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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Sains Dasar Jurnal Analisa Sosiologi Jurnal Equation: Teori dan Penelitian Pendidikan Matematika ProBisnis : Jurnal Manajemen Quadratic: Journal of Innovation and Technology in Mathematics and Mathematics Education International Journal of Computing Science and Applied Mathematics-IJCSAM
Nurtiyasari, Devi
UIN Sunan Kalijaga Yogyakarta
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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 1 
THE APPLICATION OF DEEP NEURAL NETWORK FOR BREAST CANCER CLASSIFICATION Devi Nurtiyasari; Abdurakhman Abdurakhman; Muhamad Rashif Hilmi
Jurnal Sains Dasar Vol 7, No 1 (2018): April 2018
Publisher : Faculty of Mathematics and Natural Science, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (272.384 KB) | DOI: 10.21831/jsd.v7i1.22237

Abstract

Breast cancer is one of the most common cancers, especially for women. Early detection of breast cancer may increase the survival rate of patients significantly. Detecting breast cancer from breast image can be done by classification process. There are so many classification models which can be used for the classification process, such as neural network, fuzzy, neuro fuzzy, wavelet neural network, wavelet neuro fuzzy, etc. This research propose one of the neural network variant, i.e. Deep Neural Network. This kind of neural network model is using at least two hidden layers on the network. The more hidden layers used the deeper the neural network will be. The architecture of Deep Neural Network used in this research is feedforward network. Classification of breast tumor using Deep Neural Network model provides results with sensitivity, specificity, and accuracy were respectively 100%, 100%, and 66.67% for training data and 100%, 20%, and 60% for testing data. Keywords: breast cancer, Deep Neural Network
Efektivitas Pembelajaran Daring Menggunakan Google Classroom pada Mata Kuliah Statistika Penelitian Pendidikan Matematika Lintang Ega Shavira; Zahrina Salsabila; Muhammad Nauval Muwaffiq; Devi Nurtiyasari, S.Si., M.Sc.
Jurnal Equation: Teori dan Penelitian Pendidikan Matematika Vol 5, No 1 (2022)
Publisher : IAIN BENGKULU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29300/equation.v5i1.5882

Abstract

Pengunaan Goggle Classroom cukup terkenal dalam pendidikan di masa pandemi. Google Classroom menjadi sarana atau media yang dipilih untuk kegiatan proses pembelajaran daring yang dilakukan pada mata kuliah statistika penelitian pendidikan Matematika UIN Sunan Kalijaga Yogyakarta. Jenis penelitian ini adalah penelitian kuantitatif dengan metode deskriptif kuantitatif yang bertujuan untuk memberikan gambaran tentang keefektifan pembelajaran daring pada mata kuliah Statistika Penelitin Pendidikan Matematika dengan menggunakan Google Classroom. Data pada penelitian ini diperoleh dari jawaban-jawaban responden dalam mengisi kuisioner (angket). Terdapat 23 Responden yang menjadi sampel dengan menggunakan teknik Convenience Sampling. Data tersebut kemudian diolah dengan menggunakan analisis deskriptif statistik dan dilanjutkan dengan uji hipotesis menggunakan one sample t-test. Setelah data di analisis, makadiperoleh kesimpulan bahwa penggunaan Google Classroom dalam pembelajaran daring pada mata kuliah Statistika Penelitian Pendidikan Matematika dikatakan efektif.
ACEHNESE AWARENESS OF PHYSICAL DISTANCING POLICY DUE TO COVID-19 Angga Syahputra; Devi Nurtiyasari; Zani Anjani
Jurnal Analisa Sosiologi Vol 10, No 1 (2021)
Publisher : UNIVERSITAS SEBELAS MARET (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jas.v10i1.45160

