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All Journal MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jurnal Saintika Unpam : Jurnal Sains dan Matematika Unpam Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat InPrime: Indonesian Journal Of Pure And Applied Mathematics Jurnal Riset Pembelajaran Matematika Sekolah Jurnal Statistika dan Aplikasinya Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi International Journal of Progressive Mathematics Education MATHunesa: Jurnal Ilmiah Matematika International Journal of Applied Science and Sustainable Development (IJASSD) Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Pattimura International Journal of Mathematics (PIJMath) JMT (Jurnal Matematika dan Terapan) Parameter: Jurnal Matematika, Statistika dan Terapannya BAKTI : Jurnal Pengabdian Kepada Masyarakat
Vera Maya Santi
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Analisis Distribusi Gamma Bivariat Jadid Irtakhoiri; Suyono Suyono; Vera Maya Santi
Jurnal Statistika dan Aplikasinya Vol 2 No 1 (2018): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.02104

Abstract

Skripsi ini membahas mengenai distribusi Gamma bivariat khususnya tentang konstruksi dan karakteristik dari distribusi Gamma bivariat. Gamma bivariat dikonstruksi berdasarkan karakteristik dari distribusi Gamma dan distribusi Beta, serta membangun p.d.f bersama, dan p.d.f bersyarat. Gamma bivariat dibentuk dengan mendefinisikan variabel acak X = UW dan Y = VW, dimana U dan V berdistribusi Gamma dan W berdistribusi Beta. Konstruksi dilakukan dengan memanfaatkan fungsi Whittaker untuk membantu proses pengintegralan dalam membentuk p.d.f bersama distribusi Gamma bivariat. Karakteristik distribusi Gamma bivariat yang dibahas adalah product moment, kovariansi, dan korelasi.
Pengembangan Model Regresi Logistik Multinomial untuk Klasifikasi Politik pada Pemilihan Umum Vera Maya Santi
Jurnal Statistika dan Aplikasinya Vol 2 No 1 (2018): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.02105

Abstract

Untuk memenuhi semua persyaratan pemerintah dari rakyat, oleh rakyat, dan untuk rakyat sepenuhnya, politik demokrasi memerlukan pemilihan umum. Berbagai partai politik dalam pemilihan umum menunjukkan keragaman minat dan ideologi. Jumlah fluktuasi partai dalam pemilihan umum dan perilaku pemilih mempengaruhi fluktuasi jumlah pemilih. Analisis regresi logistik multinomial adalah salah satu metode yang dapat digunakan untuk mengklasifikasikan partai politik berdasarkan perilaku pemilih. Dalam penelitian ini, variabel respon berdasarkan ideologi partai pemilu memiliki tiga kategori: Partai Nasionalis-Agama (PNR), Partai Nasional-Sekuler (PNS), dan Partai Islam (PI). Variabel penjelasnya adalah perilaku pemilih pemula. Berdasarkan uji signifikansi model dengan tingkat signifikansi 0,05, terdapat 11 variabel yang menunjukkan pengaruh signifikan terhadap klasifikasi partai politik dalam pemilu secara bersamaan.
Analisis Survival dengan Model Regresi pada Data Tersensor Berdistribusi Log-Logistik Gatri Eka Kusumawardhani; Vera Maya Santi; Suyono Suyono
Jurnal Statistika dan Aplikasinya Vol 2 No 2 (2018): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.02204

Abstract

Survival analysis is an analysis used to determine the length of time required by an object in order to survive. That time is sometimes influenced by several factors called independent variables. One way to know relationship is through a regression model. The dependent variable in this regression model is a survival time which is log-logistic distributed. The data used in this study were right censored survival data. Log-logistic regression models for survival data can be expressed by transformation Y=lnT= θ0+θ1xi1+...+θixij+σԑ. The parameter of the log-logistic regression models for right censored survival data are estimated with the maximum likelihood method. In this study, the application of log-logistic regression model for survival data is in data of lung cancer patients. Based on the data already performed, best log-logistic regression model is obtained yi=1.92458+0.0242393 xi1+0.639037ԑi.
Pemodelan Jumlah Kasus Malaria di Indonesia Menggunakan Generalized Linear Model Vera Maya Santi; Abi Wiyono; Sudarwanto
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.05111

