Article Per Year (5 Year)
p-Index From 2020 - 2025
1.554
P-Index
This Author published in this journals
All Journal JURNAL ILMIAH MATEMATIKA DAN TERAPAN Parameter: Journal of Statistics Tadulako Science and Technology Journal Economics Development Analysis Journal
Nur'Eni
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Mathematics

Published : 9 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 9 Documents
Search

 1 
Identifikasi Model Generalized Space-time Autoregressive (GSTAR) untuk Nilai Inflasi di Pulau Sulawesi Nur'Eni; Lusiyanti, D; Gunawan, I
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 18 No. 1 (2021)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2021.v18.i1.15522

Abstract

This study aims to identify a forecast model for the value of inflation at seven locations on the island of Sulawesi, namely Palu, Makassar, Gorontalo, Kendari, Manado, Mamuju and Palopo. Estimation of the parameters of the GSTAR model is carried out using the Ordinary Least Square (OLS) method with uniform location weights. The analysis results show that the GSTAR model (1,1) can be used to predict the value of inflation in Sulawesi Island.
Analisis Pengaruh Faktor-Faktor Kebijakan Moneter Terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia (BEI) Anam, H; Nur'eni; Sain, H
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 19 No. 2 (2022)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2022.v19.i2.16218

Abstract

Harga saham merupakan sebuah acuan dalam mengambil suatu keputusan khususnya dalam trading di pasar modal. Dalam trading pasar modal tersebut, investor dapat melihat harga saham untuk menentukan seberapa besar dana yang akan investasikan. Pergerakan IHSG dipengaruhi oleh banyak faktor, baik faktor dalam negeri (internal) maupun faktor luar negeri (eksternal). Faktor internal dapat berupa pertumbuhan ekonomi, nilai tukar, inflasi, jumlah uang beredar(M2), tingkat suku bunga, stabilitas keamanan. Pada penelitian ini bertujuan untuk memahami pengaruh variabel kebijakan moneter yaitu kurs, inflasi, suku bunga SBI dan jumlah uang beredar (M2) terhadap Indeks Harga Saham Gabungan (IHSG) di BEI. Teknik analisis yang di gunakan statistik deskriptif, uji asumsi klasik dengan menggunakan model analisis regresi linier berganda dan hasil penelitian menunjukkan bahwa suku bunga SBI berpengaruh positif dan signifikan terhadap IHSG sedangkan kurs dan jumlah uang beredar berpengaruh negatif dan signifikan terhadap IHSG dan tingkat inflasi tidak berpengaruh signifikan terhadap IHSG di BEI.
Sales Prediction of Palu Arshop Clothing Using the High Order Chen Fuzzy Time Series Method Marni Sagap; Nur'eni; Iman Setiawan
Tadulako Science and Technology Journal Vol. 3 No. 2 (2023): Tadulako Science and Technology Journal
Publisher : LPPM Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/sciencetech.v3i2.17313

Abstract

Introduction: Arshop is one of the clothing stores in Palu City that is in great demand by the community. As one of the many clothing stores in Palu City Arshop to find a strategy to increase sales. One way that can be used is to make predictions to determine strategies to increase sales. Method: Higher-order Chen fuzzy time series method to predict the time series data of Arshop Palu clothing sales. Chen's high-order fuzzy time series is a time series analysis that can capture varied data patterns, one of which is seasonal patterns, and is formed based on two or more data in the past. Results and Discussion: The results of this study indicate that the high-order Chen fuzzy time series method has an accuracy rate of MAPE 15.59%, which is categorized as good the prediction results of the comparison between various orders show that the fourth-order Chen fuzzy time series is the best for predicting clothing sales of Arshop Palu. Conclusion: The prediction of clothing sales at Arshop Palu using the higher-order Chen fuzzy time series method resulted in a MAPE of 15.59%, which shows good accuracy because it is less than 20%. Based on the comparison of the accuracy values of the four orders, the fourth-order FTS proved to be the most effective for predicting the clothing sales of Arshop Palu.
Estimasi Peluang Gempa Bumi Menggunakan Metode Maksimum Likelihood Dan Distribusi Poisson Di Wilayah Sulawesi Tengah Jamidun; Nur'Eni; Rais
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 20 No. 2 (2023)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2023.v20.i2.16683

