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All Journal MATEMATIKA Bulletin of Electrical Engineering and Informatics Jurnal Ketahanan Nasional Jurnal Sains Matematika dan Statistika Syntax Literate: Jurnal Ilmiah Indonesia MUST: Journal of Mathematics Education, Science and Technology J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Inferensi Journal of Mathematics Education and Science
Ana, Elly
Statistics Study Program, Faculty Of Science And Technology, University Of Airlangga, Surabaya, Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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MODEL KALIBRASI DENGAN PENDEKATAN WAVELET DAN PARTIAL LEAST SQUARE SERTA PENERAPANNYA DENGAN OSS-R Ana, Elly; chamnidah, Nur; Saifudin, Toha; Atiqi, Aniq; Erfiana, Erfiana
MATEMATIKA Vol 14, No 2 (2011): JURNAL MATEMATIKA
Publisher : MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.646 KB)

Abstract

Determination process of active compound concentration which contained by a drug plant quantitatively and qualitative can know by HPLC (High Performance Liquid Chromatography) and FTIR (Fourier TrasformInfrared)  methods. Calibration aim to find relation between a group of size measure which is relative reached and cheap with a group of other size measure which is difficult and relative costly. Measurement of FTIR was done by nsampel at pwaves number. Based on these information, problems occur because the number of predictor bigger thanthe number of perception, so that require to reduce dimension. Discrete Wavelet Transform (DWT) can reduce dimension become new variables. with . But, result of reduction still have high collinearity between coefficients of wavelet.Partial Least Squares (PLS) can be the good solving for the problems. Combining of DWT and PLS methods on calibration models use OSS-R give a good criterion of model .
Identification the number of Mycobacterium tuberculosis based on sputum image using local linear estimator Nur Chamidah; Yolanda Swastika Yonani; Elly Ana; Budi Lestari
Bulletin of Electrical Engineering and Informatics Vol 9, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (506.667 KB) | DOI: 10.11591/eei.v9i5.2021

Abstract

Infectious disease caused by infection of Mycobacterium tuberculosis is called tuberculosis (TB). A common method in detecting TB is by identifying number of mycobacterium TB in sputum manually. Unfortunately, manually calculation by pathologists take a relatively long time. Previous researches on TB bacteria were still limited to detect the absence or presence of mycobacterium TB in images of sputum. This research aims are identifying number of mycobacterium TB and determining accuracy of classification TB severity by approaching nonparametric Poisson regression model and applying an estimator namely local linear. Steps include processing of image, reducing of dimension by applying partial least square and discrete wavelet transformation, and then identifying the number of mycobacterium TB by using the proposed model approach. In this research, we get deviance values of 28.410 for nonparametric and 93.029 for parametric approaches and the average of classification accuracy values for 4 iterations of 92.75% for nonparametric and 85.5% for parametric approaches. Thus, for identifying many of mycobacterium TB met in images of sputum and classifying of TB severity, the proposed identifying method gives higher accuracy and shorter time in identifying number of mycobacterium TB than parametric linear regression method.
Applying SMOTE-NC on CART Algorithm to Handle Imbalanced Data in Customer Churn Prediction: A Case Study of Telecommunications Industry Ilma Amira Rahmayanti; Sediono Sediono; Toha Saifudin; Elly Ana
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : CV. Ridwan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.247 KB) | DOI: 10.36418/syntax-literate.v6i2.5166

Abstract

These days, telecommunications is very much needed in all areas of life. This condition has made the competition among the company is extremely tense. One strategic way to protect the company is to retain existing customers. The retention program as a scheme to retain customers must be implemented precisely and efficiently so that the company can maintain as many customers as possible. In this case, customer churn prediction holds an essential role. However, the existence of imbalanced data can increase prediction errors and create problems. Hence, in order to overcome the issue, this study combined the Synthetic Minority Oversampling Technique – Nominal Continuous (SMOTE-NC) with Classification and Regression Trees (CART). SMOTE-NC was applied to balance classes on training data, while CART formed a classification tree from those balanced data. Then, this classification tree created by CART algorithm had become the basis for predicting customer churn. The data used in this study are from https://community.ibm.com/, where the variables are related to customer demographics, customer contracts, usage history, and customer status of one of the telecom companies. Based on the analysis of these data, SMOTE-NC and CART combination succeeded in reducing errors in predicting customer churn, which also led recall value to increase by approximately 19%. Moreover, the accuracy generated from this combination method was still in a pretty good range of over 75%. Therefore, this study proposes an excellent way to improve the performance of churn prediction, especially in the telecommunications industry.
Penerapan Model ARIMAX-GARCH dalam Pemodelan dan Peramalan Volume Transaksi Uang Elektronik di Indonesia Christopher Andreas; Sediono Sediono; Elly Ana; Suliyanto Suliyanto; M. Fariz Fadillah Mardianto
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.v6i2.11214

