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Journal : Xplore: Journal of Statistics

Dekomposisi Ensemble untuk Peramalan Harga Bawang Merah DKI Jakarta Febie Tri Lestari; Farit Mochamad Afendi; Mohammad Masjkur; Budi Waryanto
Xplore: Journal of Statistics Vol. 8 No. 1 (2019): 30 April 2019
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v8i1.120

Abstract

Onions are one of the vegetable commodities that are not distributed and included as seasonal crops. Onions are commonly used as cooking spices and traditional medicine. At the time of the religious holidays or non-harvest season, the stock of onions is not able to meet the demand, hence the government has to import them, but that increase the fluctuations of onion prices on the market. Actually, by utilizing the price fluctuation, information about the factors, will be obtained by reviewing the price movement and precise forecasting of the price of onions. Ensamble Empirical Mode Decomposition (EEMD) method can be applied to examine that. EEMD is a decomposition method that can be used to convert a series of time functions from a data signal into several sub-signals resulting from flattening, otherwise known as Intrinsic Mode Function (IMF) and IMF remaining. In this research, this concept applied to data on weekly onion prices in DKI Jakarta from July 2008 to April 2018 as many as 521 data. Based on the results of data processing, as many as 7 IMF and IMF remaining were used as IMF forecasting and the IMF remaining in the future. The forecast was performed by choosing the best model of each IMF component and IMF remaining, used ARIMA. In the end, the weekly price forecast for onion in Jakarta from May - July 2018 ranged from Rp34295.67, - to Rp36133.36, - with average forecasting prices for May-July 2018 amounting to Rp34482.39 - Rp 35207.12 and Rp 36024.88 with a MAPE value of 1.85%.
Perbandingan Metode Koreksi Pencaran pada Data Hasil Alat Pemantau Kadar Glukosa Darah Non-Invasif Siti Raudlah; Mohammad Masjkur; Kusman Sadik; . Erfiani
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.127

Abstract

Scatter correction is one of the methods in data preprocessing that aim at eliminating the physical properties of the spectrum and reducing the variance between samples. The most commonly methods of scatter correction used are the Multiplicative Scatter Correction (MSC) and Standard Normal Variate (SNV) methods. The MSC method corrects the spectrum by utilizing the results of simple linear regression parameter estimation. The SNV method performs spectral correction with the median and standard deviation. Another alternative method of scatter correction is the Orthogonal Scatter Correction (OSC) applying the principle of orthogonality. The methods used in this research were MSC, SNV, and OSC methods in order to correct the result data of non-invasive blood glucose measuring instrument. The result of this research showed that the time domain spectrum data and intensity had different amount so that the summarized data was needed. Furthermore, this research found that the OSC method with the five series of statistics gained a good correction result compared to the other methods. The OSC method produced a smaller average value of the variance than the other methods.
Penerapan SMOTE dalam Pemodelan CHAID pada Data Keberhasilan Mahasiswa PPKU IPB Ririn Fara Afriani; Mohammad Masjkur; Utami Dyah Syafitri
Xplore: Journal of Statistics Vol. 8 No. 1 (2019): 30 April 2019
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v8i1.154

Abstract

Bogor Agricultural University (IPB) as the third rank of Indonesian non polytechnic universities in 2017 requires new students to join the General Competency Education Program (PPKU) for two semesters to improve the quality of human resources. Student achievement success can be determine from the student's academic status, where the student's academic status is divided into two, which are Drop Out (DO) and not DO. Only 1% of PPKU students who are drop out.. This means there is a data imbalance. One of the method used to handled that is Synthetic Minority Oversampling Technique (SMOTE) method. Classification analysis used is the Chi-Square Automatic Interaction Detection (CHAID) method to identify the factors that influence the success of PPKU students. The application of SMOTE to the 2016/2017 PPKU student data was able to improve the ability of classification trees with the average values ​​of accuracy, sensitivity, and specificity to 0.718, 0.575, and 0.72. The factors that influence the success of IPB's PPKU students are the entry point, gender, and regional origin.
Penerapan Structural Equation Modelling-Partial Least Squares pada Faktor Kemiskinan di Jawa Tengah Arini Annisa Adi; Mohammad Masjkur; Erfiani Erfiani
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 (313.609 KB) | DOI: 10.29244/xplore.v11i2.875

Abstract

The number of poverty-stricken people in Central Java in March 2020 was 3.98 million people (11.41%), the second-largest in Java. The approximately high number of poverty-stricken people is a priority for the government to reduce poverty. One of the solutions to reduce poverty is knowing the factors that may affect it. The purpose of this study is to identify the factors that affected poverty in Central Java using the Structural Equation Modeling-Partial Least Squares (SEM-PLS) method. This study used data from districts/ cities in Central Java in 2020. In this case, there is one exogenous latent variable for health and three endogenous latent variables for poverty, economy, and human resources. The problem encountered that the observed data is relatively small, specifically for 35 observations and the data distribution is suspected not fulfilled the normal assumptions. In conclusion, the appropriate analysis used in this study is Structural Equation Modeling-Partial Least Squares (SEM-PLS). The results showed that the economic latent variable had a positive but not significant effect on the latent variable of poverty, Human Resources also had a positive but not significant effect, while the latent health variable had a negative and significant effect on the latent variable of poverty. The Q2 value for the latent variable of poverty is 0.333, this shows that 33.3% of the diversity of the latent variable of poverty can be explained by the latent variables of economy, health, and human resources.
IDENTIFIKASI FAKTOR-FAKTOR YANG MEMENGARUHI PRESTASI MAHASISWA PROGRAM SARJANA DI INSTITUT PERTANIAN BOGOR MENGGUNAKAN METODE CHAID Ragsa Endahas Ahmad; Akbar Rizki; Mohammad Masjkur
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 (166.684 KB) | DOI: 10.29244/xplore.v11i2.887