Abstract

Generalized Linear Model (GLM) telah banyak digunakan untuk memodelkan berbagai macam tipe data dimana distribusi dari variabel respon merupakan distribusi yang termasuk dalam distribusi keluarga eksponensial. Contoh umum dari distribusi keluarga eksponensial adalah distribusi Poisson dan Binomial. Model regresi GLM mendeskripsikan struktur dari variabel prediktor, sedangkan fungsi penghubung secara khusus mendeskripsikan hubungan antara model regresi dengan nilai ekspektasi dari variabel respon. Tujuan dari artikel ini adalah mendapatkan variabel-variabel prediktor yang berpengaruh signifikan terhadap model. Metode Maximum Likelihood Estimation digunakan untuk mencari estimasi dari nilai parameter regresi model. Jumlah kasus malaria di Indonesia diidentifikasi berdistribusi Poisson. Terdapat 3 variabel prediktor yang berpengaruh signifikan terhadap jumlah kasus malaria di Indonesia, yaitu persentase rumah tangga yang memiliki akses sanitasi layak, jumlah kabupaten/kota yang menyelenggarakan tatanan kawasan kesehatan dan jumlah kabupaten/kota yang melakukan pengendalian vektor terpadu.
Penerapan Metode SMOTE CHAID dalam Klasifikasi Tuberkulosis Relapse Vera Maya Santi; Lina Nafisah; Qorry Meidianingsih
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.06103

Abstract

DKI Jakarta Province is one of the provinces with the highest tuberculosis cases, and a person's chance of contracting tuberculosis is the greatest among other provinces. Tuberculosis can be cured with regular treatment within a certain period of time, but after recovering, some tuberculosis sufferers may relapse so that it can cause new problems. This study aims to build a classification model and determine which factors influence tuberculosis relapse using the CHAID method. SMOTE with majority undersampling is applied as a solution to deal with the problem of patient categories (relapse and non-relapse) who have an unbalanced number of observations. Based on the CHAID classification tree, the results show that the factors that influence relapse in tuberculosis patients include the type of diagnosis, age, gender, and place of residence. In addition, the application of SMOTE can improve the performance of the CHAID classification tree in classifying patients based on their categories. These results were indicated by an increase in the values of accuracy, sensitivity, and specificity to 76,153; 26,667; and 82,608 compared to the performance of CHAID without SMOTE. Based on these results, the SMOTE CHAID classification model has better performance than CHAID
PELATIHAN RANCANGAN PERCOBAAN DALAM MENINGKATKAN KUALITAS RISET CIVITAS AKADEMIMA LLDIKTI WILAYAH III DKI JAKARTA Vera Maya Santi Santi; Widyanti Rahayu; Fariani Hermin; Syifa Azzahra; Novia Sucy Aristawidya
Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Vol 2 (2021): PROSIDING SEMINAR NASIONAL PENGABDIAN KEPADA MASYARAKAT - SNPPM2021
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.683 KB)

