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STATISTIKA
Published by Universitas Islam Bandung
ISSN : 14115891     EISSN : 25992538     DOI : https://doi.org/10.29313/statistika.v23i1.1628
Core Subject : Science, Education,
Decision Sciences, Operations Research & Management Mathematics
STATISTIKA published by Department of Statistics, Faculty of Mathematics and Natural Sciences, Bandung Islamic University as pouring media and discussion of scientific papers in the field of statistical science and its applications, both in the form of research results, discussion of theory, methodology, computing, and review books. Published biannually in May and November each.
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Articles 91 Documents
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Analisis Variabel yang Menjelaskan Penggunaan Angkutan Umum Trans Semarang Menggunakan Metode Structural Equation Modelling (SEM) Alfino Pramuji Akbar; Nurul Fitriani; Bambang Istiyanto
Statistika Vol. 24 No. 2 (2024): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v24i2.4397

Abstract

ABSTRAK Peningkatan jumlah penduduk turut menyebabkan adanya permasalahan transportasi, seperti kemacetan dan polusi udara. Salah satu upaya yang dapat dilakukan adalah penggunaan angkutan umum. Akan tetapi, minat masyarakat untuk menggunakan angkutan umum masih tergolong rendah, tidak terkecuali dengan masyarakat di Kota Semarang. Padahal, saat ini Pemerintah Kota Semarang telah menyediakan transportasi umum modern yaitu Trans Semarang. Oleh karena itu peneliti bermaksud untuk menganalisis variabel-variabel yang menjelaskan penggunaan Trans Semarang dengan metode Structural Equation Modelling (SEM). Metode SEM memungkinkan mengetahui signifikansi pengaruh antar variabel lebih dari satu variabel bebas maupun terikat. Penelitian menggunakan kepuasan penumpang dan kualitas pelayanan sebagai variabel bebas. Adapun persepsi dan perilaku penumpang menjadi variabel terikat. Hasil penelitian yang dilakukan, menunjukkan bahwa empat variabel penelitian dianggap berpengaruh terhadap penggunaan Trans Semarang. ABSTRACT The increase in population causes transportation problems, such as traffic jams and air pollution. One effort that can be done is use public transport. However, people’s interest to using  public transport is still relatively low, no exception people in Semarang. In fact, currently The Goverment of Semarang has provided modern public transport, that is Trans Semarang. Therefore, the researcher intends to analyze variables that influence of Trans Semarang usage using Structural Equation Modelling (SEM) method. SEM method makes it posible to determine the significance of influence between variables of more than one independent or dependent variable. Research uses passenger satisfaction and service quality as independent variables. Perceptions and passanger behavior are dependent variables. The result of this research showed that four variables are considered to influence using Trans Semarang.
Pendugaan Indikator Rasio Angka Partisipasi Sekolah Anak Disabilitas terhadap Nondisabilitas di Pulau Nusa Tenggara Tahun 2023 Kholiq, Adit; Putri, Afriani Kartika; Simangunsong, Sri Rohmanisa; Dewi, Isnaini Rahma; Nuraini, Fayza Zaki Asmi; Istiana, Nofita
Statistika Vol. 24 No. 2 (2024): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v24i2.4536

