningkatan sarana pendidikan, sarana Kesehatan dan juga penduduk miskin, sedangkan untuk indikator Objek Wisata sendiri terjadi peningkatan pada kecamatan yang tidak dilalui Jalan Pusat Kota
STRUCTURAL EQUATION MODELING (SEM) UNTUK MENGANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KUALITAS PELAYANAN JASA PT. PLN (Persero) TERHADAP KEPUASAN PELANGGAN DI DESA BUANO UTARA Munahaji Lukaraja; Elvinus P. Persulessy; Yopi Andry Lesnussa; Muhammad Yahya Matdoan
VARIANCE: Journal of Statistics and Its Applications Vol 2 No 2 (2020): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol2iss2page93-102

Abstract

Structural Equation Modeling (SEM) adalah suatu teknik pemodelan statistik yang bersifat sangat cross-sectional (yang mengukur berapa variabel) linier dan kompleks. SEM merupakan gabungan dari dua teknik multivariat yaitu analisis faktor konfirmatori dan analisis jalur. Pada penelitian ini akan diterapkan Structural Equation Modeling untuk menganalisa faktor yang mempengaruhi kepuasan pelanggan. Data yang digunakan dalam penelitian ini adalah data primer yang diperoleh dengan menggunakan kuisioner kepada pelanggan PT. PLN (persero) di Desa Buano Utara Kec. Huamual Belakang dengan jumlah sampel sebanyak 30. Hasil dari penelitian ini diketahui bahwa model yang disusun telah cocok digunakan untuk mengindetifikasi dan memenuhi kriteria goodness of fit. Dari hasil analisa terhadap model tersebut diperoleh nilai r squqre 0.823 (untuk taraf nyata 5%) disimpulkan bahwa variabel laten kualitas pelayanan jasa PT. PLN (Persero) mempunyai pengaruh secara signifikan terhadap kepuasan pelanggan sedangkan variabel laten kepuasan pelanggan tidak berpengaruh terhadap kualitas pelayanan jasa PT. PLN (Persero).
OPTIMASI DALAM PENENTUAN DOSIS OPTIMAL PADA KEMOTERAPI TUMOR Yopi Andry Lesnussa; Subchan Subchan
Limits: Journal of Mathematics and Its Applications Vol 7, No 2 (2010)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (753.652 KB) | DOI: 10.12962/j1829605X.v7i2.1438

Abstract

Konstruksi model matematis dari suatu fenomena dalam bidangmatematika biologi merupakan hal yang sangat penting. Salahsatunya dapat diterapkan dalam proses kemoterapi tumor. Sebagai salah satu penyakit yang mematikan, pengobatan kemoterapi tumor perlu dioptimalkan untuk mencegah proliferasi sel yang tidak terkendali. Namun proses kemoterapi yang tidak tepat, dapat berakibat fatal bagi pasien penyakit tumor. Sehingga interval waktu dan dosis yang tepat dalam kemoterapi sangat efektif untuk mengurangi ukuran tumor. Permasalahan kemoterapi tumor dimodelkan sebagai permasalahan optimal dimana penentuan dosis obat optimummerupakan fungsi tujuannya. Permasalahan optimal selanjutnyaditransformasikan menjadi permasalahan pemrograman nonlinier (PNL), yang selanjutnya diselesaikan dengan software pemrograman nonlinier (PNL).
Identification of The Phases of The Spread of Covid-19 in Maluku Province with Richards Curve Nanang Ondi; Yopi Andry Lesnussa; Francis Yunito Rumlawang
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 7, No 2 (2021)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.v7i2.10925

Abstract

Richards Curve is an extension of the Logistics Curve which was first discovered in 1959 and is a type of sigmoid curve where in the sigmoid curve there are 3 growth phases, namely the logarithmic phase, the linear phase and the aging phase. This research aims to identify and determine the phase of the spread of COVID-19 in Maluku province with the Richards curve. From the calculation results obtained that the initial phase of the spread occurred on March 23 - July 5 2020, the peak phase of the spread occurred on July 6 - October 22 2020, the final phase of the peak of the spread occurred on October 23, 2020 - April 14, 2021 and began to enter the final phase of the spread on April 15, 2021.
Co-Authors Abdul Malik Balami Abraham Z Wattimena Abraham Z. Wattimena Abraham Zakaria Wattimena Abraham Zakharia Wattimena Astrid A Titahena Astrid G. Heumasse Aulele, Salmon Notje Berny Pebo Tomasouw C. G. Mustamu Charlita Fhilya Chrisani Waas Citra Fathia Palembang D Patty D. L. Rahakbauw Dewi Ls E R Persulessy E. R. Persulessy Elvinus P. Persulessy Endro Risamasu F. Kondo Lembang Fauzan Samallo Filiany S. Tutupary H. Kelian H. Lellolsima Henry W. M. Patty Hukubun, V Idah, Mus Rika Ilwaru, Venn Yan Ishak Jefri Esna Thomas Radjabaycolle Johan Bruiyf Bension Julianty Madiuw Latumeten, Ralf Lexy Jansen Sinay M. S. Noya Van Delsen M. W. Talakua M. W. Talakua Madiuw, Julianty Marlon Stivo Noya van Delzen Mozart W. Talakua Muhammad Y. Matdoan Muhammad Yahya Matdoan Muhammad Yahya Matdoan Munahaji Lukaraja Mus Rika Idah Nanang Ondi Ondi, Nanang R. J. Djami Rumlawang, F Y Rumlawang, Francis Y RUMLAWANG, FRANCIS YUNITO Set Sasake Sinay, Lexy Jansen Stevanny Tamaela Subchan Subchan Talakua, Mozart Winston Tamaela, Stevanny Umi Sari Rumata Venn Y.I. Ilwaru Yulia S. Kakisina Zakheus Putlely Zeth Arthur Leleury, Zeth Arthur