Abstract

Abstract College as part of the education system also has a very important role, including as a printer for the nation’s next generation and even young researchers. Another function is as a research tool whose results can be applied and used in improving the welfare of the community. However, in reality, there are still many lack of understanding of lecturers and students on how to design an experiment from a quantitative study and difficulties in determining the right experimental design when dealing with real problems in the field. Because of the crucial role of lecturers and students as educational assets, especially in research development, the training targets in this training are lecturers and students appointed by the Region III Lembaga Layanan Pendidikan Tinggi (LLDIKTI), namely Private Universities from the DKI Jakarta province. This programme is implemented to improve the quality of research for lecturers and students and is expected to be able to design a quantitative research experiment, especially in the field of education. Based on the results of the questionnaire before and after the training, most of the training participants responded that the training was very beneficial and provided new knowledge, motivation and added skills that support the profession as lecturers and students. Abstrak Perguruan Tinggi sebagai bagian dari sistem pendidikan juga memiliki peranan yang sangat penting, antara lain sebagai pencetak generasi penerus bangsa bahkan peneliti-peneliti muda. Fungsi lainnya adalah sebagai sarana riset yang hasilnya dapat diterapkan dan digunakan dalam meningkatkan kesejahteraan masyarakatnya. Namun pada kenyataannya, masih banyak ditemukan rendahnya pemahaman dosen dan mahasiswa mengenai bagaimana merancang suatu percobaan dari suatu penelitian kuantitatif serta kesulitan dalam menentukan rancangan percobaan yang tepat Ketika berhadapan dengan permasalahan riil di lapangan. Oleh karena krusialnya peranan dosen dan mahasiswa sebagai aset pendidikan khususnya dalam pengembangan riset, maka sasaran pelatihan pada pelatihan ini adalah para dosen dan mahasiswa yang ditunjuk oleh Lembaga Layanan Pendidikan Tinggi (LLDIKTI) Wilayah III yaitu Perguruan Tinggi Swasta dari provinsi DKI Jakarta. Program ini dilaksanakan untuk meningkatkan kualitas riset bagi dosen dan mahasiswa serta diharapkan mampu merancang suatu percobaan penelitian kuantitatif khsususnya di bidang pendidikan. Berdasarkan hasil olah kuesioner sebelum dan sesudah pelatihan, sebagian besar peserta pelatihan memberikan respon bahwa pelatihan sangat memberikan manfaat dan pengetahuan baru, motivasi serta menambah keterampilan yang menunjang profesi sebagai dosen dan mahasiswa.
ANALYZING OPEN UNEMPLOYMENT RATE IN JAVA USING PENALIZED SPLINE NONPARAMETRIC REGRESSION Vera Maya Santi; Nia Rahayu Ningsih; Faroh Ladayya
International Journal of Applied Science and Sustainable Development (IJASSD) Vol. 4 No. 2 (2022): International Journal of Applied Science and Sustainable Development (IJASSD)
Publisher : Lembaga Penelitian dan `Pengabdian Kepada Masyarakat (LPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In regression analysis, there are three regression curve approach methods: parametric approach, semiparametric approach, and nonparametric approach. One of the estimation methods in nonparametric regression is spline regression with parameter estimation methods, namely smoothing, truncated, and penalized. Penalized spline estimation controls the smoothness of the curve so that the curve avoids stiffness and overfitting and does not require assumptions. This study aims to analyze the open unemployment rate in Java, which has the highest open unemployment rate in Indonesia, where studies using this approach have never been conducted. The study's results resulted in an additive Mean Square Error (MSE) of 4.137 with a coefficient of determination of 44.58%, indicating that explanatory variables of 44.58% could explain the open unemployment rate. Based on the parameter significance test, the factors that significantly effect the open unemployment rate are the dependency ratio, the GDP growth rate, senior high school gross enrollment, percentage of the poor population, and population growth rate.
Geographically Weighted Regression dalam Menganalisis Faktor-Faktor yang Mempengaruhi Kasus Tuberkulosis di Sumatera Utara Vera Maya Santi; Afifah Nur Mutia; Qorry Meidianingsih
Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Vol. 19 No. 2 (2022): Sainmatika : Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam
Publisher : Universitas PGRI Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31851/sainmatika.v19i2.9020

Abstract

Geographically Weighted Regression (GWR) is a method used to analyze a case by considering spatial effects. Spatial effects indicate differences in environmental characteristics between regions. A spatial effect can be seen from the violation of the assumption of the multiple linear regression homoscedasticity test. Research in the health sector often shows that the spread of disease, especially infectious diseases, is influenced by spatial effects, one of which is tuberculosis. In 2020, North Sumatra will become one of the areas with high tuberculosis cases, so it is necessary to study tuberculosis cases and determine the factors that influence it by involving spatial effects. This study aims to model tuberculosis cases and analyze the ten factors thought to influence it using the GWR method with the adaptive kernel bi-square weighting function. The results showed that 23 regencies/cities had local GWR models and different factors influencing tuberculosis cases for each region, and ten other regencies/cities were influenced by other factors outside the variables studied. Based on the variables that affect it, 13 regional groups are formed. Modeling with the GWR method can explain tuberculosis cases in North Sumatra by 99.4%, and other predictor variables influence the rest.
ANALYZING READING LITERACY SCORE OF INDONESIAN STUDENTS USING LINEAR MIXED MODELS Vera Maya Santi; Syifa Azzahra; Dania Siregar
MUST: Journal of Mathematics Education, Science and Technology Vol 7 No 2 (2022): DECEMBER
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/must.v7i2.14420

