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All Journal CommIT (Communication & Information Technology) KOLEGIAL : Jurnal Manajemen, Bisnis, dan Akuntansi Jurnal Matematika: MANTIK AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Inovasi : Jurnal Ekonomi, Keuangan, dan Manajemen Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika JTAM (Jurnal Teori dan Aplikasi Matematika) J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Majalah Ekonomi Jurnal Penamas Adi Buana Jurnal Leverage, Engagement, Empowerment of Community (LeECOM) Indonesian Journal of Social Research (IJSR) Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Jurnal Inspirasi Binsis dan Manajemen Jurnal Natural Kanigara EKOBIS ABDIMAS : Jurnal Pengabdian Masyarakat International Journal of Accounting and Management Research (IJAMR) International Journal of Computing Science and Applied Mathematics-IJCSAM Al Ibtida: Jurnal Pendidikan Guru MI
Evita Purnaningrum
Universitas PGRI Adi Buana Surabaya
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Neuroscience Physics Social Sciences Other

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Model Dynamic Ensemble Time Series untuk Prediksi Indeks Harga Saham Utama di Indonesia Pasca Pandemi Evita Purnaningrum
Majalah Ekonomi Vol 26 No 1 (2021): Juli 2021
Publisher : Fakultas Ekonomi Universitas PGRI Adi Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/majeko.vol26.no1.a3949

Abstract

Forecasting or predicting stock prices in the form of time series data is still a hot topic consistently discussed in economic forums and financial markets. This article had been analyzed prediction of stock prices in Indonesia after experiencing a pandemic and one year after the Corona virus. This study had been applied a dynamic ensemble method that combines various prediction models to improve forecasting accuracy. The results showed that the model has a high level of accuracy with MAPE (Mean Absolute Percentage Error) values of 0.003714125, and RMSE (Root Mean Square Error) of 0.03958605. Furthermore, these results could be used as a basis for government policy making and stock investment decisions for investors.
Dynamic Ensemble Time Series for Prediction Major Indices in Asean Evita Purnaningrum; Rina Fariana
Indonesian Journal of Social Research (IJSR) Vol 4 No 1 (2022): Indonesian Journal of Social Research (IJSR)
Publisher : Universitas Djuanda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30997/ijsr.v4i1.171

Abstract

World financial markets have been affected and depressed during the COVID-19 pandemic; all-digital capital market transactions experienced a sharp decline. No exception is the dynamics of capital markets in ASEAN countries. The uncertainty of the impact of the ASEAN Pandemic encourages stock price forecasting to reduce investment risk. It is also a topic that is consistently enthusiastically discussed in economic forums. This article applied stock price changes in five major ASEAN countries one year after the Coronavirus. Dynamic ensemble method that combines various predictive models to improve the accuracy of forecasts. The results showed that the model has a high level of accuracy with a small error value, which is below 1.5% for MAPE (Mean Absolute Percentage Error), and an average RMSE (Root Mean Square Error) of 5%. This suggests that investors could reduce their long-term investment risk by stealing the pandemic by using this model. In addition, these results are committed to being used as a basis for policy and decision-making for investors
PENGGUNAAN BIG DATA MELALUI ANALISIS GOOGLE TRENDS UNTUK MENGETAHUI PERSPEKTIF PARIWISATA INDONESIA DI MATA DUNIA Hanief Khoyyir Nafah; Evita Purnaningrum
SNHRP Vol. 3 (2021): Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Ke 3 Tahun 2021
Publisher : LPPM Universitas PGRI Adi Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.825 KB)

Abstract

Pariwisata sebagai salah satu penyumbang devisa terbesar negara Indonesia berpotensi untuk berkembang lebih baik lagi melalui penelitian. Pada era digital saat ini, tidak efektif dan efisien apabila penelitian masih menggunakan survei. Big Data merupakan kumpulan banyak data yang berasal dari berbagai jenis sumber data dan dapat bertambah dengan sangat cepat menjadi solusi yang tepat dalam membantu penelitian terkait pariwisata di Indonesia. Metode yang digunakan dalam penelitian ini adalah analisis big data melalui Google Trends. Penelitian ini memilih lokasi wisata di Pulau Lombok, Pulau Raja Ampat, Danau Kelimutu, Pulau Komodo, dan Gunung Bromo. Penggunaan kategori di Google Trends yang digunakan adalah hobi, travel, dan masyarakat. Berdasarkan hasil analisis, mayoritas negara yang sering melakukan pencarian terkait lima tempat wisata di Indonesia adalah Indonesia, Malaysia, Singapura, Brunei Darussalam, Australia, dan Hong Kong. Mayoritas negara yang sering melakukan pencarian terkait lima tempat wisata Indonesia berdasarkan kategori hobi, travel, dan masyarakat adalah Indonesia, Malaysia, Singapura, Brunei Darussalam, Australia, dan New Zealand
Modified Multi-Kernel Support Vector Machine for Mask Detection Muhammad Athoillah; Evita Purnaningrum; Rani Kurnia Putri
CommIT (Communication and Information Technology) Journal Vol. 16 No. 2 (2022): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v16i2.7873