Abstract

Corona Virus Disease 2019 (Covid-19) has spread to more than 190 countries around the world. Covid-19 in Indonesia was first reported on March 2, 2020, i.e. as much as 2 cases. As of June 12, 2020, there were 36.406 confirmed cases (positive) and 2048 deaths cases. In Aceh, as of June 12, 2020, there were 115 total cases with 20 confirmed cases (positive) and 1 death case. In dealing with Covid-19, Indonesia Government has issued various policies based on studies of expertise and direction from the World Health Organization (WHO). One of the policies is to implement Physical Distancing. This policy becomes a challenge to be implemented in Indonesia. The Aceh Provincial Government also urged citizens to implement this policy. This study conducted to see the factors affecting Acehnese awareness in implementing Physical Distancing policy. The result shows that it is significantly affected by job factor, whereas other factors such as age and salary have no significant effect. Keywords: Covid-19; Society Awareness; Public Awareness; Physical Distancing AbstrakVirus Covid-19 telah menyebar ke lebih dari 190 negara di dunia. Covid-19 di Indonesia pertama kali dilaporkan pada 2 Maret 2020 yaitu sebanyak 2 kasus. Hingga 12 Juni 2020, terdapat 36.406 kasus terkonfirmasi (positif) dan 2048 kasus kematian. Di Aceh, per 12 Juni 2020, terdapat total 115 kasus dengan 20 kasus terkonfirmasi (positif) dan 1 kasus kematian. Dalam menangani Covid-19, Pemerintah Indonesia telah mengeluarkan berbagai kebijakan berdasarkan kajian keahlian dan arahan dari Organisasi Kesehatan Dunia (WHO). Salah satu kebijakannya adalah dengan menerapkan physical distancing social. Kebijakan ini menjadi tantangan untuk diterapkan di Indonesia. Pemerintah Provinsi Aceh pun mengimbau warganya menerapkan kebijakan ini. Penelitian ini dilakukan untuk melihat faktor-faktor yang mempengaruhi kesadaran masyarakat Aceh dalam menerapkan kebijakan menjaga jarak fisik. Hasil penelitian menunjukkan bahwa faktor pekerjaan dipengaruhi secara signifikan, sedangkan faktor lain seperti umur dan gaji tidak berpengaruh signifikan. Kata Kunci: Covid-19; Kesadaran Masyarakat; Kesadaran Publik; Jarak Fisik.
METODE ANALYTIC NETWORK PROCESS UNTUK MENYUSUN STRATEGI PEMBERDAYAAN EKONOMI PESANTREN SUMATERA UTARA DI ERA NEW NORMAL Devi Nurtiyasari; Angga Syahputra; Ardhina Wijayanti
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 10, No 1 (2022): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.10.1.2022.15-25

Abstract

Pesantren, juga dikenal sebagai Islamic boarding school, ada di tengah-tengah masyarakat sebagai lembaga pendidikan Islam dan lembaga penyiaran sosial-agama dan ekonomi. Pesantren memiliki sejarah panjang dalam mengembangkan ekonomi kerakyatan. Pesantren di Sumatera Utara diperkirakan sudah ada sejak tahun 1912 ketika Pesantren Musthafawiyah Purba Baru didirikan. Data Kementerian Agama Republik Indonesia menunjukkan 183 pesantren di Sumatera Utara yang tersebar di 23 kabupaten/kota pada 2019. Menghadapi era globalisasi di tengah perbaikan ekonomi di era new normal, pesantren harus lebih dinamis tanpa kehilangan karakteristik utamanya, yaitu kemampuan di bidang pengetahuan agama. Optimalnya pemberdayaan ekonomi pesantren di Sumatera Utara akan membuat pesantren memiliki daya saing industri. Merumuskan strategi pemberdayaan ekonomi pesantren di Sumatera Utara diawali dengan mendeskripsikan kendala yang dialami berdasarkan hasil kajian dan observasi di lapangan. Kemudian, berdasarkan kendala tersebut, dirumuskan strategi yang dapat diterapkan untuk mengoptimalkan pemberdayaan ekonomi pesantren. Penelitian ini bertujuan untuk menganalisis kendala pesantren dan strategi pemberdayaan dengan menggunakan kajian ilmiah, yaitu dengan menggunakan metode Analytic Network Process (ANP). Hasil analisis menggunakan metode ANP diharapkan dapat digunakan untuk merumuskan kebijakan agar lebih fokus. Selain itu, hasilnya diharapkan dapat dimanfaatkan oleh pesantren dan stakeholder untuk memaksimalkan peran pesantren dalam mengembangkan industri halal dan mendorong pemulihan ekonomi.
The Application of Logistic Regression to Measure the Impact of Covid-19 Pandemic on Household Credit Financing Nurtiyasari, Devi Nurtiyasari; Syahputra, Angga; Hilmi, Rashif
Quadratic: Journal of Innovation and Technology in Mathematics and Mathematics Education Vol. 1 No. 2 (2021): October 2021
Publisher : Pusat Studi Pengembangan Pembelajaran Matematika Sekolah UIN Sunan Kalijaga Yogyakarta Jl. Marsda Adisucipto, Yogyakarta 55281

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/quadratic.2021.012-01

Abstract

The spread of the Covid-19 outbreak has a direct impact on the economic sector. The impact of Covid-19 on the economic sector can be seen from Non-Performing Loans (NPL). Credit financing affects the Financial System Stability. Furthermore, households are the sector most affected by Covid-19, because household income is obtained from other sectors that are also affected by the spread of Covid-19. This impact can be seen in terms of income, savings/assets, and consumption. This study aims to analyze the impact of Covid-19 as measured by the variables of income, savings/assets, and consumption on household credit financing using the Logistic Regression Model. The modelling results show that the consumption and savings variables do not have a significant effect on household credit financing, while the income variables have a significant effect and are able to predict 15.5% of the variability of household credit financing. Furthermore, based on the odds ratio value of the model, information is obtained that the effect of decreased household income during the Covid-19 pandemic affected one time on the value of the odds ratio for household credit financing. Overall, the model was able to predict the data correctly by 81.4%.
Pemanfaatan Skewness dan Kurtosis dalam Menentukan Harga Opsi Beli Asia Muhamad Rashif Hilmi; Devi Nurtiyasari; Angga Syahputra
Quadratic: Journal of Innovation and Technology in Mathematics and Mathematics Education Vol. 2 No. 1 (2022): April 2022
Publisher : Pusat Studi Pengembangan Pembelajaran Matematika Sekolah UIN Sunan Kalijaga Yogyakarta Jl. Marsda Adisucipto, Yogyakarta 55281