Abstract

The linear mixed models is a development of the linear model which includes both fixed and random effects in the model. Random effect in the model is used to model complex data that has a grouping structure. The grouping structure can occur because the same observations are measured repeatedly or each observation is measured only once but these observations have some form of group structure. Students who participate in the Program for International Student Assessment (PISA) are nested in several schools, so the PISA data structure is quite complex and requires a more in-depth analysis. Quantitative studies on PISA, especially in reading literacy, are still rarely done. The purpose of this study is to determine what factors effect the Indonesian student’s PISA reading literacy scores using a linear mixed model approach with school being used as a random effect in the model. The findings of the study are that the factors that affects Indonesian student’s PISA reading literacy scores are the class being taken, gender, mother's highest education, facilities at home, school entry age, student discipline and failed a grade. The result of the estimation of random effect variance which is not equal to zero indicates that there is a random effect from the student’s school on PISA reading literacy scores. Based on model diagnostics and parameter testing, it was concluded that the model obtained is fitted in modeling Indonesian student’s PISA reading literacy scores.
ANALISIS PERSEPSI MAHASISWA FMIPA UNJ DALAM MENGGUNAKAN APLIKASI PEMBELAJARAN JARAK JAUH DENGAN REGRESI LOGISTIK MULTINOMIAL Vera Maya Santi; Syarifah Ayu Angela; Yudi Mahatma
JURNAL SAINTIKA UNPAM Vol 4, No 2 (2022)
Publisher : Program Studi Matematika FMIPA Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jsmu.v4i2.18245

Abstract

Perubahan pola pendidikan yang terjadi dikarenakan pandemi Covid-19 mengharuskan kegiatan pembelajaran dilakukan melalui pembelajaran jarak jauh. Dalam hal ini, berbagai platfrom telah meluncurkan aplikasi-aplikasi yang dapat memfasilitasi kegiatan pembelajaran antara lain Zoom, Google Classroom, Google Meet, Microsoft Teams, WhatsApp dan aplikasi lainnya. Masing-masing aplikasi memiliki kelebihan dan kekurangan. Penelitian ini mengamati tiga aplikasi pembelajaran jarak jauh, yaitu Zoom, Google Meet dan Microsoft Teams. Analisis lebih mendalam perlu dilakukan untuk mengetahui persepsi mahasiswa FMIPA UNJ dalam menggunakan aplikasi pembelajaran jarak jauh dan mengetahui aspek-aspek penilaian yang mempengaruhi persepsi mahasiswa FMIPA UNJ dalam menggunakan aplikasi pembelajaran jarak jauh. Metode yang digunakan dalam penelitian ini adalah regresi logistik multinomial. Dari hasil analisis diperoleh model logit persepsi mahasiswa FMIPA UNJ dalam menggunakan aplikasi pembelajaran jarak jauh dengan regresi logistik multinomial adalah  dan  serta dari hasil analisis uji serentak diperoleh bahwa aspek penilaian kemudahan mengakses , tampilan aplikasi , fitur-fitur yang tersedia  dan penggunaan kuota  mempengaruhi persepsi mahasiswa FMIPA UNJ dalam menggunakan aplikasi pembelajaran jarak jauh.
Co-Authors Abi Wiyono Afifah Nur Mutia Ambarwati, Defina Auria Yusrin Fathya Bagus Sartono Bagus Sumargo Bagus Sumargo Bagus Sumargo, Bagus Baihaqi, Aulia Binoto, Rustham Michael Contillo, Gerry Dania Siregar Dania Siregar Dian Handayani Dwi Antari Wijayanti Ellis Salsabila, Ellis Fanya Izmi Hawa Faoza Saaroh Fariani Hermin Faroh Ladayya Gatri Eka Kusumawardhani Gusnia, Farida Herlina Nofita Ibnu Hadi Indahwati Indiyah, Fariani Hermin Jadid Irtakhoiri Jaisy Aulia Kamil, Adine Ihsan Kamilia, Rifa Khoirunnisa Koeshella, Ajeng Ladayya, Faroh Lina Nafisah Lukman El Hakim Mahatma, Yudi Maulida Audia Firdaus Meidianingsih, Qorry Meila Nadya Muhammad Alief Ghifari Muhammad Rafli Muzakki Tamami Nia Rahayu Ningsih Nilam Novita Sari Novia Sucy Aristawidya Pinta Deniyanti Sampoerno Pinta Deniyanti Sampoerno Prima Riyani Rahayuningsih, Yuliana Rahfa Qur’aniyatin Dhuha Ria Arafiyah Riam Nurussilmah Rianiati Monica Ridana, Farah Fadhilah Rifqy Marwah Akhsanti Riska Agustin Riyantobi, Ariq Muammar Safira Datu Sinta Rahmadani Siregar, Dania Siti Rohmah Rohimah Sudarwanto Sudarwanto, Sudarwanto SUYONO Suyono Suyono Suyono Suyono Syarifah Ayu Angela Syifa Azzahra Tamami, Muzakki Tian Abdul Aziz Tri Murdiyanto Wahyu, Rahadian Wardani Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Wilsen Wilsen Zahrah Hashifah