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All Journal Natural Science: Journal of Science and Technology Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Aplikasi Statistika & Komputasi Statistik Journal of System and Computer Engineering Parameter: Journal of Statistics STATISTIKA
Lilies Handayani
Universitas Tadulako
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Transportation

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PENERAPAN ANALISIS MULTIDIMENSIONAL SCALING (MDS) PADA PEMETAAN KABUPATEN/KOTA DI PROVINSI SULAWESI TENGAH BERDASARKAN INDIKATOR TENAGA KESEHATAN Islami, Mira Bela; Rais, Rais; Handayani, Lilies
Natural Science: Journal of Science and Technology Vol 8, No 2 (2019): Volume 8 Number 2 (August 2019)
Publisher : Univ. Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (972.43 KB)

Abstract

Health workers is any person who dedicates theirself in the health sector and have knowledge, skills and authority to make health efforts. The lack number of health workers or the univen distribution of health workers is a problem that often occurs in each region. This research will use the method  of multidimensional scaling in mapping districts / cities in Central Sulawesi Province based on indicators of health workers. The results obtained are formed in to 4 groups of districts/cities that have similarities among its members but different from other groups. In the group 1 is Palu, Group 2 contained Parigi Moutong districts. In the group 3 consists of Banggai, Poso, Sigi and Toli-Toli Districts. In the group 4 consist of Tojo Una-una, Morowali, Donggala, Morowali Utara, Banggai Laut, Buol, and Banggai Islands. Stress value obtained is 4.354% and the value of R^2 is 99.568%, which indicates that the data used can be mapped properly.
METODE DEKOMPOSISI MULTIPLIKATIF RATA-RATA BERGERAK UNTUK PERAMALAN TINGKAT PRODUKSI PADI LADANG SULAWESI TENGAH Kadoena, Faldi Christiawan; Rais, Rais; Handayani, Lilies
Natural Science: Journal of Science and Technology Vol 8, No 2 (2019): Volume 8 Number 2 (August 2019)
Publisher : Univ. Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (764.884 KB)

Abstract

Field rice is a rice plants that is planted in a sedentary or shifting location. This study aims to forecast field rice production using the Multiplicative Decomposition method of moving average, and to determine the size of forecasting accuracy using Tracking signal, data used is the data from Central Sulawesi Province Field rice production in 2008-2016 obtained from the Agriculture Service of Central Sulawesi Province The research procedure is begun by analyzing the components of decomposition, namely the components of trend (T), seasonal (S), cyclic (C) and random components (I) then multiplies the value of these components. Forecasting results using the decomposition method helping by the Minitab 18 application in 2017 show that the pattern of the data contains a declining trend with the equation Yt = 1895.60 - 7.97 × t, and has a strong seasonal pattern with the expected pattern of data that increases or decreases in certain months such as March, April, August and December. The forecasting results obtained are at the control limit of Tracking signal which is between -4 to +4 that means the forecasting of rice production in the province of Central Sulawesi in 2017 using the moving average Multiplicative Decomposition method is valid
ESTIMATOR NADARAYA-WATSON DENGAN FUNGSI KERNEL NORMAL DAN FUNGSI KERNEL KUADRATIK Saskia Amalia Putri; Ayudita Rahmi Aristya; Nur Azizah Janad; Yudy Novindri Tadale; Lilies Handayani
Journal of System and Computer Engineering (JSCE) Vol 3 No 1 (2022): JSCE: JANUARI 2022
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47650/jsce.v2i2.353

Abstract

The Human Development Index (HDI) is a comparative measurement of life expectancy, literacy, education and living standards for all countries around the world. The human development index is used to classify whether a country is a developed country, a developing country or a backward country and also to measure the effect of economic policies on the quality of life. The purpose of this study is to find out how the percentage of poor people and the unemployment rate are related to the human development index in Central Sulawesi. In this study, the Nadaraya-Watson kernel regression method was used with a regression comparison between normal kernel functions and quadratic kernel functions. Based on the results of the study, the best model on X1 (percentage of poor people) with the smallest MSE value is the CV.LS method with a bandwidth value of 1.369349, and for the best model on X2 (open unemployment rate) with the smallest MSE value, namely the CV.AIC method. with a bandwidth value of 1.331878.
Metode Ensemble K-Nearest Neighbor untuk Prediksi Indeks Harga Saham Gabungan (IHSG) di Indonesia Moh. Jusman; Nur’eni Nur’eni; Lilies Handayani
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.19641

