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Analisis Faktor-Faktor yang Memengaruhi Kompetensi Karyawan SOS Children’s Villages Indonesia Anis Dela Desela; Rianti Setiadi; Yekti Widyaningsih
Jurnal Statistika dan Aplikasinya Vol 4 No 2 (2020): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.04204

Abstract

Pertumbuhan ekonomi dan sosial di suatu negara tidak terlepas dari peran Non-Governmental Organization (NGO). Akan tetapi, terdapat beberapa permasalahan yang muncul dari NGO. Untuk menanggulangi permasalahan dan meningkatkan kualitas pelayanan, suatu NGO diharapkan memiliki karyawan dengan kompetensi tinggi. Penelitian dilakukan di SOS Children’s Villages Indonesia yang merupakan salah satu NGO di Indonesia yang didedikasikan untuk anak-anak yang telah atau berisiko kehilangan pengasuhan orang tua. Tujuan dari penelitian ini adalah untuk mengetahui faktor-faktor yang memengaruhi kompetensi karyawan di SOS Children’s Villages Indonesia serta mengetahui profil dari karyawan dengan kompetensi tinggi. Metode analisis yang digunakan dalam penelitian ini adalah Partial Least Square dan Classification and Regression Tree. Hasil penelitian menunjukkan bahwa variabel yang secara signifikan berpengaruh terhadap kompetensi adalah variabel interpersonal dan kreativitas. Hasil analisis profil untuk karyawan dengan kompetensi tinggi menunjukkan bahwa karyawan yang bekerja di kantor Fund Development and Communication yang terletak di Bandung atau DKI Jakarta, atau karyawan yang bekerja di kantor National Office yang terletak di Bandung dengan tingkat kreativitas tinggi cenderung memiliki kompetensi yang tinggi, selain itu karyawan yang bekerja di kantor Fund Development and Communication yang terletak di Bandung meskipun memiliki tingkat interpersonal dan kreativitas rendah, karyawan tersebut memiliki kecenderungan untuk memiliki kompetensi tinggi.
Nested Generalized Linear Model with Ordinal Response for Correlated Data Yekti Widyaningsih; Asep Saefuddin; Khairil A. Notodiputro; Aji H. Wigena
IPTEK The Journal for Technology and Science Vol 23, No 2 (2012)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v23i2.12

Abstract

In this paper, we discuss the generalized linear models with ordinal response for correlated data in nested area. Some basic concepts are described, that is nested spatial, threshold model, and cumulative link function. Due to correlated data used for this modeling, Generalized Estimating Eequation (GEE) is used as model parameters estimation method. Nested is shown by the model building and its application on nested spatially data. In this method, some Working Correlation Matrices (WCM) are able to be specified depend on the nature and type of the data. In this study, 3 types of WCM and 2 types of parameters estimation covariance are used to see the results of parameters estimation from these combinations. As a conclusion, independent WCM is appropriate to the data.
Analisis Angka Kelahiran pada Remaja Indonesia Usia 15-19 Menggunakan Regresi Binomial Negatif Silvia; Geraldine Immanuel Tangyong; Yekti Widyaningsih
Jurnal Statistika dan Aplikasinya Vol 5 No 1 (2021): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.05109

Abstract

Menurut BKKBN, angka kelahiran untuk perempuan usia remaja terbilang cukup tinggi. Hal ini perlu menjadi perhatian khusus, karena jumlah remaja di Indonesia sangat besar dan pada umur 15-19 tahun seseorang seharusnya masih dalam proses mengenyam pendidikan. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang memengaruhi angka kelahiran perempuan umur 15-19 tahun pada tahun 2012 berdasarkan provinsi di Indonesia. Faktor-faktor dalam penelitian ini adalah Indeks Pembangunan Manusia (IPM) menurut provinsi, tingkat pengangguran terbuka (dalam persen) menurut provinsi, jumlah penduduk miskin menurut provinsi, angka melek huruf, dan rata-rata lama sekolah. Penelitian ini menggunakan analisis regresi Poisson, khususnya regresi binomial negatif. Hasil pengujian menunjukkan bahwa data mengalami overdispersi. Untuk mengatasi kondisi ini digunakan regresi Binomial Negatif. Faktor yang berpengaruh signifikan terhadap angka kelahiran pada perempuan berumur 15-19 tahun adalah angka melek huruf, rata-rata lama sekolah, dan jumlah penduduk miskin.
Analisis Regresi Logistik Binomial dan Algoritma Random Forest pada Proses Pengklasifikasian Penyakit Ginjal Kronis Abraham Raja Swara Darwanto; Taza Luzia Viarindita; Yekti Widyaningsih
Jurnal Statistika dan Aplikasinya Vol 5 No 1 (2021): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.05101