Abstract

ABSTRAK Salah satu target dalam tujuan pembangunan berkelanjutan (SDGs) adalah menghapuskan diskriminasi di bidang pendidikan, termasuk bagi penyandang disabilitas. Ukuran yang digunakan pemerintah untuk menilai pencapaian target ini adalah rasio angka partisipasi sekolah (APS) anak penyandang disabilitas terhadap nondisabilitas usia 7 – 17 tahun. Namun, pendugaan langsung menghasilkan standard error yang besar. Tujuan penelitian ini adalah melakukan pendugaan rasio angka partisipasi sekolah anak disabilitas terhadap nondisabilitas berusia 7 – 17 tahun pada tingkat kabupaten/kota di Pulau Nusa Tenggara tahun 2023. Penelitian ini menerapkan metode Small Area Estimation (SAE) dengan pendekatan Hierarchical Bayes (HB). Data penelitian bersumber dari Badan Pusat Statistik. Hasil penelitian ini menunjukkan model SAE-HB menghasilkan pendugaan yang lebih presisi daripada pendugaan langsung pada anak disabilitas. Diketahui pula, rasio angka partisipasi sekolah anak disabilitas terhadap nondisabilitas berusia 7 – 17 tahun di Pulau Nusa Tenggara berada pada rentang 40,47 sampai 78,15 dengan Kabupaten Sumba Barat dan Kabupaten Rote Ndao berstatus perlu perhatian. ABSTRACT One of the targets set out in the Sustainable Development Goals (SDGs) is to eliminate discrimination in education, including for people with disabilities. The measure used to assess the achievement of this target is the ratio of school enrollment rates (APS) of children with disabilities to those without disabilities aged 7-17 years. However, direct estimation results in a large standard error. The objective of this study is to predict the school enrollment ratio of children with disabilities to non-disabled children aged 7-17 years at the district/city level in Nusa Tenggara Island in 2023. This research employs the Small Area Estimation (SAE) method with the Hierarchical Bayes (HB) approach. The research data is sourced from the Badan Pusat Statistik. The findings of this study indicate that the SAE-HB model yields more precise predictions than direct estimation of children with disabilities. Additionally, the school enrollment ratio of children with disabilities to those without disabilitie aged 7-17 years on Nusa Tenggara Island is estimated to be within the range of 40.47 to 78.15, with West Sumba Regency and Rote Ndao Regency identified as requiring attention.
Aplikasi K-Medoid dalam Regenerasi Pemain Sepak Bola Akbar, Wahyu Sa'dun; Yotenka, Rahmadi; Fajriyah, Rohmatul
Statistika Vol. 24 No. 2 (2024): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v24i2.4611

Abstract

ABSTRAK Sepakbola merupakan olahraga paling populer. Dalam permainan sepakbola, peran gelandang sangat penting sehingga setiap klub sepakbola terutama di Liga-Liga top Eropa perlu meregenerasi gelandang untuk kompetisi Liga di musim-musim berikutnya. Penelitian ini bertujuan untuk melakukan pencarian pemain tengah pengganti yang memiliki kesamaan karakteristik bermain menggunakan metode K-Medoid Clustering. Metode Principal Component Analysis diimplementasikan untuk mengatasi multikolinieritas dan untuk mereduksi variabel yang digunakan, sehingga didapatkan 2 komponen utama. Kedua komponen utama ini menjelaskan 72.9% variansi populasi yang ada. K-Medoid Clustering menghasilkan 2 kelompok dan berdasarkan pengukuran jarak dengan metode Euclidean didapatkan bahwa Tchouameni merupakan gelandang yang paling mirip dengan Casemiro. Hasil ini mendukung keputusan Real Madrid untuk membeli Tchouameni sebagai keputusan yang tepat. ABSTRACT Football is the most popular sport. In the game of football, the role of midfielders is very important so that every football club, especially in the top European leagues, needs to regenerate midfielders for league competitions in the following seasons. This research aims to search for substitute midfielders who have similar playing characteristics using the K-Medoid Clustering method. The Principal Component Analysis method was implemented to overcome multicollinearity and to reduce the variables used, so that 2 main components were obtained. These two main components explain 72.9% of the population variance. K-Medoid Clustering produced 2 groups and based on distance measurements using the Euclidean method it was found that Tchouameni was the midfielder most similar to Casemiro. These results support Real Madrid's decision to buy Tchouameni as the right decision.
Law of Total Probability of Aftershocks in Earthquake Insurance Darwis, Sutawanir; Hajarisman, Nusar; Suliadi; Fatiha Nurfauzan, Arsyi; Aulia, Githa
Statistika Vol. 25 No. 1 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i1.3886

