1,720,960 research outputs found
PEMODELAN REGRESI BETA PADA DATA KEMISKINAN DI INDONESIA
No full textBadan pusat statistik menunjukkan bahwa persentase penduduk miskin di
Indonesia mengalami peningkatan dari tahun 2019 hingga 2021, mencapai 10.14
persen. Meskipun terdapat penurunan menjadi 9.54 persen pada tahun 2022.
Model regresi Beta dikenal sebagai suatu metode yang memberikan estimasi
parameter yang tepat dan efisien jika dibandingkan dengan metode kuadrat
terkecil biasa, terutama saat variabel terikat memiliki distribusi yang tidak simetris
atau ketika terdapat masalah heteroskedastisitas. Penelitian ini bertujuan untuk
mengetahui model regresi Beta dan mengidentifikasi faktor-faktor yang signifikan
memengaruhi persentase penduduk miskin di Indonesia. Estimasi parameter
model menggunakan metode maksimum likelihood dengan iterasi Newton�Raphson. Data yang digunakan dalam penelitian ini adalah data persentase
penduduk miskin tingkat provinsi yang bersumber dari publikasi Badan Pusat
Statistik Indonesia. Variabel bebas yang digunakan adalah indeks pembangunan
manusia, tingkat pengangguran terbuka, rata-rata lama sekolah, persentase
penduduk yang memiliki jaminan kesehatan berupa BPJS, angka harapan hidup,
angka melek huruf, persentase rumah tangga yang menggunakan sumber air
minum layak. Hasil analisis yang diperoleh pada penelitian ini yaitu model
memiliki fungsi sesuai dengan kondisi untuk tahun 2019 dan tahun 2020 faktor
yang signifikan memengaruhi persentase penduduk miskin adalah indeks
pembangunan manusia, persentase penduduk yang memiliki jaminan kesehatan
berupa BPJS dan persentase angka melek huruf, sedangkan faktor yang signifikan
memengaruhi persentase penduduk miskin tahun 2021 dan 2022 adalah indeks
pembangunan manusia, rata-rata lama sekolah, persentase penduduk yang
memiliki jaminan kesehatan berupa BPJS dan persentase angka melek huruf.
Kata Kunci: Metode Newton-Raphson, Model Regresi Beta, Persentase Penduduk
Miskin
SURVIVAL ANALYSIS ON DATA OF STUDENTS NOT GRADUATING ON TIME USING WEIBULL REGRESSION, COX PROPORTIONAL HAZARDS REGRESSION, AND RANDOM SURVIVAL FOREST METHODS
Get PDFThis article presents a comprehensive study of the factors that influence the length of study data of undergraduate students at FMIPA UNIB class 2018 and 2019. This study is essential because observations show that many students study for more than 8 semesters. The purpose of this study is to determine the factors that significantly influence the length of study of undergraduate students. These factors can be internal and external. Survival analysis is the right method to identify these factors because ordinary regression analysis is unable to estimate survival data. Therefore, methods such as Weibull regression, Cox Proportional Hazards regression, and Random Survival Forest are used. This study does not compare the methods used because these methods are independent of each other, but have the same goal, namely, to determine the factors that influence the length of study of students. The data used in this study are data on the length of study of students from the 2018 and 2019 cohorts sourced from the academic subsection of FMIPA UNIB, with variables of GPA, gender, region of origin, university entry route, parents' occupation, type of study program, and length of study. The results showed that GPA and the type of study program significantly influenced the length of study in Weibull regression analysis. In Cox proportional hazard regression, the GPA variable is an influential factor, while using the Random Survival Forest method, all factors significantly influenced the length of study, with their respective levels of importance
ANALISIS SURVIVAL MAHASISWA TIDAK LULUS TEPAT WAKTU MENGGUNAKAN METODE REGRESI COX PROPORTIONAL HAZARD DAN METODE RANDOM SURVIVAL FOREST
No full textPerguruan tinggi merupakan tempat untuk mendidik generasi penerus bangsa dalam
segi akademik maupun non akademik. Pada dasarnya setiap perguruan tinggi
berusaha memaksimalkan kelulusan para mahasiswanya, baik secara kuantitas
maupun kualitas. Pendidikan program jenjang S1 ditargetkan untuk menyelesaikan
studi selama 8 semester atau dapat juga ditempuh kurang dari 8 semester dan paling
lama yaitu 14 semester. Banyak faktor yang diduga mempengaruhi lama studi
mahasiswa, baik dari faktor internal maupun faktor eksternal. Berdasarkan faktor�faktor yang diduga dapat mempengaruhi lama studi mahasiswa tersebut, maka perlu
dilakukan penelitian untuk mengetahui faktor-faktor apa saja yang berpengaruh
secara signifikan terhadap lama studi mahasiswa. Metode yang dapat digunakan
untuk mengetahui faktor-faktor tersebut adalah analisis survival menggunakan
regresi cox proportional hazard dan random survival forest. Faktor yang
mempengaruhi lama studi menggunakan regresi cox proportional hazard adalah
IPK, sedangkan dengan menggunakan metode random survival forest diperoleh
faktor-faktor yang mempengaruhi lama studi mahasiswa adalah IPK, jenis kelamin,
dan part time. Berdasarkan perbandingan menggunakan metode C-Index, random
survival forest merupakan metode yang cocok digunakan pada data karena nilai
error C-Index sebesar 26,9% yang lebih kecil dari cox proportional hazard yaitu
sebesar 27,8%.
