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Journal : Xplore: Journal of Statistics

Penerapan Metode Resampling dan K-Nearest Neighbor dalam Memprediksi Keberhasilan Studi Mahasiswa Program Magister IPB Devi Andrian; Agus Mohamad Soleh; Hari Wijayanto
Xplore: Journal of Statistics Vol. 2 No. 1 (2018): 30 Juni 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (653.137 KB) | DOI: 10.29244/xplore.v2i1.79

Abstract

Graduate School IPB (SPs - IPB) has been established for a long time and is believed to produce high quality graduates and highly competitive. However, based on existing data recaps, there are a small number of students who did not graduate, either resigned or Drop Out (DO). It needs to be handled by conducting a selection process for prospective students based on the profile and educational background S1. One of them by applying the method of classification K - Nearest Neighbor (KNN). The response variable used is the success status of the study of prospective students, ie graduated and not graduated. While the explanatory variables used are the profiles and educational background of prospective students. There is an imbalance of data in the data obtained, where the class does not pass much less than the passing class. This can reduce the value of classification accuracy in minority class (sensitivity). So that the handling of data imbalance by using resampling method, either in the form of Random Over Sampling (ROS), Random Under Sampling (RUS), and Random Over-Under Sampling (ROUS). The result of comparison of evaluation result of KNN classification by using k = 1 to 6, resulted in greater sensitivity value when accompanied by the process of handling the data imbalance than without the process of handling the data imbalance, although the accuracy and specificity value becomes smaller. The greatest sensitivity value was obtained when applying the KNN classification method with k = 1, accompanied by the handling of data imbalance by the RUS method, with the mean and median sensitivity values of 0.89 and 0.90, respectively.
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.
Analisis Tingkat Kepuasan Pelanggan dan Loyalitas Pelanggan terhadap Cafe Infinity Coffee Muhammad Nuruddin Prathama; Muhammad Nur Aidi; Agus Mohamad Soleh
Xplore: Journal of Statistics Vol. 11 No. 2 (2022):
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (283.025 KB) | DOI: 10.29244/xplore.v11i2.898

Abstract

Cafe and restaurant businesses are some of the most competitive businesses and have a sizeable market in Jakarta. In this case, the restaurant owner must know the wishes and preferences of the buyer. This research was conducted in one of the cafes in Jakarta "Infinity coffee", this study was conducted to identify consumer characteristics, customer satisfaction, and consumer loyalty. Applying customer satisfaction analysis in the Infinity coffee business can increase understanding of what Infinity coffee consumers want and improve the quality of Infinity coffee services based on research’s results. The analytical methods used in this study are descriptive analysis, Important Performance Analysis (IPA), and the Consumer Satisfaction Index (CSI) as well as correspondence analysis. The results of this study indicate that the entire Infinity coffee service satisfaction index for all aspects is above 80%, which means that the value is included in the satisfied category. However, the IPA scatter diagram shows that there are attributes with a high level of importance that need to be improved in terms of service quality. One of the most important attributes that become a priority for improvement is the attribute of completeness of supporting facilities and adequate cutlery. The Method that used was proven to be successful in examine level of consumer satisfaction also to know more about the characteristic of the consumer.