Abstract

Penyakit Ginjal Kronis (Chronic Kidney Disease) merupakan masalah kesehatan yang banyak diderita oleh masyarakat di seluruh dunia dan telah diangkat sebagai penyebab penting kematian dengan angka yang besar. Penyakit ginjal kronis termasuk penyakit yang perlu diperiksa secara rutin. Penulis berharap penyakit ini dapat dideteksi dengan tes sesedikit mungkin dan biaya yang rendah dengan menggunakan regresi logistik binomial dan metode klasifikasi Random Forest. Sehingga tujuan dari penelitian ini adalah ingin membandingkan akurasi dari kedua metode untuk melihat model yang paling efektif dalam memprediksi CKD. Hasil penelitian menunjukkan bahwa analisis menggunakan metode regresi logistik binomial memiliki keakuratan yang lebih tinggi dibandingkan dengan metode klasifikasi random forest yaitu sebesar 97.5%, di mana kedua metode menggunakan faktor-faktor yang sama yaitu Specific Gravity, Albumin, Serum Creatinine, Hemoglobin, dan kadar Packed Cell Volume.
Relationship Pattern of Fatherless Impacts to Internet Addiction, Suicidal Tendencies and Learning Difficulties for Students at SMAN ABC Jakarta Bunga Maharani Yasmin Wibiharto; Rianti Setiadi; Yekti Widyaningsih
Society Vol 9 No 1 (2021): Society
Publisher : Laboratorium Rekayasa Sosial FISIP Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (840.061 KB) | DOI: 10.33019/society.v9i1.275

Abstract

Fatherless is the absence of a father figure. Some impacts of fatherlessness are loneliness, openness, depression, self-control, and self-esteem. These factors can influence internet addiction and suicidal tendencies. It also can cause difficulty in the learning process for students. This study aims to determine the significant impacts caused by fatherlessness and the relation to internet addiction, suicidal tendencies, and learning difficulties. The method used is Partial Least Square. The results showed that the significant impacts caused by fatherlessness are loneliness, depression, and self-esteem. The impacts of fatherless that influence internet addiction are loneliness and depression. The impact of fatherlessness that influences suicidal tendencies is depression. Internet addiction and suicidal tendencies influence learning difficulties.
Pemodelan Spasial pada Data Produk Domestik Regional Bruto di Pulau Jawa Sebelum dan Ketika Pandemi Yekti Widyaningsih; Melia Rizki Fitrianingrum
Jurnal Statistika dan Aplikasinya Vol 6 No 1 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06102

Abstract

One of the regional economic indicators is GRDP, GRDP or gross regional domestic product explains the ability of the region to manage and utilize the resources in the area. In 2020, the Covid-19 pandemic entered Indonesia and caused the economy to stagnate. This has a negative effect on national economic activities and reduces the value of GRDP. To overcome these problems, we will look for factors that are thought to influence the value of GRDP. In the process there are obstacles, namely incomplete data (there are missing values). To overcome the missing values, imputation will be carried out using the k-nearest neighbor imputation method. The spatial effect test was conducted to determine whether there was a spatial effect on the data. Based on the test, it is known that there is spatial heterogeneity, so that the modeling of the GRDP value is carried out using the geographically weighted regression model. The GWR method can handle spatial non-stationary, so that it can be seen what variables significantly affect the value of GRDP in each district/city on the island of Java. Before the pandemic, the variables that affected the value of GRDP in Java were local income, average informal wages, realization of domestic investment, and the number of unemployed. During the pandemic, the variables that affect the value of GRDP in Java are local revenue, the realization of foreign investment, and the number of unemployed.
APLIKASI K-FOLD CROSS VALIDATION DALAM PENENTUAN MODEL REGRESI BINOMIAL NEGATIF TERBAIK Yekti Widyaningsih; Graceilla Puspita Arum; Kevin Prawira
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 2 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.732 KB) | DOI: 10.30598/barekengvol15iss2pp315-322

Abstract

Publikasi ilmiah merupakan salah satu indikator penilaian terhadap kualitas akademisi. Tetapi tidak dapat dipungkiri pembuatan publikasi ilmiah bukanlah suatu hal yang mudah, karena membutuhkan proses pembuatan dan proses penelaahan yang rumit. Tujuan dari penelitian ini adalah untuk mengetahui faktor-faktor yang memengaruhi banyaknya publikasi ilmiah yang dihasilkan oleh mahasiswa PhD Biokimia tahun 1997. Karena variabel dependen merupakan count data, metode analisis yang digunakan adalah Regresi Poisson. Namun karena data mengalami overdispersi, akan digunakan Regresi Binomial Negatif. Perbandingan beberapa model Regresi Poisson dan Binomial Negatif dilakukan untuk menentukan model terbaik dengan k-fold cross validation sebagai validasi model. Hasil penelitian menunjukkan bahwa model terbaik yang didapatkan adalah model Regresi Binomial Negatif dengan variabel independen jenis kelamin, status pernikahan, banyaknya anak dibawah 5 tahun, prestise, dan banyaknya artikel oleh mentor dalam 3 tahun terakhir.
Klasifikasi Pemilih dalam Pemilu 2019 di Indonesia Menggunakan Regresi Logistik Multinomial dan Chi-Square Automatic Decision Tree (CHAID) Yekti Widyaningsih; Curie Nabilah Nasution
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06201