Kata Kunci : Analisis Survival, Cox Proportional Hazard, Random Survival
Forest, Harrell’s Concordance Index, Lama Studi
MODELING THE MANY EARTHQUAKES IN SUMATRA USING POISSON HIDDEN MARKOV MODELS AND EXPECTATION MAXIMIZATION ALGORITHM
Get PDFSumatra Island is one of the islands that are prone to earthquakes because Sumatra Island is located at the confluence of three plates, namely the large Indo-Australian plate, the Eurasian plate and the Philippine plate. In general, the number of earthquake events follows the Poisson distribution, but there are cases where there is overdispersion in the Poisson distribution. The Poisson Hidden Markov Models (PHMMs) method is used to overcome overdispersion, then applying the Expectation-Maximization Algorithm (EM algorithm) to each model to obtain the estimated parameters. From the models obtained, the best model will be selected based on the smallest Akaike Information Criterion (AIC) value. The data used is secondary data on earthquake events on the island of Sumatra from January 2000 to December 2022 with a depth of ≤ 70 Km and a magnitude of ≥ 4.4 Mw. From the research, the model with m = 3 is the best estimation model with an AIC value of 1503,286. From the best model, estimates are obtained for Poisson Hidden Markov Models with an average occurrence of earthquakes of 5.7633 ≈ 6 events within one month
Sentiment Analysis of Twitter User’s Perceptions of the Campus Merdeka Using Naïve Bayes Classifier and Support Vector Machine Methods
Get PDFThe Campus Merdeka program is being implemented by the government to realize autonomous and flexible learning in tertiary institutions to create a learning culture that is innovative, not restrictive, and the needs of students. The Campus Merdeka provides added value and is attractive and provides various responses from the public both directly and on different social media platforms. One of the social media platforms is Twitter. Therefore, research was conducted on the community's response to the Campus Merdeka program on Twitter social media. Twitter documents in the form of community response tweets to the Campus Merdeka program are classified into two categories, namely positive responses and negative responses. The method used in this study is the Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) with a Polynomial Degree 2 kernel. The highest level of accuracy resulting from this research is 73.5% with a parameter value of of 0.5, a constant value is 0.5, with training data of 309 documents for training data and 132 documents for test data. The accuracy results obtained for the Naïve Bayes Classifier method are 65.9% and for the Support Vector Machine method, an accuracy is 73.5%
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
ANALISIS SURVIVAL MAHASISWA TIDAK LULUS TEPAT WAKTU MENGGUNAKAN METODE REGRESI COX PROPORTIONAL HAZARD DAN METODE RANDOM SURVIVAL FOREST
No full textPerguruan tinggi merupakan tempat untuk mendidik generasi penerus bangsa dalam segi akademik maupun non akademik. Pada dasarnya setiap perguruan tinggi berusaha memaksimalkan kelulusan para mahasiswanya, baik secara kuantitas maupun kualitas. Pendidikan program jenjang S1 ditargetkan untuk menyelesaikan studi selama 8 semester atau dapat juga ditempuh kurang dari 8 semester dan paling lama yaitu 14 semester. Banyak faktor yang diduga mempengaruhi lama studi mahasiswa, baik dari faktor internal maupun faktor eksternal. Berdasarkan faktor-faktor yang diduga dapat mempengaruhi lama studi mahasiswa tersebut, maka perlu dilakukan penelitian untuk mengetahui faktor-faktor apa saja yang berpengaruh secara signifikan terhadap lama studi mahasiswa. Metode yang dapat digunakan untuk mengetahui faktor-faktor tersebut adalah analisis survival menggunakan regresi cox proportional hazard dan random survival forest. Faktor yang mempengaruhi lama studi menggunakan regresi cox proportional hazard adalah IPK, sedangkan dengan menggunakan metode random survival forest diperoleh faktor-faktor yang mempengaruhi lama studi mahasiswa adalah IPK, jenis kelamin, dan part time. Berdasarkan perbandingan menggunakan metode C-Index, random survival forest merupakan metode yang cocok digunakan pada data karena nilai error C-Index sebesar 26,9% yang lebih kecil dari cox proportional hazard yaitu sebesar 27,8%.
Kata Kunci : Analisis Survival, Cox Proportional Hazard, Random Survival Forest, Harrell’s Concordance Index, Lama Studi
A Panel Data Spatial Regression Approach for Modeling Poverty Data In Southern Sumatra
Get PDFThis research examines the use of spatial panel data regression approach to model poverty data in the Southern Sumatra region. The main objective of the study is to model poverty in the Southern Sumatra region using spatial panel data regression. Panel data from districts/cities in South Sumatra, Jambi, Lampung, Bengkulu, and Bangka Belitung during the 2015-2021 period were used in the analysis. The spatial panel models used in this study are panel SAR regression and panel SEM. The results show that the spatial panel data approach is better at explaining variations in poverty levels compared to non-spatial models. A significant spatial spillover effect was found, where the poverty level of an area is influenced by the conditions of its neighboring areas. The results of the analysis show that the best model to use in modeling the Poverty Percentage data in the Southern Sumatra region is the Spatial Autoregressive Fixed Effect (SAR-FE) model based on the smallest AIC and BIC values. Factors such as average years of schooling and life expectancy are proven to have a significant influence on the percentage of poverty in the SAR Fixed Effect model
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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