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Isran K. Hasan
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Department of Statistics, 3rd Floor Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo Jl. Prof. Dr. Ing. B.J Habibie, Tilongkabila Kabupaten Bone Bolango, 96119
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INDONESIA
JAMBURA JOURNAL OF PROBABILITY AND STATISTICS
Published by Universitas Negeri Gorontalo
ISSN : -     EISSN : 27227189     DOI : https://doi.org/10.34312/jjps
Core Subject : Science, Social,
Computer Science & IT Decision Sciences, Operations Research & Management Environmental Science Social Sciences
Probability Theory Mathematical Statistics Computational Statistics Stochastic Processes Financial Statistics Bayesian Analysis Survival Analysis Time Series Analysis Neural Network Another field which is related to statistics and the applications Another field which is related to Probability and the application
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 44 Documents
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PERBANDINGAN MATRIKS PEMBOBOT ROOK DAN QUEEN CONTIGUITY DALAM ANALISIS SPATIAL AUTOREGRESSIVE MODEL (SAR) DAN SPATIAL ERROR MODEL (SEM) INGKA RIZKYANI AKOLO
Jambura Journal of Probability and Statistics Vol 3, No 1 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i1.13582

Abstract

The spatial weighting matrix is very important to overview of the relationship between one location to another in the spatial regression. In this study, the authors compare the weighting matrix of queen contiguity and rook contiguity in the SAR and SEM models in stunting cases in Bone Bolango Regency, Gorontalo Province. The variables used are the number of IDL, the percentage of LBW, the amount of proper sanitation, the percentage of exclusively breastfed babies, and the number of poor people. The purpose of this study was to determine the factors that influence stunting in Bone Bolango Regency, compare the results of the analysis of the rook contiguity and queen contiguity matrices in the SAR and SEM models and determine the best model and weighting matrix in stunting modeling in Bone Bolango Regency. The results showed that the significant factor in the SAR model was the number of poor people, while the significant factors in the SEM model were the number of IDL, the number of proper sanitation, and the percentage of exclusively breastfed babies. In the SEM model, the p-value of queen contiguity is smaller than that of rook contiguity.The best model in this study is the SEM model.
PENERAPAN MODEL SPASIAL DURBIN DENGAN UJI LANJUTAN LOCAL INDICATOR OF SPATIAL AUTOCORRELATION UNTUK MELIHAT PENYEBARAN STUNTING DI KABUPATEN BONE BOLANGO LISA SYAHRIA HASIRU; ISMAIL DJAKARIA; ISRAN K HASAN
Jambura Journal of Probability and Statistics Vol 3, No 1 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i1.13083

Abstract

One of the spatial regression analysis used is the spatial durbin model (SDM). This model can be applied to obtain the relationship between X and Y variables and their spatial effects. This research was continued by testing the local spatial autocorrelation, namely the local indicator of spatial autocorrelation (LISA) which aims to provide information on the pattern of spatial relationships of each observation area in Bone Bolango regency. Stunting cases in Gorontalo province, especially in Bone Bolango regency, are in a status that needs to be addressed immediately due to the prevalence rate in Bone Bolango regency in 2019 above 20% based on the WHO standard. The results showed that the factors that significantly affected stunting in 2019 in Bone Bolango regency were exclusive breastfeeding, the  proper sanitation and poverty. Meanwhile, based on the spatial effect, the factors that significantly affected stunting in 2019 in Bone Bolango regency were the percentage of exclusive breastfeeding, the percentage of LBW, the number of children with CBI and poverty. Based on result from the LISA, the observation areas of stunting cases showed that the percentage of exclusive breastfeeding, the number of children with CBI and povertu had a spatial autocorrelation or forming a grouping on the distribution of the stunting cases, the number of children with IDL and poverty, there are sub-districts that have spatial autocorrelation.
PERBANDINGAN METODE LIFE TABLE DAN METODE KAPLAN MEIER PADA ANALISIS SURVIVAL PENDERITA STROKE DI RSUD ALOEI SABOE KOTA GORONTALO PADA AGUSTUS SAMPAI DENGAN DESEMBER 2019 DEWI ZULYANI POMALINGO; ISMAIL DJAKARIA; BOBY RANTOW PAYU
Jambura Journal of Probability and Statistics Vol 3, No 1 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i1.14178