Abstract

IPB University (IPB) is one of the best universities in Indonesia, based on the Ministry of Education and Culture (Kemendikbud) clustering in 2020. As the best university, IPB requires efforts to improve the quality of its education. One of these efforts is to improve student achievement. This study aims to identify the factors that influence the competition and non-competition achievements of undergraduate students at IPB. The data used are achievement data (academic year 2016/2017 to 2020/2021) from the Directorate of Student Affairs and Career Development (Ditmawa) of IPB and demographic data of undergraduate level IPB students (entry year 2016/2017 to 2019/2020) from the Directorate of Administration and Education (Dit-Ap) IPB. The analytical method used in this study is the Chi-square Automatic Interaction Detection (CHAID) classification method. There was an imbalance of data on the Student Achievement response variable. Therefore, in this study, unbalanced data handling was also carried out by resampling in the form of oversampling, undersampling, and over-undersampling methods. The results showed that the classification using CHAID analysis with resampling in the form of oversampling with a balance accuracy of 73.7% resulted in the best classification performance. The factors that influence student achievement are 11 variables, and the 3 most influential variables are variables of year of admission, department, and last GPA.
Survei dan Identifikasi Faktor Awareness Mahasiswa IPB Terhadap Perilaku Pelecehan Seksual dan Kekerasan Menggunakan Regresi Logistik Biner Ibrahim Arif Muhammad; Rahma Anisa; Mohammad Masjkur
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 (568.797 KB) | DOI: 10.29244/xplore.v11i2.939

Abstract

The lack of public awareness of sexual harassment as well as physical and verbal abuse are still occurring frequently and becoming a concern in everyday life, especially for women. Sexual harassment is an unwanted behavior or attention from a perpetrator with sexual intentions that disturbs the victim(s). Abuse is a form of one person's action against another party that results in pain and changes both physically and psychologically. The purpose of this study is identifying the number of IPB University students that are aware on the act of sexual harassment and abuse, identifying factors that can affect awareness about it using binary logistic regression, and providing recommendations on how to increase the awareness of it. Majority of the respondents have awareness on both the act of sexual harassment and abuse, whether they have done it or not. In the logistic regression, gender and financial background of the respondents were significant factors of awareness in the act of sexual harassment, whereas in awareness of the abusive behavior, the respondents’ gender, hometown, the time amount of social media usage per day, financial background, and experience of being a victim of it factor significantly. Majority of the respondents suggest that education from various sources should be improved in order to raise awareness to the public.
Analisis Gerombol Pautan Ward Kabupaten/Kota di Provinsi Jawa Timur Berdasarkan Indikator Kesejahteraan Rakyat annida marsa salsabila; Mohammad Masjkur; Indahwati
Xplore: Journal of Statistics Vol. 11 No. 3 (2022): Vol. 11 No. 3 (2022)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.711 KB) | DOI: 10.29244/xplore.v11i3.1024

Abstract

The main goal in the development of a country is to improve the welfare ofthepeople. One of the causes of the problems of people's welfare in Indonesia is that thedevelopment carried out by the government is not carried out evenly and not on target,not least in East Java Province. to group and look at the characteristics of 38regencies/cities in East Java Province based on people's welfare indicators sothat thegovernment in making policies can be evenly distributed and on target. Thisstudy useshierarchical cluster analysis. The data used is the welfare indicator data for 38districts/cities of East Java Province in 2019. The hierarchical cluster analysismethodused is the Ward method. The results of the study using dendogram cuts and the ratioof standard deviations within clusters and standard deviations betweenclusters showedthat districts/cities in East Java province could be divided into six clusters. In eachcluster, the characteristics are seen using the average value of eachvariable. Areas withvery good development are in cluster six and areas that requiremore development inmany aspects are in cluster five.
Penerapan Bernoulli Naïve Bayes untuk Analisis Sentimen Pengguna Twitter Terhadap Layanan Online Food Delivery di Indonesia Dea Fisyahri Akhilah Putri; Ir. Mohammad Masjkur, M.S.; Indahwati Indahwati
Xplore: Journal of Statistics Vol. 12 No. 1 (2023): Vol. 12 No. 1 (2023)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (738.122 KB) | DOI: 10.29244/xplore.v12i1.1110

Abstract

Online food delivery is one of the drivers of the digital economy that all societies today are interested in. The trend of these services has intensified as changes in people's behavior and lifestyle in the Covid-19 pandemic. The digital platforms of food delivery services in Indonesia are GoFood, ShopeeFood, and GrabFood, present ease in both competitive transactions and multiple options by consumers. Its widespread use of these platforms certainly generates a variety of reviews and public opinion; one is through tweets on Twitter. This study aims to classify the sentiments on the various reviews into the label of positive and negative sentiments using the Bernoulli Naïve Bayes algorithm. The majority of reviews from March 15, 2022 to March 30, 2022 were positive sentiments, which indicated that people gave a positive impression during these online food delivery service. The results of this study show that Bernoulli Naïve Bayes with the feature selection of information gain generates a good performance in classifying sentiment labels based on accuracy scores obtained at 89%, 87%, 86%, and 85% in all data and each online food delivery platform (GoFood, ShopeeFood, and GrabFood).