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All Journal Media Statistika Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jurnal Varian Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Jurnal Abdi Insani ESTIMASI: Journal of Statistics and Its Application International Journal Of Science, Technology & Management (IJSTM) JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Jurnal Siger Matematika Journal of Research Applications in Community Services Eksponensial STATISTIKA Journal of Education Technology and Information System
Sifriyani, Sifriyani
Statistics Study Program, Department Of Mathematics, Faculty Of Mathematics And Natural Sciences, Mulawarman University, Samarinda
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SUSCEPTIBLE INFECTED RECOVERED (SIR) MODEL FOR ESTIMATING COVID-19 REPRODUCTION NUMBER IN EAST KALIMANTAN AND SAMARINDA Sifriyani, Sifriyani; Rosadi, Dedi
MEDIA STATISTIKA Vol 13, No 2 (2020): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.13.2.170-181

Abstract

Modeling and analysis of Covid-19 data, especially on the modeling the spread and the prediction of the total number of cases for Indonesian data, has been conducted by several researchers. However, to the best of our knowledge, it has not been studied specifically for East Kalimantan Province data. The study of the data on the level of provincial and District/City level could help the government in making policies. In this study, we estimate the Covid-19 reproduction number, calculate the rate of recovery, the rate of infection, and the rate of death of East Kalimantan Province and Samarinda City. We also provide a prediction of the peak of the infection cases and forecast the total incidence of Covid-19 cases until the end of 2020. The model used in this research is the Susceptible Infected Recovered (SIR) model and the data used in the study was obtained from the East Kalimantan Public Health Office.
Geographically Weighted Spline Nonparametric Regression dengan Fungsi Pembobot Bisquare dan Gaussian Pada Tingkat Pengangguran Terbuka Di Pulau Kalimantan Ilmi, Hillidatul; Sifriyani; Prangga, Surya
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 14 No 2 (2021): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Fakultas Sains dan Teknologi Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (469.063 KB) | DOI: 10.36456/jstat.vol14.no2.a4470

Abstract

Geographically weighted spline nonparametric regression merupakan pengembangan regresi nonparametrik untuk data spasial dengan estimator parameter bersifat lokal setiap lokasi pengamatan yang diaplikasikan pada kasus tingkat pengangguran terbuka. Tingkat pengangguran terbuka menjadi alat ukur kualitas kesejahteraan di suatu wilayah yang mengindikasikan besarnya persentase penduduk usia kerja yang aktif secara ekonomi. Tujuan penelitian ini yaitu untuk mengidentifikasi faktor-faktor yang mempengaruhi tingkat pengangguran terbuka 56 Kabupaten/Kota di Kalimantan. Metode yang digunakan adalah geographically weighted spline nonparametric regression dengan pembobot fungsi kernel eksponensial. Model terbaik geographically weighted spline nonparametric regression dengan pembobot fungsi kernel eksponensial pada orde 1 titik knot 1 dengan nilai R-Square sebesar 86,410 persen, nilai AIC sebesar 12,152, nilai RMSE sebesar 0,584 serta nilai CV terkecil adalah fungsi kernel bisquare sebesar 77,175. Adapun faktor-faktor yang berpengaruh signifikan terhadap tingkat pengangguran terbuka yaitu tingkat partisipan angkatan kerja, jumlah penduduk, indeks pembangunan manusia, harapan lama sekolah dan upah minimum.
Analysis Of The Effect Of Net Profit, Operational Cash Flow, Free Cash Flow, Previous Year Cash Dividends On Cash Dividends In The Indonesia Stock Fatia Fatimah; Sifriyani; Deni sunaryo; Etty Puji lestari
International Journal of Science, Technology & Management Vol. 3 No. 1 (2022): January 2022
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v3i1.450

Abstract

This study aims to determine the analysis of the effect of net income, operating cash flow, free cash flow, cash dividends in the previous year, on cash dividends. This study uses a food and beverage sub-sector research design. The research population amounted to 18 companies for 5 years from 2014-2018 and were picked up by 7 companies in a row to publish their financial statements. The method used in this data analysis using multiple linear regression analysis. Based on the results of the study, it can be concluded that: net income has no effect on cash dividends, operating cash flow has no effect on cash dividends, free cash flow has no effect on cash dividends, previous year's cash dividends have an effect on cash dividends.recommendations The company should pay attention to the cash dividend payments in previous years as an independent variable that affects the current year's cash dividend. Because the company will be attractive to shareholders whose preferences are related to dividend payout and stability. Investors want a stable dividend as a source of income embedded in shares that are paid the same amount of dividends every period. For further researchers, it is better to add the number of samples in the observation period of 6 years or 7 years, adding other variables such as Analyzing the relationship between Net profit, Operating Cash Flow with cash dividends, or Effect of accounting profit, cash profit, Free Cash Flow, Operating Cash Flow, leverage and current ratio to cash dividend. and can expand the research sample, not only to manufacturing companies but to more than one type of company.
MODEL NONPARAMETRIC GWR UNTUK IDENTIFIKASI FAKTOR YANG MEMPENGARUHI COD DAS MAHAKAM Clemensius Arles; Sifriyani Sifriyani; Fidia Deny Tisna Amijaya
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 21, No 1 (2021)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v21i1.7706

