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All Journal International Journal of Electrical and Computer Engineering Jurnal Sains dan Seni ITS MUST: Journal of Mathematics Education, Science and Technology Journal of Computer, Electronic, and Telecommunication (COMPLETE)
Siti Maghfirotul Ulyah
Airlangga University
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Mathematics

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The Comparative Study for Predicting Disease Outbreak faricha, anifatul; M. Achirul Nanda; Siti Maghfirotul Ulyah; Ni'matut Tamimah; Enny Indasyah; Robin Addwiyansyah Alvaro Samrat
Journal of Computer, Electronic, and Telecommunication (COMPLETE) Vol. 1 No. 1 (2020): July
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/complete.v1i1.48

Abstract

To know the prediction of disease outbreak, proper predictive modeling is required to represent the dataset. This study presents the comparative predictive modeling for predicting disease outbreak using two models i.e., optimizable support vector machine (SVM) and optimizable gaussian process regression (GPR). The dataset used in this study contains three cases i.e., positive cases, recovered cases, and death cases. The dataset at each case is divided into training dataset for the training process and external validation dataset for the validation process. Based on the training process and validation process, the root mean square error (RMSE) at positive cases, recovered cases, and death cases using optimizable GPR is substantially more effective for prediction than the optimizable SVM. According to the result performance, by applying optimizable GPR, the training process has the average RMSE of 19.54 and the validation process has the average RMSE of 15.85.
The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia Muhammad Achirul Nanda; Anifatul Faricha; Siti Maghfirotul Ulyah; Ni'matut Tamimah; Enny Indasyah; Muhammad Falahudin Malich Salaz; Qurrotun 'Ayun Mawadatur Rohmah; Ulfah Abqari
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2900-2910

Abstract

The COVID-19 epidemic has spread massively to almost all countries including Indonesia, in just a few months. An important step to overcoming the spread of the COVID-19 is understanding its epidemiology through mathematical modeling intervention. Knowledge of epidemic dynamics patterns is an important part of making timely decisions and preparing hospitals for the outbreak peak. In this study, we developed the susceptible-infected-recovered-dead (SIRD) model, which incorporates the key epidemiological parameters to model and estimate the long-term spread of the COVID-19. The proposed model formulation is data-based analysis using public COVID-19 data from March 2, 2020 to May 15, 2021. Based on numerical analysis, the spread of the pandemic will begin to fade out after November 5, 2021. As a consequence of this virus attack, the cumulative number of infected, recovered, and dead people were estimated at ≈ 3,200,000, ≈ 3,437,000 and ≈ 63,000 people, respectively. Besides, the key epidemiological parameter indicates that the average reproduction number value of COVID-19 in Indonesia is 7.32. The long-term prediction of COVID-19 in Indonesia and its epidemiology can be well described using the SIRD model. The model can be applied in specific regions or cities in understanding the epidemic pattern of COVID-19.
Peramalan Volume Penjualan Total Sepeda Motor di Kabupaten Bojonegoro dan Lamongan dengan Pendekatan Model ARIMAX dan VARX Siti Maghfirotul Ulyah; Destri Susilaningrum; Suhartono Suhartono
Jurnal Sains dan Seni ITS Vol 3, No 2 (2014)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (516.866 KB) | DOI: 10.12962/j23373520.v3i2.8148

Abstract

Sepeda motor merupakan salah satu alat transportasi yang banyak diminati oleh masyarakat Indonesia. Penelitian ini bertujuan untuk mengetahui karakteristik penjualan total sepeda motor jenis Automatic, Cub, dan Sport di Kabupaten Bojonegoro dan Lamongan, serta mendapatkan model ramalannya untuk tahun 2014. Model yang digunakan adalah model ARIMAX dan VARX. Hasil penelitian menunjukkan bahwa secara umum penjualan total sepeda motor dipengaruhi oleh Hari Raya Idul Fitri dan bulan tahun ajaran baru, serta terdapat siklus musiman. Selain itu, terdapat keterkaitan penjualan sepeda motor antar jenis di kabupaten yang sama, dan juga antar jenis di kabupaten yang berbeda. Hasil ramalan tahun 2014 menunjukkan bahwa masih terdapat kenaikan pada sepeda motor jenis Automatic dan Sport. Sebaliknya, terjadi penurunan pada jenis Cub.
Analisis Hubungan Penggunaan Media Sosial terhadap Inovasi Pengembangan Bisnis di Masa Pandemi Coronavirus Disease - 19 Syehvira Shal Shabilla; Diah Puspita Ningrum; Ayuning Dwis Cahyasari; Siti Maghfirotul Ulyah
MUST: Journal of Mathematics Education, Science and Technology Vol 6, No 2 (2021): DECEMBER
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/must.v6i2.10665