Abstract

The Composite Stock Price Index (CSPI) is a guide for investors to see the movement of stock prices as a whole from time to time. These movements always change from time to time, so it is necessary to use analytical methods to make predictions. The method that can be used to examine this is the K-Nearest Neighbor method. The combination of the results of several K-NN predictions is an effective way to get one final prediction result, namely the method ensemble K-NN. The response variable used in this study is the Composite Stock Price Index (CSPI), while the predictor variables are the gold price, the rupiah exchange rate against the dollar, and the Dow Jones Industrial Average (DJIA) index. The data used are 52 periods. The data used for training are 39 periods and the data used for testing is 13 periods. The prediction results from the ensemble have better results than the K-NN. The prediction results from the ensemble have better results than the single K-NN. The prediction results from the method are ensemble K-NN average of 6078, 634 with a MAPE value of 7,16% including high accuracy
ANALISIS DISKRIMINAN LINEAR ROBUST PADA BERAT BAYI LAHIR DI RSUD LUWUK Nur'eni Nur'eni; Surni’a Surni’a; Lilies Handayani
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 19, No 1 (2019)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v19i1.4759

Abstract

Analisis diskriminan linear robust digunakan untuk mengklasifikasikan suatu pengamatan apabila dalam pengamatan tersebut terdapat pencilan. Pencilan akan menyebabkan matriks varians kovarians menjadi tidak robust. Minimum Covariance Determinant (MCD) digunakan untuk menduga sebagian pengamatan dengan meminimumkan determinan matriks kovariansi. Berat bayi lahir menurut WHO (1961) terbagi menjadi dua kategori yaitu berat bayi lahir rendah (BBL  2500 gram) dan berat bayi lahir normal (BBL > 2500 gram). Hasil dari klasifikasi berat bayi lahir di RSUD Luwuk Kabupaten Banggai dengan menggunakan metode analisis diskriminan linear robust diperoleh tingkat akurasi sebesar 81%.
Forecasting of the Amount of Rupiah Banknotes Flows in the East Region of Indonesia Using Circular Regression Jassinca Chrissma Audina; Rais; Lilies Handayani
Parameter: Journal of Statistics Vol. 2 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2021.v2.i1.15681

Abstract

Money is a tool that can be used in exchanging goods and services in a certain area. Increasing and decreasing in the money supply excessively can have a negative impact on the economy. For this reason, in order to maintain financial system stability in Indonesia, it is necessary to conduct an analysis of the data on the amount of outflows of rupiah currency at each Bank Indonesia office. In this study, a relationship analysis will be carried out between the eastern region of Indonesia and the amount of outflows of Bank Indonesia banknotes during the 2016-2018 period using circular regression analysis. The results showed that 83.03% of the variation in the amount of outflows of BI banknotes could be explained by the circular regression model that was formed. In addition, in the process of forecasting data on the amount of outflows of BI banknotes in the eastern region of Indonesia for the 2019-2020 period, the time series forecasting method is used which is based on the use of analysis of the relationship pattern between the estimated variables and the time variable.
Analysis of Skin Disease Infection After the Palu Earthquake Using Binary Logistic Regression Selvia Anggun Wahyuni; Lilies Handayani; Muhammad Akriyaldi Masdin; Salmia
Parameter: Journal of Statistics Vol. 2 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2021.v2.i1.15682

Abstract

The incidence of skin disease in Indonesia is still relatively high and is a significant problem. This is evidenced by the 2010 Indonesian Health Profile data which shows that skin and subcutaneous tissue diseases are the third rank of the 10 most common diseases among outpatients in hospitals throughout Indonesia. Skin disease is growing, as evidenced by data from the Indonesian Ministry of Health, the prevalence of skin disease throughout Indonesia in 2012 was 8.46%, then increased in 2013 by 9 %. Palu City is an area that has a high skin disease problem. According to the 2016 BPS of Palu City, skin diseases are among the top 10 diseases in Palu City with a total of 11,363 sufferers. The method used in this research is binary logistic regression. Based on the analysis that has been done, it can be concluded that the best model is formed as follows:. Based on the best model, it is found that the factors that influence the transmission of skin diseases after the Palu earthquake are genetic factors.
Clustering of Province in Indonesia Based on Aquaculture Productivity Using Average Linkage Method Fachruddin Hari Anggara Putera; Septina F. Mangitung; Madinawati; Lilies Handayani
Parameter: Journal of Statistics Vol. 2 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2021.v2.i1.15683