Abstract

Indonesia is one of the countries most affected by the Coronavirus pandemic with millions confirm cases. Hence, the government has increased strict procedures for using face masks in public areas. For this reason, the detection of people wearing face masks in public areas is needed. Face mask detection is a part of the classification problem. Thus Support Vector Machine (SVM) can be implemented. SVM is still known as one of the most powerful and efficient classification algorithms. The research aims to build an automatic face mask detector using SVM. However, it needs to modify it first because it only can classify linear data. The modification is made by adding kernel functions, and a Multi-kernel approach is chosen. The proposed method is applied by combining various kernels into one kernel equation. The dataset used in the research is a face mask image obtained from Github. The data are public datasets consisting of faces with and without masks. The results present that the proposed method provides good performance. It is proven by the average value. The values are 83.67% for sensitivity, 82.40% for specificity, 82.00% for precision, 82.93% for accuracy, and 82.77% for F1-score. These values are better than other experiments using single kernel SVM with the same process and dataset.
Penyebaran Pengguna Digital Wallet Di Indonesia Berdasarkan Google Trends Analytics Dwi Ajeng Kusumawardhani; Evita Purnaningrum
INOVASI Vol 17, No 2 (2021): Mei
Publisher : Faculty of Economics and Business Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jinv.v17i2.8069

Abstract

 Industri terus menerus mengalami perubahan dan berkembang secara pesat. Teknologi dan Informasi menjadi poin terpenting dalam dunia industri saat ini. Perusahaan dituntut bergerak cepat dang memberikan inovasi untuk menyesuaiakan hal tersebut. salah satu industry yang berkembang sesuai dengan teknologi adalah digital wallet (e-wallet). Munculnya digital wallet sebagai alat pembayaran transaksi online yang mudah dan praktis membuat banyak masyarakat Indonesia mulai beralih menggunakan aplikasi tersebut. Aplikasi tersebut mengalami kenaikan jumlah pengguna di setiap tahunnya. Kebijakan ekonomi dan keuangan mengenai pertumbuhan aplikasi ini diperlukan untuk menunjang kenyamanan konsumen saat bertransaksi. Sebagai salah satu pendukung kebijakan tersebut diperlukan suatu pengetahuan mengenai penyebaran penggunaan dan pendistribuan pengguna di suatu daerah, khususnya Indonesia. Penelitian ini bertujuan membandingkan pernyebaran penguna digital wallet pra dan pasca pandemi Covid-19 dengan menggunakan salah satu Big Data yang sederhana yakni Google Trends. Google trends merupakan salah satu instrumen big data yang paling sederhana untuk mencari data yang berbasis web sehingga tidak memerlukan survey. Dalam penelitian ini, peneliti mengambil data menggunakan google trends yang penggunaanya masih jarang di Indonesia. Hasil penelitian diketahui bahwa hampir seluruh wilayah Indonesia telah tersebar digital wallet dan provinsi dengan pengguna terbesar banyak terdapat di pulau Jawa.
Study on the performance of Robust LASSO in determining important variables data with outliers ROCHYATI ROCHYATI; KUSMAN SADIK; BAGUS SARTONO; EVITA PURNANINGRUM
Jurnal Natural Volume 23 Number 1, February 2023
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v23i1.26279