Abstract

Di era ekonomi digital, berbagai aktivitas ekonomi telah banyak memanfaatkan penggunaan uang elektronik. Penggunaan uang elektronik memberi berbagai dampak positif terhadap perekonomian dan pertumbuhan ekonomi. Untuk itu, perkembangan ekonomi digital terus didorong dalam upaya untuk meningkatkan pertumbuhan ekonomi seperti salah satu pilar tujuan dari Sustainable Development Goals (SDGs). Hal ini menunjukkan bahwa pemodelan dan peramalan volume transaksi uang elektronik sangat penting untuk dilakukan karena volume transaksi uang elektronik tersebut merupakan salah satu indikator perkembangan ekonomi digital di Indonesia. Penelitian ini bertujuan untuk menciptakan model statistika yang memiliki akurasi tinggi guna meramalkan volume transaksi uang elektronik di Indonesia. Dalam hal ini, pemodelan dilakukan dengan mempertimbangkan dua variabel eksogen yaitu infrastruktur uang elektronik dan kondisi pandemi Covid-19. Penelitian ini dilakukan dengan melakukan analisis data berdasarkan data yang bersumber dari Bank Indonesia. Dengan menerapkan model ARIMAX-GARCH, diperoleh model statistika yang memiliki akurasi tinggi dalam meramalkan volume transaksi uang elektronik di Indonesia. Hal ini ditandai melalui nilai Mean Absolute Percentage Error (MAPE) sebesar 11,33%. Selain itu, kedua variabel eksogen yaitu infrastruktur uang elektronik dan kondisi pandemi Covid-19 berpengaruh signifikan terhadap volume transaksi uang elektronik di Indonesia. Penelitian ini bermanfaat sebagai landasan dalam melakukan evaluasi kebijakan terkait perkembangan ekonomi digital khususnya penggunaan uang elektronik di Indonesia.
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. 
Estimasi Interval Kredibel Distribusi Normal Terpotong Kiri pada Data Waktu Sembuh Pasien Covid-19 Putri Fardha Asa Oktavia Hans; Ardi Kurniawan; Sediono; Elly Ana; M. Fariz Fadillah Mardianto
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 15 No 1 (2022): 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 (232.386 KB) | DOI: 10.36456/jstat.vol15.no1.a5285

Abstract

The Covid-19 pandemic has been declared a Public Health Emergency of International Concern. One of the government's efforts to get out of the epidemic is to conduct an analysis based on existing data. The purpose of this study was to estimate the credible interval of the left truncated normal distribution. The results of the estimated credible intervals obtained have an implicit form so that they are solved by using a numerical integral approach. The results of this study were applied to the recovery time of Covid-19 patients from the Jemursari Health Center Surabaya in the range of December 2020 to February 2021. Through left cutting, the parameter estimation process only uses data that is more than 10 days, so that 37 data is obtained from a total of 45 data. It was found that the average recovery time for left-cut Covid-19 patients was between 10.583 days to 11.087 days. Meanwhile, the variance of recovery time for Covid-19 patients is cut left between 1.706 days to 1.772 days.
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.
Pengelompokkan Provinsi Berdasarkan Prioritas Potensi Sektor Maritim Indikator Blue Economy Menggunakan Analisis Cluster Average Linkage Grace Lucyana Koesnadi; Karina Tri Handayani; Nadia Dwi Marwanda; Putri Masyita Qomaryah; Dita Amelia; M. Fariz Fadillah Mardianto; Elly Ana
Jurnal Sains Matematika dan Statistika Vol 9, No 1 (2023): JSMS Januari 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v9i1.20291

Abstract

Indonesia sebagai negara kepulauan terbesar memiliki kekayaan sumber daya laut yang tinggi, sehingga memiliki potensi yang besar pada bidang maritim dalam pembangunan ekonomi nasional jangka panjang. Dalam realisasinya, pengelolaan ekonomi kelautan menemui banyak tantangan dan belum terlaksana dengan optimal. Blue economy bisa dijadikan salah satu upaya yang dapat ditempuh untuk memulihkan perekonomian Indonesia yang memburuk akibat adanya  pandemi Covid-19.  Pemetaan sektor unggulan dalam bidang kemaritiman untuk wilayah provinsi di Indonesia menjadi salah satu kunci utama dalam proyeksi blue economy. Metode yang digunakan yaitu pendekatan kuantitatif dengan teknik pengumpulan data yaitu dokumentasi. Objek penelitian pada tulisan ini yaitu 34 provinsi di Indonesia. Analisis statistika yang digunakan adalah analisis cluster hierarki metode average linkage untuk mengelompokkan provinsi di Indonesia berdasarkan proyeksi sektor unggulan dalam indikator blue economy. Setelah dilakukan pengelompokkan, didapatkan jumlah cluster optimal sebanyak 3 cluster dengan nilai Pseudo-F tertinggi yaitu 6,2642. Hasil penelitian menyatakan bahwa terbentuk 3 cluster dengan tingkat capaian indikator blue economy yang dikategorikan rendah, sedang, dan tinggi. Maka dari itu, strategi kebijakan yang sesuai dengan karakteristik setiap cluster perlu dilakukan agar upaya memulihkan perekonomian dan mewujudkan Indonesia yang biru secara berkelanjutan dapat berlangsung secara maksimal dan efisien.Kata Kunci:  Analisis Cluster, Average Linkage, Blue Economy, Maritim, Pseudo-F
Pola Kecenderungan Penyakit Menular Terhadap Topografi Kabupaten/Kota di Jawa Timur Menggunakan Analisis Korespondensi Dita Amalia; Na'imatul Lu'lu'a; Isna Nurul Izza Amalia; Annisa Putri Nayumi; Muhammad Walid Jumlat; Muhammad Fariz Fadillah Mardianto; Elly Ana
Jurnal Sains Matematika dan Statistika Vol 9, No 1 (2023): JSMS Januari 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v9i1.20853