Abstract

Data Badan Pusat Statistik (BPS) pada triwulan III tahun 2020 menyatakan bahwa perekonomian Indonesia mengalami resesi dengan pertumbuhan sebesar -3,49 persen. Hal ini mengartikan bahwa pandemi Coronavirus Disease (Covid-19) berdampak pada kondisi ekonomi di Indonesia. Dalam laporan World Economic Forum (WEF) menunjukkan bahwa nilai terendah Indonesia terletak pada indikator kemampuan inovasi sebesar 37.7 tepatnya di peringkat ke-74. Hal ini dapat mengganggu salah satu tujuan Sustainable Development Goals (SDGs) yaitu menjaga kestabilan pertumbuhan ekonomi yang salah satunya bagi negara berkembang seperti Indonesia. Namun, survei Katadata Insight Center (KIC) menyatakan bahwa marketplace membantu pebisnis di masa pandemi. Berdasarkan hal tersebut penelitian ini dilakukan untuk mengetahui hubungan media sosial terhadap inovasi pengembangan bisnis dalam membantu perekonomian di masa pandemi Covid-19 yang diuji dengan analisis statistika deskriptif dan uji Wilcoxon. Analisis statistika deskriptif bertujuan untuk memberikan gambaran dari hasil survei terkait penggunaan sosial media dan inovasi dalam berbisnis berdasarkan nilai maksimum dan minimum. Uji Wilcoxon dilakukan untuk menganalisis perbedaan pendapatan rata – rata baik sebelum dan selama pandemi serta sebelum dan sesudah pelaku bisnis melakukan inovasi untuk mengembangkan bisnisnya di masa pandemi. Hasil analisis menunjukkan bahwa terdapat perbedaan pendapat baik sebelum dan selama pandemi maupun sebelum dan sesudah berinovasi. Hal ini mengindikasikan bahwa dengan adanya keterkaitan sosial media terhadap inovasi pengembangan bisnis dapat membantu perekonomian di masa pandemi Covid-19 berbasis digital yang nantinya dapat dijadikan acuan pemerintah dalam meningkatkan sektor ekonomi.
Improving the Competency of High School Teachers in Understanding and Designing Questions Based on Minimum Competency Assessment in Babat Lamongan District Siti Maghfirotul Ulyah; Sediono Sediono; Elly Ana; Noviatus Sholihah; Khoirun Niswatin
MUST: Journal of Mathematics Education, Science and Technology Vol 6, No 1 (2021): JULY
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/must.v6i1.7773

Abstract

One of the latest topics in the world of education is the presentation of policies regarding the replacement of the National Examination (UN) into a Minimum Competency Assessment (AKM) and a character survey by the Minister of Education and Culture. With the new policy, all schools and school residents must make preparations as early as possible. Because this policy has never been implemented before, most educators (teachers) do not have sufficient insight into AKM. Therefore, it is necessary to conduct research on teacher competence in understanding and designing AKM-based questions. Teachers will be given a workshop that aims to provide insight and competence for teachers to prepare for the implementation of AKM in the future with the target of mathematics and science teachers at the state high school level in Babat District (SMAN 1 Babat and MAN 2 Lamongan). Workshops and mentoring for teachers are provided to prepare themselves as pioneers in the implementation of AKM who have the ability to understand and design numeracy category questions. The teachers were given pre-test and post-test during the workshop and the results would be compared and analyzed descriptively with a quantitative approach. The results of the study stated that by giving the workshop, there was an increase in the ability of teachers to understand AKM-based questions by 24.19 points. However, in the ability to design AKM questions, there was only an increase of 5.95 points. Therefore, it is necessary to carry out further post-workshop mentoring. 
Peningkatan Kompetensi Guru SMA/MA di Kecamatan Bungah dalam Sistem Pembelajaran Daring Menggunakan Learning Management System Menuju Terbentuknya Sekolah Digital Siti Maghfirotul Ulyah; Elly Pusporani; Toha Saifudin; Christopher Andreas; Ayuning Dwis Cahyasari
MUST: Journal of Mathematics Education, Science and Technology Vol 6, No 2 (2021): DECEMBER
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/must.v6i2.10667