Abstract

Sulawesi Tengah merupakan salah satu daerah yang sering dilanda gempa bumi. Hal ini mengindikasikan bahwa daerah ini memiliki aktifitas seismik yang cukup tinggi. Secara geologi wilayah ini mendapat tekanan karena interaksi tumbukan 3 lempeng utama dunia yakni lempeng Eurasia, Indo Australia dan Pasifik Akibat tumbukan tersebut menyebabkan terbentuknya beberapa Sesar yang aktif. Gempa bumi yang menyebabkan liquifakasi dan sunami di Sulawesi Tengah pada 28 September 2018 sumber gempanya berada dijalur lintasan sesar Palu Koro di kedalaman 10 km di bawah dasar permukaan laut pada jarak 80 km barat laut Kota Palu. Waktu kejadian gempa bumi besar hingga saat ini belum ada ahli yang bisa meprediksi secara tepat. Untuk itu melalui kajian ini kami melakukan pendekatan untuk memprediksi waktu kejadian gempa bumi ini dengan melakukan analisis secara statistik menggunakan metode maksimum likelihood dan distribusi Poisson dari data data gempa bumi yang pernah terjadi. Nilai parameter seismotektonik () dari hubungan magnitudo dengan frekuensi gempa bumi, diperoleh nilai yang terbesar pada region I untuk gempa menengah yakni sebesar 0,8065, hal ini menyatakan bahwa pada daerah region I merupakan daerah rawan terjadi gempa bumi karena kemampuan untuk meredam energi penggeseran sesar relatif kecil sehingga tingkat kerapuhan material yang tersusun di dalam bumi tersebut yang jika diberi gaya sedikit akan terjadi patahan dan kemudian terjadilah gempa bumi.
Pemodelan Kasus Balita Stunting Di Provinsi Sulawesi Tengah Menggunakan Robust Geographically Weighted Regression Gamayanti, Nurul Fiskia; Nur'eni; Fadjryani; Difa Shalsabila
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 20 No. 2 (2023)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2023.v20.i2.16585

Abstract

Stunting pada balita merupakan kasus yang semakin berbahaya bagi balita. Dimana kasus tersebut dapat mengakibatkan kematian pada penderitanya. Jumlah kasus kejadian stunting balita di Sulawesi Tengah terus meningkat setiap tahunnya. Pada pemodelan kasus balita stunting di Sulawei Tengah dibutuhkan pemodelan khusus dimana pada kasus tersebut terdapat keragaman spasial dan terdapat data pencilan sehingga dibutuhkan penanganan khusus yaitu model yang dapat mengakomodasi keragaman spasial dan pencilan tersebut yaitu Robust Geographically Weighted Regression (RGWR). Pada hasil penelitian ini diperoleh 13 model kasus balita stunting untuk masing-masing kabupaten/kota di Sulawesi Tengah. Dimana tingkat akurasi dari model yang diperoleh sebesar 12,60% artinya model RGWR yang diperoleh telah sesuai dan efektif dalam memodelkan kasus balita stunting di Sulawesi Tengah
Optimization of Overdispersion Modeling in Low Birth Weight Cases in Central Sulawesi Using Conway-Maxwell Poisson Regression Gamayanti, Nurul Fiskia; Nur'eni; Fadjryani; Astuti, Dewi Puji
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 21 No. 2 (2024)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2024.v21.i2.17429

Abstract

Low birth weight (LBW) is a condition of a baby weighing less than 2,500 grams where gestational age is not taken into account and the baby's weight is measured within 24 hours after birth. The level of infant development also plays an important role in determining the mortality rate and incidence rate of disease in infants with LBW. This study aims to find models and factors that influence LBW using Conway Maxwell Poisson Regression (CMPR). CMPR is an extension method of Poisson regression that has the advantage of overcoming violations of the equidispersion assumption, where data can experience overdispersion or underdispersion
Analysis of Economic Growth with Spatial Interaction Between Regions in Indonesia Nur'eni; Patta Tope; Nadiatulhuda Mangun
Economics Development Analysis Journal Vol. 14 No. 1 (2025): Economics Development Analysis Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edaj.v14i1.21326

