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Jurnal Matematika
Published by Universitas Udayana
ISSN : 16931394     EISSN : 26550016     DOI : https://doi.org/10.24843/JMAT
Core Subject : Education,
Mathematics
Jurnal Matematika (p-ISSN: 1693-1394 |e-ISSN: 2655-0016| DOI: 10.24843/JMAT ) is an open access journal which publishes the scientific works for researchers. The articles of this journal are published every six months, that is on June and December.
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Articles 7 Documents
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Search results for , issue "Vol 10 No 2 (2020)" : 7 Documents clear
Pemilihan Titik Knot Optimal Model Spline Truncated Dalam Regresi Nonparametrik Multivariabel dengan GCV Luh Putu Safitri Pratiwi
Jurnal Matematika Vol 10 No 2 (2020)
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.2020.v10.i02.p125

Abstract

One of the most frequently studied nonparametric regression model approaches is the spline truncated. This method is applied to cases of Maternal Mortality Rate because in various cases there is an increase in maternal mortality problems so that the government is expected to be more serious in dealing with and suppressing the MMR value through the programs launched or by overcoming the factors that significantly influence the high MMR value. This study aims to examine the determination of the optimal knot point of the multivariable nonparametric spline regression model using the GCV method as the optimal knot point selection method. The criteria for selecting the best model in this study using the MSE value. The results obtained are the best model suitable for AKI 2017, namely by using the GCV method which is located in the three knot linear spline, which is 0.07722 and an MSE value of 0.018. The variables that have an effect on the model are the percentage of deliveries performed with the help of medical personnel (x1), the percentage of pregnant women who receive Fe1 tablets (x2), the percentage of pregnant women implementing the K1 (x3), and the percentage of pregnant women implementing the K4 (x4).
Estimasi Maksimum Likelihood Melalui Algoritma Ekspektasi Maksimasi Untuk Model Regresi Linear dengan Data Hilang Hariza hayu S
Jurnal Matematika Vol 10 No 2 (2020)
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.2020.v10.i02.p127

Abstract

Data merupakan salah satu poin penting dalam setiap analisis data, karena tidak akan mungkin analisis dapat dilakukan jika datanya tidak lengkap. Data yang digunakan diharapkan merupakan data yang baik. Namun pada kenyataannya, seringkali data tidak sesuai dengan yang kita harapkan. Data yang tidak lengkap menyebabkan proses mengambil kesimpulan mejadi lebih sulit. Jika data yang hilang diabaikan, maka akan menyebabkan kesimpulan bias atau tidak valid. Dalam penelitian ini akan digunakan model regresi linear. Analisis regresi adalah analisis statistik yang dilakukan untuk memodelkan hubungan antara (variabel dependen) dan variabel random kategorik (variabel independen). Untuk variabel kontinu dan variabel diskrit, dengan mengasumsikan variabel yang seluruhnya teramati dan terdapat beberapa variabel yang hilang. Adapun klasifikasi data hilang yang akan dibandingkan terdiri dari tiga klasifikasi yaitu: MCAR, MAR, dan MNAR. Pembahasan ini diakhiri dengan studi kasus mengenai estimasi nilai data hilang pada variabel presentasi data xerostomia dengan menggunakan algoritma EM untuk menghitung maksimum likelihood estimasi (MLE) pada model regresi linear dengan tiga klasifikasi data hilang.
Penentuan Rute Terpendek dengan Menggunakan Algoritma Dijkstra pada Jalur Bus Sekolah I Putu Winada Gautama; Koko Hermanto
Jurnal Matematika Vol 10 No 2 (2020)
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.2020.v10.i02.p128

Abstract

Peran angkutan umum atau bus sekolah sangat vital dalam mengurangi pelanggaran lalu lintas bagi pengendara di bawah umur. Alat transportasi bus sekolah mulai populer di Bali. Khususnya di kota Denpasar, dinas perhubungan Kota Denpasar sudah beroperasi pada bulan September 2017. Salah satu optimasi yang dapat dilakukan adalah menentukan jarak terpendek dari rute bus sekolah. Semakin pendek jarak yang dilalui tentunya berdampak pada biaya dan waktu. Biaya yang dikeluarkan dapat diminimalkan dan waktu tempuh lebih efisien. Berdasarkan hasil yang diperoleh bahwa biaya bahan bakar yang dihabiskan bus sekolah shift pagi adalah Rp 70.132,-. Hasil ini dapat memberikan gambaran untuk Dinas Perhubungan kota Denpasar mengenai terapan matematika dalam menentukan rute yang dapat mengoptimalkan pengeluaran biaya bahan bakar
Peramalan Nilai Tukar Petani Kabupaten Lamongan dengan Arima Mohammad Syaiful Pradana; Dinita Rahmalia; Ericha Dwi Ayu Prahastini
Jurnal Matematika Vol 10 No 2 (2020)
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.2020.v10.i02.p126