Abstract

A variable selection method is required to deal with regression models with many variables, and LASSO has been the most widely used methodology.  However, as several authors have noted, LASSO is sensitive to outliers in the data.  For this reason, the Robust-LASSO approach was introduced by applying some weighting schemes for each sample in the data.  This research presented a comparative study of the three weighting schemes in Robust LASSO, namely Huber-LASSO, Tukey-LASSO, and Welsch-LASSO.  The study did a rich simulation containing many scenarios with various characteristics on the covariance structures of the explanatory variable, the types of outliers, the number of outliers, the location of active variables, and the number of variables.  The study then found that Tukey-LASSO outperformed Huber-LASSO and Welsch-LASSO in identifying significant variables.  The Robust LASSO performance generally decreased as the covariances among explanatory variables increased and the data dimension increased.  Exploration of sembung leaf extract data shows that the data is high dimensional data which contains outliers of about 14,28% on the response variable and about 25,71% on the explanatory variables.  Based on the research, the number of variables selected using the Tukey-LASSO method was nine compounds, Huber-LASSO and Welsch-LASSO were eight compounds, and LASSO 13 compounds.  The Tukey-LASSO prediction accuracy is superior to the other three methods.
Kajian terkait ketangkasan belajar tenaga kerja pada perusahaan manufacturing di era digital Wardatur Roikhah; Evita Purnaningrum; Heny Afifatul Mu’asyaroh
Jurnal Inspirasi Bisnis dan Manajemen Vol 7, No 1 (2023): JUNI 2023
Publisher : Lembaga Penelitian Universitas Swadaya Gunung Jati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33603/jibm.v7i1.8416

Abstract

Abstract. Digital transformation plays an important role in changing the shape of a person's behavior along with increasingly advanced technology. Current technological developments require businesses to have an agile workforce and talented employees. Speed in learning is forced to be positively correlated with technological developments. The purpose of this research is to determine the competency readiness of the workforce through the learning agility of each individual. The factors investigated include learning culture, work involvement in Industry 4.0 by adjusting the contents of the questionnaire related to the Digital era. A quantitative method approach based on SEM-PLS with R software and plspm Package is used to determine the relationship between learning culture (X1) and work engagement (X2) with learning agility (Y) as a latent variable. The results of this study indicate that learning agility to achieve workforce readiness in the digital era can be influenced by learning culture and work enggagement. Keywords: Learning Agility; Learning Culture; Work Enggagement; Digital Era Abstrak. Transformasi digital memainkan peran penting pada perubahan bentuk tingkah laku seseorang bersanding dengan teknologi semakin maju. Perkembangan teknologi saat ini menuntut bisnis untuk memiliki tenaga kerja yang gesit dan karyawan yang berbakat. Kecepatan dalam belajar dipaksa berkorelasi positif dengan perkembangan teknologi. Tujuan penelitian ini adalah untuk mengetahui kesiapan kompetensi tenaga kerja melalui ketangkasan belajar dari setiap individunya. Faktor-faktor yang diselidiki meliputi budaya belajar, keterlibatan kerja di Industri 4.0 dengan menyesuaikan isi kuisioner terkait era Digital. Pendekatan metode kuantitatif berbasis SEM-PLS dengan software R dan plspm Package digunakan untuk mengetahui hubungan budaya belajar (X1) dan keterikatan kerja (X2) dengan ketangkasan belajar (Y) sebagai variabel laten. Hasil penelitian ini menunjukkan bahwa ketangkasan belajar untuk menju kesiapan tenaga kerja di era digital dapat dipengaruhi learning culture dan work enggagement. Katakunci: Ketangkasan Belajar;Budaya Belajar;Keterikatan Kerja; Era Digital
Pelatihan Bisnis Online Bagi Komunitas Disabilitas Dimasa Pandemi Covid-19 Muhammad Nurrohman Jauhari; Evita Purnaningrum
Kanigara Vol 1 No 2 (2021): Kanigara
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/kanigara.v1i2.4041

Abstract

Tujuan dari dilaksanakannya kegiatan pelatihan ini untuk memberikan pemahaman tentang keterampilan vokasional dan mengembangkan usaha yang dilakukan oleh penyandang disabiltas. Metode pelaksanaan menggunakan langkah-langkah yang terdiri terdiri dari 3 tahap, yaitu: (1) perencanaan, (2) pelaksanaan, dan (3) evaluasi. Hasil pelatihan ini didapatkan bahwa 85% peserta mitra disabilitas melaksanakan tugas sesuai dengan arahan dari tim peneliti. Beberapa kendala yang dihadapi mitra disabilitas antara lain: tidak memiliki sarana dan prasarana yang memadai seperti laptop, sehingga dalam pelaksaanaan tugasnya mitra disabilitas menggunakan sarana dan prasarana secara bergantian.
Study on the performance of Robust LASSO in determining important variables data with outliers ROCHYATI ROCHYATI; KUSMAN SADIK; BAGUS SARTONO; EVITA PURNANINGRUM
Jurnal Natural Volume 23 Number 1, February 2023
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v23i1.26279

