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Identifying the Characteristics of Pregnant Women with Inflammation/Infection in Indonesia Muhammad Nur Aidi; Efriwati Efriwati; Santy Suryanty; La Ode Abdul Rahman; Khalilah Nurfadilah; Fitrah Ernawati
Jurnal Gizi dan Pangan Vol. 17 No. 3 (2022)
Publisher : Food and Nutrition Society of Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (406.816 KB) | DOI: 10.25182/jgp.2022.17.3.177-186

Abstract

Infection in pregnant women is common and one of the highest causes of death in Indonesia. Reducing infection conditions through early infection prevention needs to be done, one of which is by knowing the characteristics that contribute to the incidence of infection in pregnant women in Indonesia. This study used the Classification and Regression Tree (CART) method to determine the pregnant women with infections and not infections characteristics and classify them. The results of the CART analysis found that seven variables contributed to separating infected and not-infected status in pregnant women, they are nutritional status based on Body Mass Index (BMI), history of anemia, pregnancy distance, Chronic Energy Deficiency (CED) status, ages, socioeconomic and gestational age. Characteristics of the highest incidence of infection, namely 79%, occurred in the group of pregnant women with overweight – obese (BMI>25.0), anemia and pregnancy distance <3 years. The classification analysis of the CART method in this study resulted in the accuracy of identification performance which was still not good, with an accuracy value of 52.78%. It is necessary analysis with other classification methods such as the Chi-square Automatic Interaction Detection (CHAID) in the future.
Evaluation of Bicluster Analysis Results in Capture Fisheries Using the BCBimax Algorithm Cynthia Wulandari; I Made Sumertajaya; Muhammad Nur Aidi
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.15457

Abstract

Biclustering is a simultaneous clustering technique by finding sub-matrixes that have the same similarity between rows and columns. One of the biclustering algorithms that is relatively fast and can be used as a reference for the comparison of several algorithms is the BCBimax algorithm. The BCBimax algorithm works by finding a sub-matrix containing element 1 of the formed binary data matrix. The selection of thresholds in the binarization process and the minimum combination of rows and columns are essential in finding the optimal bicluster. Capture fisheries have an important role in supporting sustainable growth in Indonesia, so information on the potential of fish species that have similarities in several provinces is needed in optimally mapping the potential. The BCBimax algorithm found 11 optimal biclusters in grouping capture fisheries data. The median of each variable is used as a threshold in the binarization process, and the minimum combination of row 2 and maximum column 2 is chosen to find the optimal bicluster result. The optimal average value of Mean Square Residual bicluster obtained is 0.405403 with the similarity of bicluster results (Liu and Wang index) which is different for each bicluster combination produced. All the bicluster results grouped the provinces and types of fish that had the same potential simultaneously.
Penerapan Teknik Prapemrosesan Smoothing Spline pada Data Hasil Pengukuran Alat Pemantau Kadar Glukosa Darah Non-Invasif Putu Gita Karlina Jayanti; Rahma Anisa; Muhammad Nur Aidi; . Erfiani
Xplore: Journal of Statistics Vol. 2 No. 2 (2018): 31 Agustus 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (393.635 KB) | DOI: 10.29244/xplore.v2i2.90

Abstract

A non-invasive blood glucose monitoring device is performed without injuring the limbs. One method of measurement in the form of qualitative and relatively simple to use because the process is fast and requires a cheap cost, namely Fourier Transform Infrared (FTIR). Spectroscopic results allow for a shifting of the scatter, since the same object is measured several times incorrectly producing the same spectrum, requiring a preprocessing method to reduce the problem. However, in some cases it is difficult to identify the existing data pattern, so that a nonparametric approach is needed to identify the pattern of data held so that in the process of calibration model obtained accurate results. Smoothing Spline is one nonparametric method is piecewise polynomial, which is a piece of polynomial that has a segmented property on the hose k that formed at knot points, thus providing flexibility in constructing the shape of the curve that we have. The Smoothing Spline method produces an optimum value when the GCV value is minimum on the use of a linear order with sixteen knot points. The resulting varians value after Smoothing Spline method is smaller than before smoothing, this indicates that this method can minimize the effect of liquefaction in the non-invasive blood glucose value spectrum. In addition, Smoothing Spline method can also capture data patterns well.
Kajian Simulasi Perbandingan Interpolasi Tetangga Terdekat dan 2-Tetangga Terdekat pada Sebaran Titik Spasial Retno Ariyanti Pratiwi; Muhammad Nur Aidi; Anik Djuraidah
Xplore: Journal of Statistics Vol. 2 No. 2 (2018): 31 Agustus 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (342.431 KB) | DOI: 10.29244/xplore.v2i2.106