Abstract

General Elections (Elections) in Indonesia are conducted once in every 5 years. This paper focused on the election of the president and his representatives. Voters in elections are regulated by law. There are many aspects of voter’s background that influence voters in making decisions during elections. In this paper, the focus is on voter background factors in geographical, demographic, and socio-economic aspects. The geographical aspect is the region where voters live; demographic aspects are gender, age, recent education, marital status, and religion; socioeconomic aspects are the household expenses, household income, personal expenses, type of work, type of residence, and status of residence. There are 3 categories of voter decisions in the election, namely candidate pair A, candidate pair B, and refuse to vote. The objectives of this paper are to find out what variables significantly influence voters in making decisions during elections, and to classify voters based on the significance of variables in geographical, demographic, and socio-economic aspects related to voter choice in elections. Multinomial logistic regression analysis is used to answer the first objective, while the CHAID (Chi-Square Automatic Decision Tree) decision tree is used to answer the second objective. Through multinomial logistic regression analysis, it can be seen that the variable type of region, age, recent education, religion, household expenditure, household income, house type and home status influence voter decisions in elections. Through the CHAID decision tree, the results obtained are 5 types of voters based on a decision tree of several independent variables that are significant to the dependent variable.
Analisis Faktor-Faktor yang Menjelaskan Kasus AIDS Provinsi Jawa Timur Menggunakan Model Geographically Weighted Logistic Regression (GWLR) Natasha Latifatu Soliha; Dian Lestari; Yekti Widyaningsih
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07104

Abstract

AIDS is the most chronic phase of HIV infection which can weaken the immune system. In 2020, East Java Province is a province which has the most HIV infections and in the third place for the highest total number of AIDS cases in Indonesia. The purpose of this research is to build a model using Geographically Weighted Logistic Regression (GWLR), and to work out the grouping results of regencies/cities using K-means Clustering Analysis. The variables used in this research are Gini Ratio, L Index of Per Capita Expenditure, Gender Ratio, Dependency Ratio, Gender Development Index, and The Number of Pos Pelayanan KB Desa. The proportion levels of AIDS cases are categorized into 2 categories based on cut-point which has been specified, which 0 as the category of low level with the proportion of AIDS cases is less than 0.0006 and 1 as the category of high level with the proportion of AIDS cases is more than or equal to 0.0006. Parameter estimation for GWLR is using Maximum Likelihood Estimation (MLE) method with Fixed Gaussian as weighted kernel function and optimum bandwidth is determined using Akaike's Information Criterion Corrected (AICc). Z-Score of the most suitable model will be grouped using K-means Clustering Analysis, with Z-score is parameter estimator divided by standard error. Grouping results indicates cluster 1 members tend to be regencies/cities that have gender ratio and dependency ratio as significant variables, meanwhile cluster 2 members tend to be regencies/cities that have only dependency ratio as significant variable.
Analisis Faktor-Faktor yang Menjelaskan Pengimplementasian Nilai-Nilai Utama (Corevalues) AKHLAK pada Karyawan di PT TASPEN (Persero) Mohammad Zahran Pratomo; Yekti Widyaningsih; Dian Lestari
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07103

Abstract

The development of the global economy is currently entering the era of Industry 4.0. Industry 4.0 cannot be faced only with technological development, but must involve social dynamics in it. Every company and agency must create a strategy in dealing with this era, including Badan Usaha Milik Negara (BUMN) by establishing main values that become the reference for the behavior of all human resources in BUMN. These core values consist of Trustworthy, Competent, Harmonious, Loyal, Adaptive, and Collaborative (AKHLAK). In practice, AKHLAK has not been implemented properly, even though the corevalues of AKHLAK need to be implemented by all human resources in BUMN. This study examines the significant factors explaining the implementation of AKHLAK core values on PT TASPEN (Persero) employees and to examine the profile of employees who have implementation core values high and low are based on significant factors. The factors used in this study are work motivation, work environment, employee welfare, socialization, employee commitment, religiosity, work stress, age, gender, education level, and years of service. The methods used in solving this research problem are the Partial Least Square (PLS) method and the Classification and Regression Tree (CART) method. The data used is primary data of 209 PT TASPEN (Persero) employees taken using purposive sampling. The results showed that work motivation, socialization, religiosity, and education level can significantly explain the implementation of AKHLAK. The profile of employees who have a high level of implementation of AKHLAK are employees with high level of religiosity, high work motivation, for all categories of educational levels, and work stress levels. The profile of employees who have a low level of implementation of AKHLAK are employees who have low religiosity and work motivation.