Abstract

A variable selection method is required to deal with regression models with many variables, and LASSO has been the most widely used methodology.  However, as several authors have noted, LASSO is sensitive to outliers in the data.  For this reason, the Robust-LASSO approach was introduced by applying some weighting schemes for each sample in the data.  This research presented a comparative study of the three weighting schemes in Robust LASSO, namely Huber-LASSO, Tukey-LASSO, and Welsch-LASSO.  The study did a rich simulation containing many scenarios with various characteristics on the covariance structures of the explanatory variable, the types of outliers, the number of outliers, the location of active variables, and the number of variables.  The study then found that Tukey-LASSO outperformed Huber-LASSO and Welsch-LASSO in identifying significant variables.  The Robust LASSO performance generally decreased as the covariances among explanatory variables increased and the data dimension increased.  Exploration of sembung leaf extract data shows that the data is high dimensional data which contains outliers of about 14,28% on the response variable and about 25,71% on the explanatory variables.  Based on the research, the number of variables selected using the Tukey-LASSO method was nine compounds, Huber-LASSO and Welsch-LASSO were eight compounds, and LASSO 13 compounds.  The Tukey-LASSO prediction accuracy is superior to the other three methods.
Pelatihan Aspek Marketing Mix Pada Pelaku Usaha Bonggolan Di Desa Pengulu Kecamatan Sidayu Kabupaten Gresik ferry hariawan; Nashrudin Latif; Christina Menuk Sri Handayani; Evita Purnaningrum
Ekobis Abdimas Vol 1 No 1 (2020): Juni
Publisher : Fakultas Ekonomi, Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/ekobisabdimas.1.1.2337

Abstract

Lapangan usaha pada sektor pertanian, perikanan dan industri pengolahan di Desa Pengulu sangat beragam. Kondisi tersebut merangsang munculnya UMKM yang saling terkait dengan potensi lokal yang dimiliki Desa Pengulu dengan wilayah desa lainnya di Kecamatan Sidayu, Kabupaten Gresik. Permasalahan yang terjadi menunjukkan kurang berkembangnya produk Bonggolan dari sisi pemasaran dikarenakan minimnya pendidikan dalam mengembangkan potensi lokal yang ada. Potensi UMKM membutuhkan penguatan melalui pengabdian masyarakat dengan basis pemberian edukasi tentang marketing mix 7P untuk mengembangkan produk Bonggolan. Peningkatan dan perbaikan atas kendala yang dihadapi dengan keterkaitan antar komponen marketing mix 7P untuk meningkatkan penjualan dan kepuasan konsumen. Dampak yang dihasilkan dari pengabdian masyarakat menunjukkan peningkatan kesadaran masyarakat desa dalam upayanya untuk pengembangan produk, peningkatan kesejahteraan warga dan perekonomian desa Pengulu
Co-Authors Aji Prasetyo Ariqoh2, Ihdina Ariyanti, Viki Bagus Sartono Bayu Adi Bisma Arianto Cahya, Septa Dwi Cahyaningtias, Sari Christina Menuk Sri Handayani Dwi Ajeng Kusumawardhani Dyatmika, Sutama Wisnu Erna Apriliani Fauziyah Fauziyah Ferry Hariawan Firdausia, Yuli Kurnia Hanief Khoyyir Nafah Hanief Khoyyir Nafah Heny Afifatul Mu’asyaroh I Made Bagus Dwiarta Ihdina Ariqoh2 Indahwati Jauhari, Muhammad Nurrohman Kusman Sadik Kusumawardhani, Dwi Ajeng Moch. Munir Rachman Muhammad Athoillah, Muhammad Nafah , Hanief Khoyyir Nashrudin Latif Noerchoidah Putri, Rani Kurnia Rachmadtullah, Reza Rafikayati, Ana Reza Rachmadtullah Rina Fariana ROCHYATI ROCHYATI Satya Putra, Eza Widhy Sigit Prihanto Utomo Subakir Sugijanto Suharni Suharni Suharni, Suharni Sutama Wisnu Dyatmika Sutama Wisnu Dyatmika Tri Ariprabowo Viki Ariyanti W, Tony Susilo Wahyuning Murniati Wardatur Roikhah Waryanto, Bambang Dwi Widhayani Puri S