Abstract

Abstract. Seismic hazard expressed in annual rate of exceedance of a peak ground acceleration traditionally refers to mainshock. A similar seismic hazard, APSHA, has been adopted for aftershock probabilistic seismic hazard. Probabilistic seismic hazard assessment (PSHA) refers to a homogeneous Poisson process to describe mainshock while APSHA models aftershock occurrence as a nonhomogeneous Poisson process whose rate modeled as Omori law. It shown that the combination of PSHA and APSHA results seismic hazard for mainshock-aftershock seismic sequence/cluster (SPSHA/CPSHA). This study shows how to combine results of APSHA and PSHA and proposes a method for earthquake insurance. The study was carried out for West Java region with 206 occurrences consist of 11 clusters. One cluster with 74 aftershocks was chosen for further study. The parameters of SPSHA/CPSHA was estimated using maximum likelihood. The results of SPSHA/CPSHA combined with damage probability matrix (DPM) yields an expected annual damage ratio (EADR) as an indicator of earthquake insurance. The proposed method in this study can be used as a method for computing earthquake insurance premium. Due to limited data further study is needed to obtain accurate and reasonable results.
The Effect of The Mortality Rate Multiplier on Determination of Contribution to Sharia Group Life Insurance Using TMI III and TMI IV at PT Asuransi Jiwa ABC Jihan Khafidhotin Najah; Hikmah, Yulial; Karin Amelia Safitri; Fia Fridayanti Adam
Statistika Vol. 25 No. 1 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i1.4123

Abstract

Abstract. The human mortality rate is an important factor in determining premiums. Information about mortality rates can be obtained through mortality tables that describe the probability or the probability of individual deaths. This study examines the effect of the mortality rate multiplier on gross premium determination in sharia-term life insurance using TMI III and TMI IV at PT Asuransi Jiwa ABC. This research method includes data analysis in the form of claim estimation data and claim realization data for several years from members in the Sharia group term life insurance products. The results of the analysis show that the difference in the mortality rate multiplier value between TMI III and TMI IV affects the gross premium value, especially in certain age ranges, there is a mortality rate value in TMI III that is greater than that in TMI IV, but the resulting premium value is the opposite: the premium in TMI IV is greater than the premium value in TMI III.
Forecasting Foreign Tourist Visits in North Sumatra Province Using the SARIMA Model with Step Function Intervention Debora Sebrina Br. Simanjuntak; Alvionita S., Mika; Achmad Syaiful
Statistika Vol. 25 No. 1 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i1.4629

Abstract

Abstract. Time series analysis is a method for identifying trends, patterns, and fluctuations in data. Its interpretation can be used for forecasting, such as the number of foreign tourist visits in the tourism sector. The Indonesian tourism sector contributes positively to the national economy with a contribution value of 3.79% of the total foreign exchange worth 146.6 billion USD in December 2023. North Sumatra Province as one of the provinces that contributes to the local economy, through landscape diversity and easy access through Kuala Namu Airport (KNO) as a Passenger Exit Survey (PES) makes North Sumatra Province a priority scale destination. Foreign tourist visits to North Sumatra from January 2017 to March 2020 fluctuated, but in April 2020 there was a significant decline due to Covid-19 and social restriction policies. The purpose of this study was to forecast foreign tourist arrivals in North Sumatra from August 2023 to March 2024 using the SARIMA model with step function intervention analysis. The results showed that the number of tourist visits will increase according to the ARIMA (0,1,1)(1,0,1)12 model with the intervention orders b = r = s = 0. The forecasting evaluation obtained is AIC 447.38 and MAPE 9.91%.
Comparison of Generalized Poisson Regression and Negative Binomial Regression Models Based on Akaike Information Criterion Values Sinta Qorri Aina; Darnah; Meirinda Fauziyah; Wiwit Pura Nurmayanti
Statistika Vol. 25 No. 1 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i1.5402

Abstract

Abstract. Poisson regression models discrete data and assumes equidispersion, where the variance equals the mean. It is frequently observed that discrete data exhibits a variance exceeding its mean, a phenomenon known as over-dispersion. Over-dispersion may be addressed through various methodologies, such as Generalized Poisson Regression (GPR) and Negative Binomial Regression (NBR). Model selection is predicated on the smallest Akaike Information Criterion (AIC) value. This study aimed to identify the best model in the comparison of models between GPR and NBR based on the smallest AIC value so that it can be known what factors influence the number of cases of pulmonary tuberculosis (TB) in Indonesia in 2022. The results of the study showed that the NBR model was the best model, with an AIC value of 688.49. Factors that influence cases of pulmonary TB in Indonesia in 2022 are the percentage of households that have access to proper sanitation, nursing staff, and the percentage of education levels completed are high school or equivalent.
Analysis of International Tourist Visits Based on Nationality and Tourism Travel Characteristics Using Complete Linkage Handayani, Vitri Aprilla; Sulistyono, Eko; Arrafi, Adamsyam; Hayati, Nahrul
Statistika Vol. 25 No. 1 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i1.5801