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/quadratic.2022.021-02

Abstract

Opsi Asia adalah opsi dimana besar perhitungan keuntungannya menggunakan rata-rata harga aset selama periode kontrak. Penentuan harga Opsi Asia yang umum digunakan adalah dengan metode Black-Scholes. Metode Black-Scholes mempunyai beberapa syarat yang harus terpenuhi, salah satunya adalah logaritma dari rata-rata harga aset berdistribusi normal atau nilai skewness dan kurtosis tidak normal. Dalam aplikasinya, sangat sedikit kasus dimana syarat ini terpenuhi . Salah satu solusi dari permasalahan ini adalah memasukkan nilai skewness dan kurtosis kedalam model. Model ini menggunakan ekspansi Gram-Charlier untuk menambahkan nilai skewness dan kurtosis kepada rumus Black-Scholes. Harga Opsi Asia yang diperoleh adalah harga opsi Asia metode Black-Scholes ditambah dengan persamaan yang berhubungan dengan skewness dan kurtosis yang tidak normal. Dalam studi kasus dilakukan perbandingan harga Opsi Asia metode Black-Scholes dengan ekspansi Gram-Charlier dimana data yang digunakan adalah data simulasi dan diperoleh kesimpulan nilai skewness dan kurtosis dapat mempengaruhi harga Opsi beli Asia dengan Metode Black-Scholes.
Analisis pengelolaan Jurnal Polynom sebagai Wadah Publikasi Karya Tulis Mahasiswa Ramadani, Iqbal; Nurtiyasari, Devi
ProBisnis : Jurnal Manajemen Vol. 15 No. 6 (2024): December: Management Science
Publisher : Lembaga Riset, Publikasi dan Konsultasi JONHARIONO

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

Abstract

A scientific journal can be interpreted as the outcome of studies or research published periodically through educational and research institutions. Polynom is a journal from the mathematics education program, specifically serving as a platform for student publications, particularly those from the mathematics education program at UIN Sunan Kalijaga. However, the Polynom Journal, as a platform for student scientific publications, does not simply publish student works without a quality review process. This is because it will impact the accreditation of the journal itself. The purpose of this research is to understand the management strategies of the Polynom journal as a student journal that adheres to National Journal Accreditation and Program Accreditation. The research method used is descriptive qualitative. The researcher carried out several research steps, including collecting data from the Polynom journal's dashboard, interviewing journal managers, and analyzing data. The Polynom Journal, as a student journal, has implemented strategies that adhere to national journal accreditation and program accreditation. However, the applied strategies have not been fully implemented. The peer reviewers at the Polynom Journal are already more than 50% from outside UIN Sunan Kalijaga, but the manuscript reassessment process has not yet been fully implemented. There is already a publication workflow, but it has not run optimally. Nevertheless, the Polynom Journal has established good writing guidelines, consistent writing style, and good regularity.
The Dynamics of Stock Price Change Motion Effected by Covid-19 Pandemic and the Stock Price Prediction Using Multi-layered Neural Network Zani Anjani Rafsanjani; Devi Nurtiyasari; Angga Syahputra
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 7 No. 1 (2021)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

In this paper, we work on the analysis of dynamical change on stock price during Covid-19 pandemic using nonlinear deterministic motion equation. The model is given by the second-order differential equation with constant coefficient over time with some consideration under stock market structure. This coefficient shows the rate of change of stock price throughout Covid-19. Thus, the Least Square estimator is derived to determine the constant factor. Further, we conduct the Multi layered Neural Network algorithm to predict the future stock price. To provide accurate forecasting results, the algorithm used in this paper has to be able to recognize stock price data pattern which has dynamic characteristics. Multi-layered Neural Network solve the data with dynamic characteristics by using more than one hidden layer. The input layers of this network are not directly connected to the output layers of the network. Therefore, this algorithm is expected to provide accurate forecasting results. We use the Jakarta Composite Stock Price Index (IHSG) and Waskita Karya Company stock price's data for the subject of observation.
Co-Authors Abdurakhman Abdurakhman Agus Indra Gunawan Angga Syahputra Ardhina Wijayanti Hilmi, Rashif Iqbal Ramadani Lintang Ega Shavira Muhamad Rashif Hilmi Muhamad Rashif Hilmi Muhammad Nauval Muwaffiq Sukiyanto Sukiyanto Syahputra, Angga Syahputra, Angga Zahrina Salsabila Zani Anjani Zani Anjani Rafsanjani Zani Anjani Rafsanjani HSM