Abstract

Penelitian ini bertujuan untuk mengestimasi fungsi survival pasien penderita stroke di RSUD Aloei Saboe kota Gorontalo bulan Agustus sampai dengan Desember 2019 menggunakan metode life table dan Kaplan Meier. Hasil estimasi keduanya dibandingkan dengan estimasi terbaik adalah yang menghasilkan nilai standar error terkecil. Hasil penelitian menunjukkan probabilitas survival pasien menggunakan estimasi life table adalah sebesar 0,8591 dan Kaplan Meier sebesar 0,8628. Berdasarkan perbandingan nilai standar error, dapat disimpulkan bahwa pada awal waktu survival, estimasi life table dan Kaplan Meier sama baiknya untuk menganalisis survival pasien. Namun untuk waktu survival yang semakin besar, estimasi Kaplan Meier menghasilkan nilai standar error yang lebih kecil dibandingkan estimasi life table.
DISTRIBUTED LAG MODEL PENGARUH JUMLAH UANG BEREDAR TERHADAP NILAI TUKAR RUPIAH MENGGUNAKAN METODE KOYCK DAN ALMON SRIRAPI H LIHAWA; RESMAWAN RESMAWAN; DEWI RAHMAWATY ISA; LA ODE NASHAR
Jambura Journal of Probability and Statistics Vol 3, No 1 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i1.11805

Abstract

A regression model that contains the dependent variable which is influenced by the current independent variable, and is also influenced by the independent variable at the previous time is called a distributed lag model. Distributed lag model is a dynamic model in econometrics that is useful in empirical econometrics because it makes a static economic theory dynamic by taking into account the role of time explicitly. There are two distributed lag models, namely the infinite lag model and the finite lag model using the Koyck method and the Almon method in determining the estimated Distributed lag model. This study aims to determine the Distributed lag model for the effect of the money supply on the rupiah exchange rate and determine the best model based on the Koyck method and the Almon method. From the results of selecting the best model based on the SIC value and judging by the more precise R2 of the Koyck method, the resulting model ist  = 7958 + 0.0002Xt + 0.000177Xt-1+ 0.000157Xt-2+ 0.000139Xt-3 + 0.0000123Xt-4
ANALISIS KLASIFIKASI ARTIST MUSIC MENGGUNAKAN MODEL REGRESI LOGISTIK BINER DAN ANALISIS DISKRIMINAN ANDREA TRI RIAN DANI; VITA RATNASARI; LUDIA NI'MATUZZAHROH; IGAR CALVERIA AVIANTHOLIB; RADITYA NOVIDIANTO; NARITA YURI ADRIANINGSIH
Jambura Journal of Probability and Statistics Vol 3, No 1 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i1.13708

Abstract

Characteristics of a song are an important aspect that must be kept authentic by a singer. Using the Spotify API feature, we can extract the characteristics or elements of a song sung by a singer.  There are eight (8) elements that we can get from the extraction of a song, namely: Danceability, Energy, Loudness, Speechiness, Acousticness, Liveness, Valence, and Tempo. Based on the extraction results, we can label the music artist using the classification analysis method. In this study, the labels are music artists, namely Ariana Grande and Taylor Swift. This study aims to obtain the classification of music artist labels using binary logistic regression methods and discriminant analysis. The response variable used in this study is Artist Music (Y) which is categorized into two categories, namely Ariana Grande (Y=0) and Taylor Swift (Y=1). The data will be divided into training and testing data with the proportion of data 90:10 and 80:20. Based on the results of the analysis, the binary regression model that was built, with the proportion of training testing data that is 90:10 has a classification accuracy for data testing of 90.00%.
PEMODELAN SPASIAL PRODUKSI IKAN PADA INDUSTRI BUDIDAYA PERIKANAN DI KOTA CILEGON Atia Sonda; Faula Arina; Ade Sri Mariawati; Asep Ridwan; Dyah Lintang Trenggonowati
Jambura Journal of Probability and Statistics Vol 3, No 2 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i2.16753

Abstract

The aquaculture industry in Cilegon City is fairly substantial. In the year 2020, 230.09 tons of farmed fish were produced. In Cilegon City, fish production statistics is often used for each sub-district. So far, no research has been undertaken to examine the dependency of fish output from one district to the next. Spatial modeling is used to examine the spatial correlation of fish production data in each sub-district, making it easier to characterize observations in a sub-district and their relationships with other sub-districts. A semivariogram model was fitted using the fish production data, and it was discovered that fish production in the city of Cilegon followed the cubic model with model parameters C = 2.9891 and range a = 5.28. Furthermore, using this spatial model, assessment of fish production in a location, in this example Cilegon City, can be carried out in further research in an effort to see food security.
PENERAPAN PETA KENDALI T^2 HOTELLING ALGORITMA FAST MINIMUM COVARIANCE DETERMINANT PADA PENGENDALIAN KUALITAS BAWANG MERAH VARIETAS LEMBAH PALU Puja Lestari Marulu; Junaidi Junaidi; Fadjryani Fadjryani
Jambura Journal of Probability and Statistics Vol 3, No 2 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i2.15522