Abstract

Fisheries are one of the agricultural sub-sectors that play an important role in contributing to income figures for the state and the region because most of Indonesia's territory is water so that the fisheries sector is a sub-sector that is feasible to be developed in this country, one of which is through aquaculture. One of the efforts that can increase and maintain productivity in the aquaculture sector is to classify provinces that produce aquaculture production into groups based on the similarity of characteristics possessed by each province in Indonesia. In this study, clustering was carried out using cluster analysis using the average linkage method and based on the analysis results obtained showed that cluster 1 consists of 25 provinces, cluster 2 consists of 5 provinces, cluster 3 consists of 2 provinces, cluster 4 consists of 1 province, and cluster 5 consists of 1 province with a standard deviation value within a cluster of 11,729 and a standard deviation between clusters of 118,745.
Regresi Probit untuk Analisis Variabel-Variabel yang Mempengaruhi Perceraian di Sulawesi Tengah Nur'eni Nur'eni; Lilies Handayani
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 12 No 1 (2020): Journal of Statistical Application and Computational Statistics
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v12i1.211

Abstract

Sulawesi Tengah adalah salah satu Provinsi di Indonesia yang memiliki permasalahan dalam perceraian. Tingkat perceraian di Sulawesi Tengah pada tahun 2016 sebesar 2,44%. Persentase tingkat perceraian di Sulawesi Tengah ini menjadi tingkat perceraian ketiga tertinggi di Indonesia. Pada penelitian ini diteliti faktor-faktor yang mempengaruhi kasus perceraian di Sulawesi Tengah. Metode yang digunakan adalah regresi probit biner dengan variabel respon adalah status perkawinan. Hasil penelitian menunjukkan bahwa variabel prediktor yang mempengaruhi perceraian secara signifikan di Provinsi Sulawesi Tengah adalah umur kawin pertama (X2) kategori 1 (18-21 tahun) dan kategori 2 ( >21 tahun), tingkat pendidikan (X3) kategori 1 (SD) dan kategori 4 (di atas SMA), daerah tempat tinggal (X4) kategori 1 (kota) dan jumlah pengeluaran rumah tangga (X6) dengan tingkat ketepatan klasifikasi model sebesar 99,2%.
Corn Production Exploration of Central Sulawesi Using Multiplicative Winter Model Fachruddin Hari Anggara Putera; Rezi Amelia; Lilies Handayani
Parameter: Journal of Statistics Vol. 2 No. 2 (2022)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2022.v2.i2.15943

Abstract

Corn is a very important food ingredient after rice. Central Sulawesi corn production data is in the form of time series data which every year in certain months increases or decreases in production. Therefore, the method that can be used for forecasting is the winter multiplicative method. This study aims to build the best model for forecasting corn production in Central Sulawesi using the winter multiplicative method. The results of this study are used to explore corn production for the next period. Modeling is done by selecting the best combination of parameters and the best combination of model parameters is obtained with a mean absolute percentage error (MAPE) of 18% with a value of α = 0,5; γ = 0,1; and β = 0,1. The data plot of the forecasted corn production shows fluctuations which indicate seasonal factors and trends in it
Co-Authors Ayudita Rahmi Aristya Fachruddin Hari Anggara Putera Fachruddin Hari Anggara Putera Islami, Mira Bela Jassinca Chrissma Audina Kadoena, Faldi Christiawan Madinawati Marni Sagap Moh. Jusman Mohammad Fajri Muhammad Akriyaldi Masdin Nur Azizah Janad Nur Sakinah Nur'eni Nur'eni Nur'eni Nur'eni Nur'eni Nurfitra Nurmasyita Ihlasia Nur’eni Nur’eni Rais Rais Rais Rais Rezi Amelia Rohis Rachman Salmia Saskia Amalia Putri Selvia Anggun Wahyuni Septina F. Mangitung septyani kawuwung Surni’a Surni’a Yudy Novindri Tadale