Abstract

Penyebaran penyakit menular dapat disebabkan oleh faktor geografis lingkungan tempat tinggal masyarakat. Salah satu faktor geografis lingkungan adalah daerah topografi tempat tinggal masyarakat. Daerah topografi memiliki pengaruh terhadap terhadap penyebaran penyakit menular seperti malaria, TBC, pneumonia, dan kusta.   Penelitian ini menggunakan sumber data sekunder hasil rekapitulasi kasus penyakit di Jawa Timur tahun 2021 yang terdapat di 38 kabupaten dan kota di Provinsi Jawa Timur yang dikategorikan menjadi dataran rendah, dataran tinggi, dan dataran sedang. Penelitian menunjukkan bahwa penyakit TBC menjadi kasus penyakit menular terbesar, dengan jumlah sebesar 11.747 orang. Sedangkan kategori wilayah dengan jumlah kasus penyakit menular terbesar adalah dataran rendah sebanyak 8.067 orang. Penelitian ini bertujuan untuk mengetahui kecenderungan antara variabel penyakit menular dan kabupaten/kota di Jawa Timur dengan menggunakan metode analisis korespondensi. Berdasarkan hasil analisis penelitian ini, terdapat hubungan yang signifikan antara topografi wilayah di Jawa Timur dengan jumlah angka kasus penyakit menular. Penyakit malaria memiliki kecenderungan di dataran tinggi, penyakit TBC memiliki kecenderungan di dataran sedang, penyakit pneumonia dan kusta memiliki kecenderungan di dataran rendah. Hasil ini kemudian dapat digunakan sebagai acuan pemerintah dalam mempertimbangkan tindakan yang tepat serta efektif dalam menangani kasus penyakit menular di wilayah topografi tertentu.
Pemodelan Indeks Ketahanan Pangan di Indonesia Berdasarkan Pendekatan Regresi Logistik Ordinal Data Panel Efek Acak Anisa Laila Azhar; Suliyanto Suliyanto; Nur Chamidah; Elly Ana; Dita Amelia
Jurnal Ketahanan Nasional Vol 29, No 2 (2023)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jkn.86511

Abstract

ABSTRACTIndonesia is an agricultural country with the agricultural sector being an important sector in supporting food needs. Food availability that is less than necessary can lead to an unstable economy, as well as disrupt national food security. This study was conducted to model The Food Security Index (Indeks Ketahanan Pangan, IKP) and to find out what factors affect the status of food security in Indonesia.The analysis method used in this study is the logistic regression analysis of panel data with random effects. The data used in this study is secondary data related to IKP sourced from the Ministry of Agriculture and factors that are suspected to affect IKP in each province sourced from the Central Statistics Agency (Badan Pusat Statistik, BPS) from 2019 to 2021. The results of the analysis showed that statistically, the variable percentage of stunted toddlers and the variable percentage of households with access to electricity had a significant effect on the IKP. In addition, the results of the model conformity test showed that the random effect panel data logistic regression model was more in line with the classification accuracy of 50.98% when compared to the standard logistic regression with a classification accuracy of 40.80%.
Co-Authors Aniq Atiqi Anisa Laila Azhar Annisa Putri Nayumi Ardi Kurniawan Ayuning Dwis Cahyasari Budi Lestari Christopher Andreas Cynthia Anggelyn Siburian Dita Amelia Elly Pusporani Erfiana Erfiana Faradilla Harianto Grace Lucyana Koesnadi Ilma Amira Rahmayanti Isna Nurul Izza Amalia Karina Tri Handayani Khoirun Niswatin M. Fariz Fadillah Mardianto Marcel Laverda Subiyanto Maria Setya Dewanti Muhammad Fikry Al Farizi Muhammad Walid Jumlat Na'imatul Lu'lu'a Nadia Dwi Marwanda Noviatus Sholihah Nur Chamidah Nur chamnidah Putri Fardha Asa Oktavia Hans Putri Masyita Qomaryah Salsabylla Nada Apsariny Sediono, Sediono Siti Maghfirotul Ulyah Suliyanto Toha Saifudin Yolanda Swastika Yonani