Abstract

Spatial point distribution in an area has three types of pattern. They are random, regular, and cluster. A set of points in space is an information about the number of events in that particular space. Oftenly, the number of events in a space is difficult to obtain, thus number of events estimation is necessary in order to conduct analysis and generate the right conclusion. This research uses nearest neighbor and 2- nearest neighbors interpolation as an interpolation methods under the principle of the object location proximity. The accuracy measurements were used in both methods can be computed by the smallest MAE values. MAE is a measure to evaluate the level of accuracy by using the absolute mean of the observed and interpolation expected value difference. This research uses MAE to determine the best method. This research uses both simulated and real-life data regarding the number of Dengue Hemorrhagic Fever (DBD) patient in Central Java Province. Simulated data were generated from the Poisson, binomial, and negative binomial distribution which were set in the quadrant. The results show that the 2-nearest neighbors interpolation yield smaller MAE value than the nearest neighbor interpolation MAE either in the random, regular, or cluster spatial point distribution. The percentage of bias of the observation and estimation value of the two interpolation methods are relatively small or less than 20%. Meanwhile, in the real-life data, the 2-nearest neighbors interpolation also yield a smaller MAE value than the nearest neighbor interpolation.
Penanganan Overdispersi pada Regresi Poisson dengan Regresi Binomial Negatif pada Kasus Kemiskinan di Indonesia Lulu Mahdiyah Sandjadirja; Muhammad Nur Aidi; Akbar Rizki
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.v8i1.165

Abstract

Poisson regression can be used to model rare events that consist of count data. Poisson regression application is carried out to find out external factors that affect the number of poor people in Indonesia by the province in 2016. The assumptions that must be met in this analysis are equdispersion. However, in real cases there is often a problem of overdispersion, ie the value of the variance is greater than the average value. High diversity can be caused by outliers. Expenditures on outliers have not been able to deal with the problem of overdispersion in Poisson Regression. One way to overcome this problem is to replace the Poisson distribution assumption with the Negative Binomial distribution. The results of the analysis show that the Negative Binomial Regression model without outliers is better than the Poisson Regression without outliers model indicated by a smaller AIC value. Based on the Negative Binomial Regression model without this outlier the external factors that affect the number of poor people in Indonesia by the province in 2016 are the percentage of households with floor conditions of houses with soil by province, population by province, percentage of unemployment to the total workforce by province and the percentage of the workforce against the working age population.
Analisis Faktor-Faktor yang Mempengaruhi Prestasi Mahasiswa Departemen Statistika IPB menggunakan Metode SEM-PLS Zunita Sari; Muhammad Nur Aidi; La Ode Abdul Rahman
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.v8i1.201

Abstract

Education is improving human power. Education is divided into three level namely primary, secondary and high level education. High level education can be obtained from University. University as one of high level education, is a formal education place for all studying and teaching activities, research, community service and develop scientific student to become qualified workforce. Student achievement in universities is influenced by various factors that cannot be measured both direct and indirect. The method that is used to determine those factors is structural equation modeling (PPS) with partial least square (PLS) method. PPS with PLS method used when there are some assumptions on diverse PPS which is not fullfiled, like binormal distribution and the big ammount of examples. The results showed that the six exogenous latent variables (family background, motivation, environment, visual learning style, auditory learning style, and kinesthetic learning style) did not have a significant influence on endogenous variables (student achievement). The model used in this study has a R2 value 14.1%. This values ​​indicates that the model built is still weak in explaining the diversity of student achievement.
Analisis Korelasi Kanonik pada Parameter Kualitas Fisik dan Parameter Kualitas Kimia Air Sungai Ciliwung Nadya Amelia Dewi Suryana; Itasia Dina Sulvianti; Muhammad Nur Aidi
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (664.154 KB) | DOI: 10.29244/xplore.v10i2.245