Abstract

SMA ASSA’ADAH dan MA MA’ARIF NU ASSA’ADAH merupakan sekolah-sekolah yang berlokasi di Kecamatan Bungah, Kabupaten Gresik. Dalam pelaksanaan pembelajaran jarak jauh, sekolah-sekolah tersebut memiliki permasalahan seperti belum efektifnya penggunaan fitur-fitur pada platform pembelajaran online dikarenakan keterbatasan keterampilan guru dan keterbatasan sinyal internet peserta didik dan guru. Oleh karena itu, perlu diberikan pelatihan penggunaan fitur-fitur platform pembelajaran online yang efektif dan interaktif. Tujuan dari penelitian ini adalah untuk mengetahui apakah ada peningkatan kompetensi guru sesudah dilakukan pelatihan tersebut. Penelitian ini dilakukan dengan metode kuantitatif, yaitu dengan mengaplikasikan uji-T berpasangan pada data hasil pre-test dan post-test. Hasil penelitian menunjukkan bahwa rata-rata nilai post-test lebih tinggi daripada nilai pre-test. Hasil pengujian dengan uji-T berpasangan juga menunjukkan bahwa terdapat perbedaan yang signifikan antara kompetensi peserta sebelum dan sesudah pelatihan. Hal ini menunjukan bahwa proses pelatihan efektif meningkatkan kompetensi peserta.
Comparison study of transfer function and artificial neural network for cash flow analysis at Bank Rakyat Indonesia Anifatul Faricha; Siti Maghfirotul Ulyah; Rika Susanti; Hawwin Mardhiana; Muhammad Achirul Nanda; Ilma Amira Rahmayanti; Christopher Andreas
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6635-6644

Abstract

The cash flow analysis is essential to examine the economic flows in the financial system. In this paper, the financial dataset at Bank Rakyat Indonesia was used, it recorded the sources of cash inflow and outflow during a particular period. The univariate time series model like the autoregressive and integrated moving average is the common approach to build the prediction based on the historical dataset. However, it is not suitable to estimate the multivariate dataset and to predict the extreme cases consisting of nonlinear pairs between independent-dependent variables. In this study, the comparison of using two types of models i.e., transfer function and artificial neural network (ANN) were investigated. The transfer function model includes the coefficient of moving average (MA) and autoregressive (AR), which allows the multivariate analysis. Furthermore, the artificial neural network allows the learning paradigm to achieve optimal prediction. The financial dataset was divided into training (70%) and testing (30%) for two types of models. According to the result, the artificial neural network model provided better prediction with achieved root mean square error (RMSE) of 0.264897 and 0.2951116 for training and testing respectively.
Pemodelan Nilai Saham Perusahaan Pertambangan di Indonesia Berdasarkan Metode Generalized Autoregressive Conditional Heteroscedasticity (GARCH) Ayuning Dwis Cahyasari; Sediono Sediono; Elly Ana; M. Fariz Fadillah Mardianto; Elly Pusporani; Siti Maghfirotul Ulyah
MUST: Journal of Mathematics Education, Science and Technology Vol 8 No 1 (2023): JULY
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/must.v8i1.17117

Abstract

Indonesia masih menghadapi tantangan untuk mewujudkan Sustainable Development Goals (SDGs). Salah satunya, upaya dalam mendukung pertumbuhan ekonomi yang inklusif dan berkelanjutan. Peranan pasar modal dianggap penting dalam pembangunan perekonomian sebagai media investasi sehingga dapat memperkuat posisi keuangan pada Industri khususnya dalam negeri. Untuk mewujudkan tujuan dan cita - cita Indonesia perlu diadakan pengoptimalan kegiatan sektor yang bergerak pada bidang pertambangan salah satunya pada saham PT. X yang merupakan salah satu perusahaan pertambangan. Pergerakan naik turun saham dikenal dengan volatilitas harga saham. Volatilitas disebabkan karena kondisi data yang bersifat heteroskedastisitas yang berarti variansi dari residual dapat berubah - ubah  dan tergantung waktu. Saham yang mengalami penurunan secara drastis dapat mempengaruhi kualitas kerja. Salah satu solusi untuk mengatasi permasalahan heteroskedastisitas tersebut adalah dengan menggunakan pendekatan analisis Generalized Autoregressive Conditional Heteroscedasticity (GARCH). Berdasarkan hasil diagnostic checking, didapatkan model GARCH (2,1) yang merupakan model GARCH terbaik, dan didapatkan nilai MAPE sebesar 15,5195% yang termasuk ke dalam kategori prediksi baik. Prediksi dari hasil model terbaik dapat menjadi rekomendasi dan evaluasi bagi pemerintah juga bagi para pelaku kegiatan ekonomi untuk mempersiapkan perencanaan ekonomi yang lebih baik dalam rangka mencapai target memperbaiki ekonomi nasional.
Co-Authors Ana, Elly Anifatul Faricha Ayuning Dwis Cahyasari Ayuning Dwis Cahyasari Ayuning Dwis Cahyasari Christopher Andreas Destri Susilaningrum Diah Puspita Ningrum Elly Pusporani Hawwin Mardhiana Ilma Amira Rahmayanti Indasyah, Enny Khoirun Niswatin M. Fariz Fadillah Mardianto Muhammad Falahudin Malich Salaz Nanda, Muhammad Achirul Ni'matut Tamimah Ni'matut Tamimah Noviatus Sholihah Qurrotun 'Ayun Mawadatur Rohmah Rika Susanti Robin Addwiyansyah Alvaro Samrat Sediono, Sediono Suhartono Suhartono Syehvira Shal Shabilla Toha Saifudin Ulfah Abqari