Abstract

This study employs a quantitative research approach with a descriptive methodology to analyze spatial interconnections between provinces in Indonesia. The research utilizes panel data regression, assisted by EViews software, and a Spatial Autoregressive (SAR) fixed effects model using R software. The spatial panel regression testing results indicate that the SAR fixed effects model is the most appropriate. The findings reveal that inflation (X1), exports (X3), and national health insurance (X6) have significant effects on economic growth. Global spatial autocorrelation was analyzed using the Moran Index and the Local Indicator of Spatial Autocorrelation (LISA) to identify provinces with spatial autocorrelation from 2019 to 2023. For inflation, 13 provinces exhibit spatial interconnections, namely West Java, Central Java, DI Yogyakarta, North Sumatra, North Maluku, Papua, Bengkulu, Bangka Belitung Islands, West Kalimantan, DKI Jakarta, West Sumatra, Jambi, and South Sumatra. For exports, 11 provinces demonstrate significant spatial interconnections, including West Java, Central Java, Lampung, South Sumatra, Jambi, North Maluku, Bengkulu, Bangka Belitung Islands, DI Yogyakarta, Papua, and Southeast Sulawesi. Meanwhile, for national health insurance, 11 provinces show significant spatial interconnections: Southeast Sulawesi, West Sumatra, Papua, Riau, Bengkulu, Jambi, South Sumatra, Bangka Belitung Islands, Riau Islands, West Kalimantan, and North Kalimantan.
SENTIMENT ANALYSIS OF REVIEW DATA OF THE RUANGGURU ONLINE LEARNING APPLICATION USING THE C5.0 ALGORITHM Izzah, Nurul; Nur'eni; Pitri, Rizka
Parameter: Journal of Statistics Vol. 3 No. 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i2.16919

Abstract

Sentiment analysis is process to determine the sentiment of a person that is manifested in the form of text. Internet users write their opinions and everything that concerns them in the google play store review column. Moreover, when the world of education could not carry out face-to-face learning due to the covid-19 pandemic, learning turned to e-learning applications. Through this innovation, many pros and cons flow from the community with the existence of Ruangguru online learning application in the world of education. This research was conducted with the aim of determining word cloud visualization and the accuracy of the results of sentiment analysis of review data on the Ruangguru application using the C5.0 algorithm. The word cloud visualization results are dominated by word such as “paham”, “bagus”, “mudah”, “suka”, “langganan”, “seru”, “nyaman”, “senang”, “menarik”, “keren”, “lancar”, “sukses”. This shows that Ruangguru Application is a good application because it is dominated by positive sentiment words which means that users find it helpful and easy to understand the learning material in Ruangguru. The results of the Confusion Matrix show that the model successfully classifies 0.8557 or 85.57% of the data correctly from all test data
REGRESSION ANALYSIS OF ROBUST ESTIMATION-S WITH TUKEY BISQUARE WEIGHTING ON POVERTY LEVEL ON SULAWESI ISLAND Saputri, Sandra; Nur'eni; Masyitah Meliyana R, Sitti
Parameter: Journal of Statistics Vol. 3 No. 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i2.16923

Abstract

Poverty is a situation where a person experiences difficulty in meeting basic needs. There are several factors that influence poverty, including population, unemployment, gross regional domestic product, human development index, average years of schooling and labor force participation rate. Therefore, it is necessary to carry out regression analysis to determine the relationship between one variable and other variables. One method for estimating regression parameters is the least squares method. Some classic assumptions are not met because there are outlier data. Outliers are data that do not follow the overall distribution pattern, so a method is used that can overcome outliers, namely the S-estimation robust regression method with the Tukey bisquare weighting function. The results of the research show that the best model was obtained from robust S-estimation regression with Tukey bisquare weighting, namely factors that influence the level of poverty on the island of Sulawesi, namely Population Number ), Human Development Index ( ), Average Years of Schooling ( ) and, Force Participation Level. Work .
Co-Authors Anam, H Desy Lusiyanti Dewi Puji Astuti, Dewi Puji Difa Shalsabila Fadjryani, Fadjryani Gamayanti, Nurul Fiskia Gunawan, I Iman Setiawan IZZAH, NURUL Jamidun Marni Sagap Masyitah Meliyana R, Sitti Nadiatulhuda Mangun Patta Tope Pitri, Rizka Rais Sain, H Saputri, Sandra