Abstract

ABSTRAKModel Regresi Spline Nonparametrik dengan Pembobot Geografis merupakan pengembangan model regresi nonparametrik untuk data spasial dengan estimator parameter bersifat lokal untuk setiap pengamatan yang di aplikasikan pada data spasial. Data penelitian ini merupakan data sekunder yang diperoleh dari Dinas Lingkungan Hidup Provinsi Kalimantan Timur Samarinda. Tujuan penelitian ini adalah menentukan model pada data Chemical Oxygen Demand (COD) di Daerah Aliran Sungai Mahakam Kalimantan Timur dan untuk mengetahui faktor-faktor apa saja yang mempengaruhi COD di 28 titik pengambilan sampel pada DAS Mahakam tahun 2018. Pada Metode Regresi Spline Nonparametrik dengan Pembobot Geografis terdapat pemilihan titik knot optimum dengan menggunakan kriteria Generalized Cross-Validation (GCV) yang terkecil. Pembobot spasial yang digunakan adalah fungsi kernel bisquare. Hasil penelitian menunjukkan bahwa faktor-faktor yang berpengaruh terhadap COD di DAS Mahakam adalah Dissolved Oxygen (DO), Nitrit, dan tingkat keasaman pH. Kata Kunci: Chemical Oxygen Demand, Pembobot Geografis, GCV, Knot dan Spline
Regresi Data Panel dengan Pendekatan Common Effect Model (CEM), Fixed Effect model (FEM) dan Random Effect Model (REM) (Studi Kasus: Persentase Penduduk Miskin Menurut Kabupaten/Kota di Kalimantan Timur Tahun 2015-2018) Eka Nur Amaliah; Darnah Darnah; Sifriyani Sifriyani
ESTIMASI: Journal of Statistics and Its Application Vol. 1, No. 2, Juli, 2020 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (477.461 KB) | DOI: 10.20956/ejsa.v1i2.10574

Abstract

Panel data regression is a regression that combines cross section data and time series data. Panel data regression estimation can be done through 3 estimates namely CEM, FEM and REM. This research will make a modeling of the percentage of poor people according to regencies / cities in East Kalimantan using panel data regression analysis. Poverty occurs due to lack of income and assets to meet basic needs. For this reason, variables that are assumed to affect the percentage of the poor are used, including the Population Growth Rate (LPP), Human Development Index (HDI), and Adjustable Per capita Expenditure (PPD). By using 3 CEM, FEM and REM approaches based on testing, the best FEM model is obtained. Based on the FEM model the factors that significantly influence are the HDI and PPD. A value of 0.7755 means that the HDI and PPD can explain the percentage of poor people according to the Regency / City in East Kalimantan of 77.55% while the remaining 22.45% is influenced by other variables not yet included in the model.
Geographically Weighted Spline Nonparametric Regression dengan Fungsi Pembobot Bisquare dan Gaussian Pada Tingkat Pengangguran Terbuka Di Pulau Kalimantan Hillidatul Ilmi; Sifriyani; Surya Prangga
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 14 No 2 (2021): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (469.063 KB) | DOI: 10.36456/jstat.vol14.no2.a4470

Abstract

Geographically weighted spline nonparametric regression merupakan pengembangan regresi nonparametrik untuk data spasial dengan estimator parameter bersifat lokal setiap lokasi pengamatan yang diaplikasikan pada kasus tingkat pengangguran terbuka. Tingkat pengangguran terbuka menjadi alat ukur kualitas kesejahteraan di suatu wilayah yang mengindikasikan besarnya persentase penduduk usia kerja yang aktif secara ekonomi. Tujuan penelitian ini yaitu untuk mengidentifikasi faktor-faktor yang mempengaruhi tingkat pengangguran terbuka 56 Kabupaten/Kota di Kalimantan. Metode yang digunakan adalah geographically weighted spline nonparametric regression dengan pembobot fungsi kernel eksponensial. Model terbaik geographically weighted spline nonparametric regression dengan pembobot fungsi kernel eksponensial pada orde 1 titik knot 1 dengan nilai R-Square sebesar 86,410 persen, nilai AIC sebesar 12,152, nilai RMSE sebesar 0,584 serta nilai CV terkecil adalah fungsi kernel bisquare sebesar 77,175. Adapun faktor-faktor yang berpengaruh signifikan terhadap tingkat pengangguran terbuka yaitu tingkat partisipan angkatan kerja, jumlah penduduk, indeks pembangunan manusia, harapan lama sekolah dan upah minimum.
Pemodelan Regresi Nonparametrik Spline Linear Persentase Penduduk Miskin di Kalimantan Wianita Noviani; Sifriyani Sifriyani; Ika Purnamasari
Jurnal Siger Matematika Vol 1, No 2 (2020)
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (246.686 KB) | DOI: 10.23960/jsm.v1i2.2565