Abstract

Abstract. This research aims to analyze the characteristics of international tourists in Indonesia using Clustering Method: Complete Linkage. The study successfully identified 5 distinct clusters based on nationality and tourism travel characteristics. The analysis showed significant differences between clusters in terms of country of origin, travel patterns, preferences, expenditure, and tourist activities. Cluster 1 was dominated by ASEAN and Middle Eastern countries with stable visitation patterns influenced by geographical proximity and cultural and business relationships. Cluster 2 was the largest group, encompassing various countries with holiday and business tourism characteristics, longer stays, and higher expenditure. Clusters 3, 4, and 5 each consisted of a single country: Timor Leste, Hong Kong, and Papua New Guinea respectively, with unique visitation patterns. Each cluster showed differences in travel purposes, length of stay, expenditure, and activities of interest. A deep understanding of each tourist group’s characteristics was crucial for developing more targeted tourism marketing strategies. The clustering results could be utilized for infrastructure planning, resource allocation, promotional strategies, and service improvements tailored to each group’s characteristics, thereby enhancing tourist experiences and Indonesia’s overall tourism competitiveness.
Geographically Weighted Logistic Regression Modeling on the Spread of Dengue Fever in Bali Province Safitri Pratiwi, Luh Putu; I Made Pasek Pradnyana Wijaya
Statistika Vol. 25 No. 1 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i1.5852

Abstract

Abstract. One of the statistical methods that can be used for data analysis by taking spatial factors into account is Geographically Weighted Logistic Regression (GWLR). GWLR is a model where there are parameters that are influenced by location (Geographically varying coefficient) and parameters that are not influenced by location. Research continues to be carried out to understand the factors that influence the spread of dengue fever and to develop more effective strategies for controlling this disease as well as the best model for data on the spread of dengue fever in Bali Province based on AIC values. The variables used are the response variable (Y) which is the case of dengue fever. The variables studied are the number of dengue fever sufferers in 2022 as the response variable and the predictor variables are number of drinking water facilities (X1), population density (X2), number of doctors (X3), number of health workers, namely nurses (X4), and number of adequate sanitation facilities (X5). The GWLR model is better used to analyze dengue fever data in Bali compared to the Logistic Regression model seen from the low AIC value of 29.4481. The variable number of doctors (X3) is the only variable that significantly affects the probability of DHF occurrence in Bali Province at α = 10%. The positive coefficient for β3 indicates that an increase in the number of doctors increases the probability of DHF occurrence in the region.
Modeling of Maternal Mortality Risk Factors Using Negative Binomial Regression Approach in Southeast Sulawesi Province in 2022 Alfia Mutmainah; Ruslan; Irma Yahya
Statistika Vol. 25 No. 1 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i1.6137

Abstract

Abstract. This study aims to model the risk factors for maternal mortality in Southeast Sulawesi Province in 2022 using a negative binomial regression approach. This analysis is used to overcome the overdispersion problem in count data. The data used is secondary data obtained from the Southeast Sulawesi Provincial Health Service. The variables studied included the number of health centers, the percentage of births in health service facilities, the percentage of pregnant women who implemented the K4 program, the percentage of pregnant women who implemented the K1 program, and the number of midwives. The research results showed that the variables percentage of births in health service facilities, percentage of pregnant women implementing the K4 program, and number of midwives significantly affected maternal mortality. The negative binomial regression model illustrates that increasing the percentage of births in health service facilities and implementing the K4 program can reduce maternal mortality. On the other hand, increasing the number of midwives did not have a significant effect on reducing maternal mortality.

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