Abstract

Water is an important factor in fulfilling the needs of living things, therefore the water that is used must be free from bacterias and do not contain any toxic substances. The most common water source comes from the river. Ciliwung River as one of the main rivers used for drinking, household needs, industrial needs, and transportation must have good water quality. Therefore, the Ciliwung River water quality needed to be known. The water quality is measured based on the parameters such as the physical water quality and the chemical water quality. The measurement of those parameters are classified to be complicated as it measured by laboratorium research, so that the identification of the chemical water quality parameter could be done through the physical water quality that is easier and simpler to be measured. This study aims to determine the variable of the physical water parameters that can be used to identify the chemical water quality parameters, so that the water quality of the Ciliwung River can be known in a simpler way. Statistical method that can be used to see the relationship between the two variable groups is the canonical correlation analysis. Canonical correlation analysis is a method in multiple variable analysis used to investigate the relationship of two groups of variables using the linear combination principle of the two variables. Based on the results of the canonical correlation analysis, it can be concluded that there is a relationship between the physical quality of water and the chemical quality of water. The correlation exists between the variables of physical quality of water, which are the water temperature and the content of suspended substances in water, with the variables of chemical quality of water, namely groups of metals (manganese levels in water and iron content in water) and groups of acid (the level of deep phosphate in water, the level of sulfate in water, the level of nitrite in water, and the level of nitrate in water). The relationship between the physical quality of water is positive between the temperature of water and the chemical quality of water whereas negative between the levels of suspended substances in water and the chemical quality of water.
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.
Perbandingan CART dan SMOTE CART dalam Mengklasifikasikan Kebutuhan KB Tidak Terpenuhi di Indonesia Ulfa Afilia Shofa; Muhammad Nur Aidi; Budi Susetyo
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 (582.121 KB) | DOI: 10.29244/xplore.v11i2.917

Abstract

Indonesia is ranked fourth in the world as the country with the largest population. The high population growth in Indonesia can cause problems in several fields. The government seeks to suppress the rate of population growth through the Family Planning (KB) program. In Indonesia, the number of unmet needs for family planning is still relatively high and has not yet reached the BKKBN target. Therefore, it is necessary to identify the characteristics of unmet need for family planning among married women or living with partner. This study used the Classification and Regression Trees (CART) method. This study handling unbalanced data by Synthetic Minority Oversampling Technique (SMOTE). This study aims to compare the performance of the CART and SMOTE CART classification methods in classifying unmet need for family planning and to identify the characteristics of unmet need for family planning among married women or living with partner in Indonesia. The SMOTE CART model has better performance than the CART model, with the percentages of balanced accuracy, sensitivity, and specificity being respectively 54.83%, 34.96%, and 74.70%. In general, the characteristics of unmet need for family planning among married women or living with partner in Indonesia are having 1-4 living children, not getting information from mass media, not accessing the internet in the last month, having a primary or secondary education level, a husband with no education or with a primary or secondary education level, and aged more than 30 years old.     Keywords: CART, SMOTE CART, unmet need for family planning
Influencing factors for the human development index in West Java using geographically and temporally weighted regression kernel functions Anis Dyah Rahmawati; Aji Hamim Wigena; Muhammad Nur Aidi
Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi Vol 28, No 2 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um017v28i22023p228-241

Abstract

Human Development Index (HDI) is a competitive index that serves as one of the crucial metrics for evaluating the effectiveness of enhancing the quality of human resources. HDI values from different areas can be compared. This study aims to spatially and temporally explore the HDI data from districts or cities in West Java and examine the factors that influence HDI in each of these districts or cities using the GTWR Great Circle Distance Fixed Kernels model. In this study, we used a combination of cross-sectional data from districts or cities in West Java and time series data with seven annual periods from 2015-2021. The GTWR Great Circle Distance Fixed Kernels model was expected to display coefficient values at each location and time simultaneously, providing more in-depth information and analysis results at each location and time. The analysis results using the GTWR Great Circle Distance Fixed Kernels model show that HDI in West Java carries a positive influence on the location and time. This finding should be of particular concern to the relevant government, particularly the factors presenting a natural effect on HDI based on location and time. The positive influence obtained by an area at a particular time will also have a positive impact on other regions, and if there is a negative influence, it will undoubtedly affect other regions as well. Analysis of the HDI model in West Java using the GTWR Great Circle Distance Fixed Exponential Kernel model also presents better results in comparison to the Global OLS model and the GTWR model without the Great Circle Fixed Exponential Kernel. The final parameter estimator results are displayed in the form of a geographic map to facilitate ease of understanding.