Abstract

Agriculture is a sector that has a significant role for the Indonesian economy. In Lamongan Regency, about 35.71 percent of the workers depends on the primary agricultural sector, so it is not surprising that the agricultural sector is the basis of growth, especially in rural areas. Agricultural development is oriented towards improving the welfare of farmers. One of the measurements the level of farmer welfare is by calculating the Farmer Exchange Rate. It is the relationship between the produce sold by farmers and the goods and services purchased by farmers. Seeing how important this Farmer Exchange Rate is, predicting the value of Farmer Exchange Rate in the following year will be very useful. The results of this value can be a benchmark to anticipate all situations in the following years and how to control the rising value of Farmer Exchange Rate so as to improve the welfare of the people of Lamongan. From the results of the analysis and discussion, food plants have a low NTP value, namely ?100 per month for a period of 3 years and have the highest Farmer Exchange Rate reduction in 2019 of 10.25%.
Estimasi Koefisien Regresi Linear Berganda dengan Metode Goal Programming Baiq Diah Fitasari
Jurnal Matematika Vol 10 No 2 (2020)
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.2020.v10.i02.p129

Abstract

The alternative method that can be used to determine the value of a multiple linear regression variable coefficient is goal programming method. The kind of data used in this research is secondary data namely the production of freshwater fish pond system data in the Province of West Nusa Tenggara based on Fisheries Service of West Nusa Tenggara Province year 2018. Software used to assist in reckoning is POM for Windows.Settlement calculation procedure in this research was conducted in two stages, namely the calculation with variable ????????4 and the calculation without variables ????????4. The results obtained with the variable ????????3 namely ????????1 = ????????0 = 64,08 ; ????????2 = ????????1 = 2,67 ; ????????3 = ????????2 = 0,27 ; ????????4 = ????????3 = 0, and the results obtained without variables ????????4 namely ????????1 = ????????0 = 64,08 ; ????????2 = ????????1 = 2,67 ; ????????3 = ????????2 = 0,24. The production of fresh water fish pond system in the Province of West Nusa Tenggara were affected by extensive fish ponds and food availability, while the number of domestic aquaculture freshwater fish do not affect production. Keywords : Multiple Linear Regression, Goal Programming, Production of Fish.
Data Mining Pada Faktor-Faktor Potensi Daerah di Kabupaten Sidoarjo Provinsi Jawa Timur Trianingsih Eni Lestari; Hendro Permadi; Sri Susilowati
Jurnal Matematika Vol 10 No 2 (2020)
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.2020.v10.i02.p124

Abstract

Abstract: Sidoarjo is one of the districts located in East Java that has developed rapidly. The remarkable progress can be achieved due to several potentials had by its people, for instance, industries, trades, small and medium businesses. Therefore, this research aims to find out the information regarding dominating factors had by the Sidoarjo using data mining. The result shows that Keboansikep, Sawotratap, Tebel, Keboananom, Gedangan, Keboguyang, Ketajen, Sidomulyo, Terik, Ponokawan, Sedengan Mijen, and Barengkrajan villages are the most potential villages in Sidoarjo. Based on the classification method, it is found that the villages of Keboansikep, Sawotratap, Tebel, Keboananom, Gedangan, and Ketajen (Gedangan District) have local potential in the form of agricultural factors such as rice and secondary crops. All residences in Keboguyang Village (Jabon District) already have an IMB. Meanwhile, the villages of Sidomulyo, Terik, Ponokawan, Sedengan Mijen, and Barengkrajan (Krian District) have high early childhood education factors such as kindergarten students, kindergarten teachers, and kindergarten schools Keywords: Data Mining, Local Potential, Biplot analysis
Memodelkan Impor Beras Menggunakan Regresi Data Panel Eka N Kencana; Darma Arnawa; Ketut Jayanegara
Jurnal Matematika Vol 10 No 2 (2020)
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.2020.v10.i02.p130

Abstract

Abstract Rice is one of the world’s most important commodities. The Food and Agri-cultural Organizations estimates about 90 percent of the world’s rice is produced bycountries in the Asian continent with the rice production centers located in the ASEANregion. As an agricultural country, Indonesia is ranked third in the world rice producersafter China and India, and in the first rank of ASEAN rice producers. However, Indone-sia along with other producing countries in ASEAN also import rice. This article aimsto model rice imports from 5 ASEAN countries. Using data from FAO for the period2009–2018, 3 types of Panel Data Regression models were applied to model rice imports.The results of the analysis show Random Effect Model (REM) is the most appropriatemodel for rice imports in 5 ASEAN countries with the difference for two consecutiveyears import, consumption, and rice production was used as explanatory variables .Keywords: import, panel data, random effect, regression, rice.

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