Abstract

Pengenalan Pojok Statistik Sejak Dini dan Ilmu Data Sains Bagi Siswa dan Guru di SMAN Kota Samarinda Meirinda Fauziyah; Sifriyani Sifriyani; Sri Wahyuningsih; Suyitno Suyitno; Andrea Tri Rian Dani; Siti Mahmuda; Hadi Koirudin
Journal of Research Applications in Community Service Vol. 2 No. 3 (2023): Journal of Research Applications in Community Service
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/jarcoms.v2i3.2263

Abstract

Pendidikan merupakan bentuk usaha sadar seseorang untuk mengembangkan potensi diri agar memiliki kekuatan spiritual, keagamaan, serta keterampilan diri. Pada masa kini keterampilan diri terfokus dalam urgensi data yang banyak dibutuhkan di sektor industri dengan keahlian menganalisis masalah dan menghasilkan insight untuk menjawab kepentingan manusia di masa depan dengan mengenal ilmu data sains. Data sains merupakan cabang ilmu gabungan dari statistika, pendekatan sains, Artificial Intelligence (AI) untuk menganalisis sebuah big data sampai menghasilkan kesimpulan yang mudah dipahami. Tujuan kegiatan PKM ini memberikan pemahaman informasi pojok statistik sebagai wadah ilmu statistik kepada siswa dan guru sejak dini, membagikan informasi pengembangan ilmu data sains terkini menjadi seorang data scientist. Pelaksanaan kegiatan ini menggunakan metode Participatory Learning and Action (PLA) dengan melibatkan siswa/siswi dan guru. Hasil dari kegiatan ini menunjukkan bahwa terdapat perbedaan pemahaman sebelum dan setelah diberikan pemahaman ilmu data sains.
Comparison K-Means and Fuzzy C-Means In Regencies/Cities Grouping Based on Educational Indicators Gerald Claudio Messakh; Memi Nor Hayati; Sifriyani Sifriyani
Jurnal Varian Vol 7 No 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i1.2879

Abstract

Cluster analysis is an analysis that aims to classify data based on the similarity of specific characteristics. The methods used in this research are K-Means and Fuzzy C-Means (FCM). K-Means is a partition-based non-hierarchical data grouping method. FCM is a clustering technique in which the existence of each data is determined by the degree of membership. The purpose of this study is to classify regencies/cities in Kalimantan based on education indicators in 2021 using K-Means and FCM and find out which method is better to use between K-Means and FCM based on the standard deviation ratio so it can be used efficiently and effectively for decision making by the government to advance the level of education on the island of Kalimantan. Based on the results of the analysis, it's concluded that K-Means is the better method with the ratio of the standard deviation within a cluster against the standard deviation between clusters of 0.6052 which produces optimal clusters of 2 clusters, namely the first cluster consisting of 14 Regencies/Cities, while the second cluster consists of 42 Regencies/Cities in Kalimantan.
Regresi Nonparametrik Multivariabel dengan Pendekatan Spline Truncated pada Kasus Tuberculosis Muhammad Hunaipi Pratama; Sifriyani; Darnah Andi Nohe
Statistika Vol. 22 No. 1 (2022): 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.v22i1.506

