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Akbar Rizki
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Xplore: Journal of Statistics
Published by Institut Pertanian Bogor
ISSN : 23025751     EISSN : 26552744     DOI : https://doi.org/10.29244/xplore
Core Subject : Science, Education, Engineering,
Decision Sciences, Operations Research & Management Engineering Mathematics
Xplore: Journal of Statistics diterbitkan berkala 3 (tiga) kali dalam setahun yang memuat tulisan ilmiah yang berhubungan dengan bidang statistika. Artikel yang dimuat berupa hasil penelitian atau kajian pustaka dalam bidang statistika dan atau penerapannya. ISSN: 2302-5751 Mulai Desember 2018, Xplore: Journal of Statistics mendapatkan ISSN baru untuk media online (eISSN:2655-2744) sesuai dengan SK no. 0005.26552744/JI.3.1/SK.ISSN/2018.12 - 13 Desember 2018. Maka sesuai ketentuan pada SK tersebut, edisi Xplore: Journal of Statistics mulai Desember 2018 akan dimulai menjadi Volume 7 dan No 3. eISSN: 2655-2744
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 7 Documents
 1 
Search results for , issue "Vol. 10 No. 3 (2021)" : 7 Documents clear
Evaluasi Faktor yang Memengaruhi Usability Aplikasi Thymun Menggunakan Structural Equation Model-Partial Least Square Rahma Dany Asyifa; Agus M Soleh; Bagus Sartono
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (906.115 KB) | DOI: 10.29244/xplore.v10i3.743

Abstract

Application development must be done by considering the usability factor of the application. Three aspects of usability measurement, namely usefulness, satisfaction, and ease of use, are latent variables that cannot be measured directly, so the appropriate analysis is the Structural Equation Model-Partial Least Square (SEM-PLS). PLS is a SEM analysis approach that does not require assumptions of data distribution and a minimum number of observations. The measurement of the usability of the Thymun application is described in two SEM-PLS models. This study aims to determine the best model and determine the effect of usefulness, satisfaction, and ease of use on the usability of the Thymun application. The data used is survey data to 44 Thymun application users. The sampling technique used was purposive sampling. The results showed that the best model has a good measure with an R-square value of 0.730 and Q2 0.453 with a Goodness of Fit 0.736. The variables of usefulness and ease of use have a significant effect on the 5% real level with path coefficient values ​​of 0.255 and 0.636. While the satisfaction variable does not have a significant effect on the 5% real level with a path coefficient of 0.058. Thymun application usability score is 76.47.
Pemodelan dengan Geographically Weighted Negative Binomial Regression (Studi kasus: Banyaknya Penderita Kusta di Jawa Barat) Khusnul Khotimah; Itasia Dina Sulvianti; Pika Silvianti
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (805.227 KB) | DOI: 10.29244/xplore.v10i3.833

Abstract

The number of leper in West Java is an example of the count data case. The analyzes commonly used in count data is Poisson regression. This research will determine the variables that influence the number of leper in West Java. The data used is the number of leper in West Java in 2019. This data has an overdispersion condition and spatial heterogenity. To handle overdispersion, the negative binomial regression model can be employed. While spatial heterogenity is overcome by adding adaptive bisquare kernel weight. This research resulted Geographically Weighted Negative Binomial Regression (GWNBR) with a weighting adaptive bisquare kernel classifies regency/city in West Java into ten groups based on the variables that sigfinicantly influence the number of leper. In general, the variable in the percentage of households with Clean and Healthy Behavior (PHBS) has a significant effect in all regency/city in West Java. Especially for Bogor Regency, Depok City, Bogor City, and Pangandaran Regency, the variable of the percentage of people poverty does not have a significant effect on the number leper.
Penggerombolan Sekolah pada Penerimaan Mahasiswa Baru Jalur SNMPTN di IPB Menggunakan Metode Two-Step Cluster Ni Kadek Manik Dewantari; Utami Dyah Syafitri; Aam Alamudi
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (246.624 KB) | DOI: 10.29244/xplore.v10i3.834

Abstract

New student admissions are opened in three pathways including SNMPTN, SBMPTN, and Seleksi Mandiri. In order to improve the SNMPTN selection system at IPB, a study was conducted on the quality of SMA/MA which registered to IPB through school clustering. In general, cluster analysis cannot handle large and mixed-type data, so this school clustering used the Two-Step Cluster method with two alternatives, namely without handling outliers and handling 5 percent outliers. Both of these alternatives produced an average Silhouette coefficient value of 0.2 and 0.3 respectively, which was still under the good category. However, clustering without handling outliers resulted in more detailed cluster criteria with 4 optimal clusters. The criteria for these four clusters include, Cluster 1 is a category of Low Commitment, Low Quality, and Low Consistency schools, Cluster 2 and 3 are categories of schools that have special criteria in certain categories, and Cluster 4 is a category of High Commitment, High Quality, and High Consistency.
Latent Dirichlet Allocation dalam Identifikasi Respon Masyarakat Indonesia Terhadap Covid-19 Tahun 2020-2021 Karel Fauzan Hakim; Pika Silvianti; Agus Mohamad Soleh
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (298.682 KB) | DOI: 10.29244/xplore.v10i3.836

