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Utami, I T
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Mathematics

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PEMODELAN TIME SERIES DENGAN PROSES ARIMA UNTUK PREDIKSI INDEKS HARGA KONSUMEN (IHK) DI PALU – SULAWESI TENGAH Wigati, Y; Rais, Rais; Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 12 No. 2 (2015)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (545.341 KB) | DOI: 10.22487/2540766X.2015.v12.i2.7908

Abstract

PEMODELAN TIME SERIES DENGAN PROSES ARIMA UNTUK PREDIKSI INDEKS HARGA KONSUMEN (IHK) DI PALU – SULAWESI TENGAH
ANALISIS KORESPONDENSI UNTUK MELIHAT POLA HUBUNGAN FAKTOR – FAKTOR ALASAN MAHASISWA TERHADAP PEMILIHAN JURUSAN MATEMATIKA DI FMIPA UNTAD Rahmayani, R; Rais, Rais; Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 14 No. 1 (2017)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (452.374 KB) | DOI: 10.22487/2540766X.2017.v14.i1.8356

Abstract

ANALISIS KORESPONDENSI UNTUK MELIHAT POLA HUBUNGANFAKTOR – FAKTOR ALASAN MAHASISWA TERHADAPPEMILIHAN JURUSAN MATEMATIKA DI FMIPA UNTAD
MENGANALISIS DAN MELIHAT HUBUNGAN ANTARA FAKTOR – FAKTOR YANG MEMPENGARUHI PEMILIHAN PRODUK MIE INSTAN STUDI KASUS : MAHASISWA JURUSAN MATEMATIKA FMIPA UNTAD Rahmayuni, N; Rais, R; Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 14 No. 2 (2017)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (471.144 KB) | DOI: 10.22487/2540766X.2017.v14.i2.9023

Abstract

MENGANALISIS DAN MELIHAT HUBUNGAN ANTARA FAKTOR – FAKTORYANG MEMPENGARUHI PEMILIHAN PRODUK MIE INSTAN STUDI KASUS : MAHASISWA JURUSAN MATEMATIKA FMIPA UNTAD
PERBANDINGAN ANTARA METODE CART (CLASSIFICATION AND EGRESSION TREE) DAN REGRESI LOGISTIK (LOGISTIC REGRESSION) DALAM MENGKLASIFIKASIKAN PASIEN PENDERITA DBD (DEMAM BERDARAH DENGUE) Lestawati, R; Rais, Rais; Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 15 No. 1 (2018)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (335.219 KB) | DOI: 10.22487/2540766X.2018.v15.i1.10206

Abstract

Classification is one of statistical methods in grouping the data compiled systematically. The classification of an object can be done by two approaches, namely classification methods parametric and non-parametric methods. Non-parametric methods is used in this study is the method of CART to be compared to the classification result of the logistic regression as one of a parametric method. From accuracy classification table of CART method to classify the status of DHF patient into category of severe and non-severe exactly 76.3%, whereas the percentage of truth logistic regression was 76.7%, CART method to classify the status of DHF patient into categories of severe and non-severe exactly 76.3%, CART method yielded 4 significant variables that hepatomegaly, epitaksis, melena and diarrhea as well as the classification is divided into several segmens into a more accurate whereas the logistic regression produces only 1 significant variables that hepatomegaly
APLIKASI REGRESI KUANTIL PADA KASUS DBD DI KOTA PALU SULAWESI TENGAH Idris, N; Rais, Rais; Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 15 No. 1 (2018)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (597.672 KB) | DOI: 10.22487/2540766X.2018.v15.i1.10207

Abstract

Palu city is one of the cities with unstable changes of natural conditions. The natural conditions such as the frequency of rainy day, temperature and humidity which are always changeable bring bad impacts and will cause of diseases especially dengue hemorrhagic fever (DBD). Therefore, it needs an action to recognise whether or not the natural condition factor influences the spread of DBD and determines what factors of the natural condition can influence the spread of DBD. This research applied quantile regression in the case of DBD in Palu city. Quantile regression is an analysis technique regarding to the functional relationship between one dependent variable with one or more independent variables which can provide accurate and stable results even though there will be outliers. Based on the result of the research, it is obtained that the natural condition factor affected the spread of DBD. This is because from 3 natural conditions only 11 significant or influential quantiles on the tested data, the quantiles are 0,30; 0,35; 0,40; 0,45; 0,50; 0,55; 0,60; 0,65; 0,70; 0,75 and 0,80. Meanwhile the most influential factor of natural conditions in spreading DBD is  the frequency of rainy day because it has positive which means that 1 progress of percentage will increase the quantity of DBD case.
PERBANDINGAN KINERJA KLASIFIKASI SUPPORT VECTOR MACHINE (SVM) DAN REGRESI LOGISTIK BINER DALAM MENGKLASIFIKASIKAN KETEPATAN WAKTU KELULUSAN MAHASISWA FMIPA UNTAD Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 15 No. 2 (2018)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.82 KB) | DOI: 10.22487/2540766X.2018.v15.i2.11361

Abstract

Evaluasi kinerja klasifikasi dapat ditentukan berdasarkan persentase besarnya kesalahan klasifikasi (misclassification rate atau MCR). Penelitian ini bertujuan membandingkan kinerja klasifikasi ketepatan waktu kelulusan mahasiswa FMIPA UNTAD dengan menggunakan metode support vector machine dan regresi logistik biner. Hasil penelitian diperoleh bahwa kesalahan klasifikasi dengan menggunakan metode Support Vector Machine (SVM) dan regresi logistik biner masing-masing sebesar 16.84% dan 19.3%. Berdasarkan perbandingan kinerja kedua metode tersebut, metode dengan kesalahan klasifikasi terkecil adalah metode Support Vector Machine. Metode tersebut dapat digunakan untuk mengklasifikasikan ketepatan waktu kelulusan mahasiswa FMIPA UNTAD
ANALISIS KLASTER PAUTAN LENGKAP UNTUK MENGELOMPOKKAN KABUPATEN/KOTA DI PROVINSI SULAWESI TENGAH BERDASARKAN INDIKATOR KRIMINALITAS Utami, I T; Rais, Rais; Seftiani, W
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 16 No. 1 (2019)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (738.659 KB) | DOI: 10.22487/2540766X.2019.v16.i1.12757

Abstract

Criminality is all kinds of actions and deeds which is economically and psychologically harmful. The statistical method could be used to classify the crime is cluster analysis. Cluster analysis is a multivariate method which aims to classify a sample of subjects (or objects) on the basis of a set of measured variables into a number of different groups such that similar subjects are placed in to the same group. The objective of this research is to classify Regency/City in Central Sulawesi Province based on the criminality indicator and to discover the profile of each cluster which had been formed. The results of the study shows that those are two clusters formed: Cluster 1 consists of Buol, Banggai, Morowali, Toli-Toli, Donggala, and Tojo Una-Una Regency; Cluster 2 consists of Regency/Palu City, and Parigi Moutong. The profile of each cluster is: Cluster 1 with low crime rate on average and Cluster 2 with high crime rate on average.Keywords : Cluster Analysis, Complete Linkage, Criminality, Hierarchy Method.
Co-Authors Idris, N Lestawati, R Rahmayani, R Rahmayuni, N Rais Rais Rais, R Seftiani, W Wigati, Y