Abstract

The physical condition of the Palu Valley shallots variety greatly affects the quality of the fried onions that are obtained. The poor quality of shallots will affect the product that will sale by the farmers. Therefore, it is necessary to monitor by conducting the quality control analysis of the physical condition of shallots. In this study we use the quality control method of the  Hotelling control map with the fast-MCD algorithm. This method is used because the outlier in the data to be analyzed. The purpose of this study is to produce average vector estimates and variance-covariance matrix estimates in the formation of the  Hotelling control map. From the calculation by using the mean vector and the variant-covariant matrix with fast-MCD estimation, 93 data were obtained that experienced out of control on the  Hotelling control map with the fast-MCD algorithm where the observations that experienced out of control were more than the usual of  Hotelling control map. This shows that the  Hotelling control map with the fast-MCD algorithm is more effective in detecting observations which contain outliers. The value of the multivariate  process capability analysis is less than one showing the process is uncapable.
APLIKASI METODE SINGULAR SPECTRUM ANALYSIS (SSA) PADA PERAMALAN CURAH HUJAN DI PROVINSI GORONTALO Eka Purnama
Jambura Journal of Probability and Statistics Vol 3, No 2 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i2.16537

Abstract

This paper aims to study the forecasting model of rainfall in Gorontalo Province and forecast it for 2022-2023. Usually, rainfall data is seasonal. In this study, we used Singular Spectrum Analysis (SSA) with the Linear Recurrent Formula (LRF) method. The result showed that the models of rainfall forecasting in Gorontalo using SSA with windows lengthL=36 obtained MAPE of forecasting in out-sample was 0,029 or 2,9 %. So that SSA was very accurate in forecasting rainfall in Gorontalo Province in 2022-2023. The forecasting result showed that rainfall was relatively high generally. So, it is necessary for the government to take policies to avoid the negative impact that can be caused.
ANALISIS SENTIMEN MASYARAKAT PADA KEBIJAKAN VAKSINASI COVID-19 DI TWITTER MENGGUNAKAN METODE MESIN VEKTOR PENDUKUNG DENGAN KERNEL RADIAL BASIS FUNCTION BERBASIS FITUR LEKSIKON Sri Mulyani; Sri Astuti Thamrin; Siswanto Siswanto
Jambura Journal of Probability and Statistics Vol 3, No 2 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i2.16663

Abstract

Twitter is one of the popular social media used to get news quickly and briefly. After the outbreak of the COVID-19 virus and the government's policy to vaccinate against COVID-19 in Indonesia, more and more public opinion has been expressed through tweets. This makes the topic of COVID-19 vaccination interesting for sentiment analysis. Through sentiment analysis, information in the form of text data can be extracted to classify information related to positive or negative opinions. In this study, the classification of public opinion on COVID-19 vaccination was carried out using the supporting vector machine method without and with lexicon-based features. The manual labeling data used were 2981 tweets. The results of the classification of public opinion on COVID-19 vaccination in Indonesia with a supporting vector machine without the lexicon feature obtained accuracy, g-mean and AUC of 83%, 50% and 61.35%, respectively. Meanwhile, with lexicon-based features, the performance of the supporting vector machine method for classifying public opinion on COVID-19 vaccination in Indonesia obtained accuracy, g-mean and AUC of 90%, 86.63% and 87%, respectively. Based on these results, the performance of the supporting vector machine method with lexicon-based features provides better results for the performance of classifying of public opinion on COVID-19 vaccination compared to supporting vector machines without lexicon-based features.
THE OPERATING CHARACTERISTICS CURVE OF THE ACCEPTANCE SAMPLING OF TYPE-A BASED ON OUTGOING PERCENT DEFECTIVE LOT Bahagia Rafika Dewi; Fergyanto E Gunawan; Firdaus Alamsjah
Jambura Journal of Probability and Statistics Vol 3, No 2 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i2.15965

Abstract

The common type-A of Operating Characteristics (OC) curve measures the consumer’s risk through the incoming quality. However, the proportion of defective can alter after the sampling process; hence, the measure of consumer’s risk is better described by the outgoing quality or lot quality of post sampling inspection. A modified OC curve is developed based on the outgoing quality for two applicable cases; returned samples to the lot and non-returned or destructive samples. This research aims to develop the algorithm and evaluate the alternative acceptance sampling plan for isolated lots by outgoing percent defective. For the returned samples, the acceptance sampling requires less sample than that based on the common OC-curve and is seen as an opportunity for sampling size reduction. The number of reduced samples varies depending on the input parameters: Acceptance Quality Level (AQL), Rejectable Quality Limit (RQL), producer’s risk (α), consumer’s risk (β), and lot size (N). For the non-returned sample, more sample size (n) is required, even more than that of using the Binomial distribution’s sample size, which has been considered conservative.

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