Abstract

Covid-19 is a very troubling disease in Indonesia. Therefore, understanding public opinion is required to find solutions and evaluate the government performance in handling the pandemic. Twitter can be helpful to identify the public opinion of significant events. Twitter’s tweet is a large dimension text-based big data. It requires text sampling and text mining to be processed efficiently and effectively. Stratified random sampling with 20 repetitions applied to assume days as strata followed by topic modeling with latent Dirichlet allocation (LDA). This research aims to find out public opinion regarding Covid-19 and itsgrowth over time. Other than that, this research also aims to find out sampling effects on tweet data using stratified random sampling. Therefore, the extracted topics will be transformed into time-series data and considering the variety of the pattern made. Afterward, the transformation results will be explored and interpreted. This research suggests that discussions related to Covid-19 are divided into four topics by the first model, namely: “Vaccine”, “Positive or affected people”, “Health protocol”, and “Indonesia” then nine topics by the second model, namely: “Vaccine”, “Prayer”, “Health protocol”, “Social aid and corruption”, “Affected people”, “Indonesian economy”, “Work”, “Persuading to wear mask”, and “Willing to watch”. Furthermore, some topics peak whenever a significant event occurs in Indonesia. Afterward, this research suggests that 20 repetitions of stratified random sampling could provide good results.
Identifikasi Faktor-faktor yang Memengaruhi Hasil Akreditasi SMA di Indonesia Berdasarkan Data ARKAS Muh Nur Fiqri Adham; Budi Susetyo; Kusman Sadik; Satriyo Wibowo
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (540.898 KB) | DOI: 10.29244/xplore.v10i3.837

Abstract

Accreditation is an indicator of the quality of education at the education unit level. One affects the quality of education units is the school budget. School budgets are prepared in order to fulfill 8 national education standards. School budget management uses School Activity Plan and Budget Application (ARKAS) developed by the Ministry of Education, Culture, Research and Technology (Kemendikbudristek). ARKAS is an information system for managing school budget and expenditure planning. The Research is identifies the factors that influence the accreditation of high school (SMA) with accreditation as a response variable and 17 explanatory variables sourced from ARKAS and Dapodik data using ordinal logistic regression analysis. The best model stage is the model formed that has the smallest AIC value and has high model accuracy in determining the best model. The best model stage is the third model stage which is composed of 7 explanatory variables that affect the high school accreditation rating with AIC value of 1886,20 and model accuracy of 65,79%. The variables that affect to results of accreditation include school status, percentage of students eligible PIP, ratio of the number of students per number of teachers, percentage of teachers certified educators, ratio of the number of students per number of study groups, ratio of the number of students per number of computers, and ratio of the number of students per number of toilets
Penggerombolan Mutu SMA/MA per Provinsi Berdasarkan Hasil Akreditasi Menggunakan Metode Fuzzy C-Means Rifannisa Bahar; Pika Silvianti; Budi Susetyo
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (482.328 KB) | DOI: 10.29244/xplore.v10i3.842

Abstract

Mapping the quality of education in Indonesia needs to be studied so that the provincial government, as the institution responsible for secondary education management policies, can more easily determine priorities and what actions will be taken to improve the quality of education in Indonesia. One of the analytical methods that can be used to map the quality of education is fuzzy c-means. This research aims to classify the quality maps of provinces in Indonesia based on the results of SHS/MA accreditation using the fuzzy c-means method. The fuzzy c-means method can show the probability of objects entering a cluster with a degree of membership. The optimum cluster sizes obtained were 2 and 3. The final solution with cluster size 2 was 12 provinces categorized in cluster 1 and 22 provinces categorized in cluster 2. Clustering with cluster size 3 resulted in cluster 1 consisting of 11 provinces, cluster 2 consisting of 16 provinces, and cluster 3, which consists of 7 provinces. The main character of cluster 1 is a high national education standard score, while the main character of cluster 2 is a low national education standard score. Then the main character of group 3 is the national standard score, whose value is around the national average.
Perbandingan ARIMA dan Artificial Neural Networks dalam Peramalan Jumlah Positif Covid-19 Di DKI Jakarta Tri Wahyuni; Indahwati Indahwati; Kusman Sadik
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (425.867 KB) | DOI: 10.29244/xplore.v10i3.846

Abstract

DKI Jakarta is the center of the spread of Covid-19. This is indicated by the higher cumulative number of Covid-19 positive in DKI Jakarta compared to other provinces. The high number of cases in DKI Jakarta is a concern for all groups, so it is necessary to do forecasting to predict the number of Covid-19 positive in the next period. Accurate forecasting is needed to get better results. This study compares the Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN) methods in predicting the number of Covid-19 positive in DKI Jakarta. Forecasting accuracy is calculated using the value of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and correlation. The results show that the best model for forecasting the number of Covid-19 positive in DKI Jakarta is ARIMA(0,1,1) with drift, with a MAPE value of 15.748, an RMSE of 268.808, and the correlation between the forecast value and the actual value of 0.845. Forecasting using ARIMA(0,1,1) with drift and BP(3,10,1) models produces the best forecast for the long forecasting period of the next six weeks.

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