Abstract

ABSTRAK Regresi nonparametrik merupakan suatu metode statistika yang digunakan untuk mengetahui pola hubungan antara variabel prediktor dengan respon ketika tidak diketahui bentuk fungsi regresinya dimana kurva regresi hanya diasumsikan smooth. Spline truncated adalah suatu pendekatan ke arah pencocokan data dengan tetap memperhitungkan kemulusan kurva yang memiliki sifat tersegmen kontinu sehingga memberikan fleksibilitas dan efektif menyesuaikan diri dalam menjelaskan karakteristik lokal dari fungsi data. Tujuan penelitian ini adalah untuk mendapat model regresi nonparameterik multivariabel dengan pendekatan spline truncated dan mengetahui faktor-faktor yang berpengaruh terhadap jumlah kasus tuberculosis di Kalimantan Timur, Kalimantan Selatan dan Kalimantan Barat tahun 2019. Hasil menunjukkan bahwa model regresi nonparametrik spline truncated terbaik dalam memodelkan jumlah kasus tuberculosis adalah dengan tiga titik knot. Model ini memiliki nilai generalized cross validation (GCV) yang paling minimum sebesar 40.813,24, dengan nilai R2 sebesar 95,84%. Berdasarkan hasil pengujian signifikansi parameter model, disimpulkan bahwa faktor-faktor yang memengaruhi jumlah kasus tuberculosis di Kalimantan Timur, Kalimantan Selatan dan Kalimantan Barat tahun 2019 adalah persentase penduduk miskin, persentase tenaga kesehatan terlatih, persentase keluarga memperoleh sanitasi, dan persentase gizi buruk masyarakat. ABSTRACT Nonparametric regression is a statistical method used to determine the pattern of the relationship between the predictor variable and the response when the form of the regression function is unknown where the regression curve is only assumed to be smooth. The truncated spline is an approach towards data matching while taking into account the smoothness of the curve which has continuous segmented properties so as to provide flexibility and effectively adapt to explain the local characteristics of the data function. The purpose of this study was to obtain a multivariable nonparametric regression model with a spline truncated approach and find out the factors that influence the number of tuberculosis cases in East Kalimantan, South Kalimantan and West Kalimantan in 2019 using the data from Indonesian Central Bureau of Statistics. The results show that the spline truncated nonparametric regression model is the best in modeling the number of cases. tuberculosis is with three point knots. This model has the minimum generalized cross validation (GCV) value of 40,813.24, with an R2 value of 95.84%. Based on the results of testing the significance of the model parameters, it was concluded that the factors that influenced the number of tuberculosis cases in East Kalimantan, South Kalimantan and West Kalimantan in 2019 were the percentage of poor people, the percentage of trained health workers, the percentage of families receiving sanitation, and the percentage of poor nutrition in the community.
Co-Authors A'yun, Qonita Qurrota Afriani, Nur Alam, Muhammad Zainul Andrea Tri Rian Dani Andrea Tri Rian Dani Anggraeni, Sitti Anisar, Anggi Putri Asnita, Asnita Astafira, Ilyas Aufi, Tresna Restu Bahriah, Ayu Chairunnisa, Nurul Rizky Clemensius Arles Damayanti, Elok Dani, Andrea Dani, Andrea Tri Rian Darnah Andi Nohe Darnah, Darnah Dedi Rosadi Deni Sunaryo Eka Nur Amaliah Erlyne Nadhilah Widyaningrum Etty Puji Lestari Fachrian Bimantoro Putra Fadlirhohim, Rizki Dwi Fatia Fatimah Fauziyah, Meirinda Febriana Rinda Sihotang Febriyani, Eka Riche Fidia Deny Tisna Amijaya Gerald Claudio Messakh Hadi Koirudin Hidayanty, Nurul Ilma Hillidatul Ilmi I Nyoman Budiantara Ika Purnamasari Ilmi, Hillidatul Kesuma, Ahmad Rizky Khotimah, Ariska Khusnul Kosasih, Raditya Arya Lestari, Tri Septi Ayu M. Fariz Fadillah Mardianto Mahmuda, Siti Mar'ah, Zakiyah Mar’ah, Zakiyah Meirinda Fauziyah Memi Nor Hayati Memi Nor Hayati Messakh, Gerald Claudio Mohammad Nurul Huda Muhammad Aldani Zen Muhammad Hunaipi Pratama Mumtaz, Ghina Fadhilla Nabilla, Maghrisa Ayu Nadia Serena NARITA YURI ADRIANINGSIH Nariza Wanti Wulan Sari Novalia, Viona Nugraha, Pratama Yuly Nur, Yumi Handayani Nuraini, Ulfa Siti Nurmayanti, Wiwit Pura Padatuan, Aprianti Boma Pangruruk , Thesya Atarezcha Pangruruk Paradilla, Yunda Sasha Pasarella, Muhammad Danil Purnaraga, Tirta Putra, Fachrian Bimantoro Putri, Asyifa Charmadya Rabiatul Adawiyah Rahman, Athaya Azahra Rahmania Rahmania Rinanda, Farikah Ayu Risti Raihani Rito Goejantoro, Rito Saputri, Marisa Nanda Sari, Ar Ruum Mia Saska, Indria Siti Mahmuda SITI MAHMUDAH Sitohang, Frans Karta Sayoga Sri Wahyuningsih Sri Wahyuningsih Surya Prangga Suyitno Suyitno Suyitno Suyitno Tutik Handayani Tutik Handayani Vita Ratnasari Wasono, Wasono Wianita Noviani Wiyli Yustanti Yuniarti, Desi Zarkasi, Rifka Nurfaiza