Venia Restreva Danestiara
Program Studi Informatika, Fakultas Teknologi Dan Informatika, Universitas Informatika Dan Bisnis Indonesia

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ANALISIS SENTIMEN PELAKSANAAN KULIAH ONLINE MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE Setiana, Elia; Marwondo; Venia Retreva Danestiara; Wiyanudin
NUANSA INFORMATIKA Vol. 17 No. 2 (2023): Volume 17 No 2 Tahun 2023
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v17i2.11

Abstract

This writing aims to assess the satisfaction of students regarding the implementation of online lectures, categorized into three classes: positive, neutral, and negative. Data collection was conducted using Twint from the social media platform Twitter, with a total of 25,000 tweets. The data processing process to determine sentiment analysis utilized the support vector machine algorithm. With this algorithm, the obtained results show an accuracy rate of 76.86% for positive sentiment. The precision is 0.49, recall is 0.53, and the F1 score is 0.51
Penguatan Profil Pelajar Pancasila dalam Berekayasa dan Berteknologi Melalui Wawasan Software Development pada Peserta Didik SMP Negeri 7 Bandung Budiman Budiman; Elia Setiana; Venia Restreva Danestiara; Valencia Claudia Jennifer Kaunang; Dirham Triyadi
Jurnal Bhakti Karya dan Inovatif Vol 4 No 1 (2024): Jurnal Bhakti Karya dan Inovatif
Publisher : LPPM Universitas Informatika dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/bhaktikaryadaninovatif.v4i1.726

Abstract

Pentingnya wawasan software development atau pemrograman bagi peserta didik dapat memberikan manfaat jangka panjang bagi perkembangan peserta didik dalam berbagai aspek kehidupan. Tujuan untuk memberikan pengetahuan, keterampilan, dan peluang kepada peserta didik untuk berkontribusi dalam memajukan Indonesia melalui pengembangan perangkat lunak. Pemrograman melibatkan pemecahan masalah secara logis dan sistematis. Tahapan-tahapan yang dilakukan dalam kegiatan Pengabdian kepada Masyarakat adalah penjajakan dengan mitra, wawancara, kunjungan langsung untuk melakukan analisa sebagai bahan penyusunan program, koordinasi dengan mitra terkait program yang akan dijalankan, pelaksanaan kegiatan, dan evaluasi. Setelah dilakukan pemaparan materi bentuk evaluasi kegiatan dilakukan dengan post-test, penyebaran pertanyaan sama dengan pertanyaan pada saat pre-test. Hasil Pos-test menunjukkan peningkatan pengetahuan peserta pelatihan rata-rata sebesar 45,6%.
Optimalisasi Sumber Informasi dan Kolaborasi Produktif Melalui Website Coworking Space di Kecamatan Coblong Budiman Budiman; Venia Restreya Danestiara; Imannudin Akbar
Jurnal Bhakti Karya dan Inovatif Vol 4 No 1 (2024): Jurnal Bhakti Karya dan Inovatif
Publisher : LPPM Universitas Informatika dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/bhaktikaryadaninovatif.v4i1.797

Abstract

Sebagai wilayah yang terus berkembang, Kecamatan Coblong mengalami banyak perubahan. Meningkatnya konektivitas dan digitalisasi telah menimbulkan tantangan baru, tetapi juga telah membuka peluang untuk meningkatkan potensi ekonomi dan sosial di daerah tersebut. Website Coworking Space ini dibuat dengan tujuan utama untuk menjadi sumber informasi yang memungkinkan masyarakat untuk mengakses peluang penjualan produk lokal. Diharapkan para pelaku usaha dapat memasarkan barang-barang unggulan mereka dengan lebih efektif dengan menyediakan platform yang terintegrasi. Metode pelatihan untuk adopsi situs web Coworking Space di Kecamatan Coblong memberikan pengarahan tentang tujuan pelatihan, mengajarkan konsep dasar pengelolaan konten dan situs web, memberikan kesempatan untuk praktek langsung dalam proyek, dan didukung oleh interaksi langsung dan pemanfaatan teknologi untuk meningkatkan keterampilan peserta dalam membuat dan mengelola situs web. Kegiatan pengabdian masyarakat untuk adopsi wwebsite Coworking Space Kecamatan Coblong menghasilkan peningkatan keterampilan peserta dalam pembuatan dan pengelolaan website, peningkatan aksesibilitas informasi tentang layanan Coworking Space, dan peningkatan hubungan antara Coworking Space dan komunitas lokal. Kegiatan ini berdampak positif pada pertumbuhan ekonomi dan reputasi wilayah tersebut.
Pengembangan Aplikasi Closing Register Berbasis Web untuk Membantu Customer Service Digital Marketing Titan Parama Yoga Titan; R. Yadi Rakhman Alamsyah; Venia Restreva Danestiara; Aliman Fauzi
Jurnal Accounting Information System (AIMS) Vol. 6 No. 2 (2023)
Publisher : Ma'soem University

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

Abstract

This research was conducted to solve sales data collection problems in the digital marketing business at CV. Icommits Work Solutions. The problem that occurs is that the process of entering data is inefficient and still uses ineffective conventional methods. By doing this research the authors are looking for a way to solve this problem, and the way to solve it is to develop the Closing Register application. The purpose of developing the Closing Register application is to simplify the process of entering data and monitoring sales data so that consumers, customer service and CS admins do not need to expend a lot of energy in the sales data collection process. The Closing Register application is made with the RAD (Rapid Application Development) design model, as well as the technology used in application development, namely ReactJS as a framework in charge of creating web admin views, Flutter as a framework in charge of creating mobile displays, MySQL as a database, and ExpressJS as a framework whose job is to create an API (Application Programming Interface). The results showed that technologies are used to create up-to-date applications and for long-term use, so that later these applications can be used directly and are useful for digital marketing businesses.
Information Systems Strategic Planning at one of the Vocational High Schools in Cimahi Imannudin Akbar Iman; Venia Restreva Danestiara; Syahira Putri Himmaniah
Jurnal Computech & Bisnis (e-journal) Vol. 18 No. 1 (2024): Jurnal Computech & Bisnis (e-Journal)
Publisher : LPPM STMIK Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56447/jcb.v18i1.301

Abstract

A strategic plan is an organization's detailed and extensive strategy to effectively manage its resources and achieve its goals within a specified period. Effective implementation of an information system necessitates strategic planning inside an organization to capitalize on the advantages of the information system implementation fully. This also applies to a Vocational High School in Cimahi. The school encounters many obstacles, including managing school data and performance assessments and requiring a unified system across departments to facilitate the school's operational procedures. Strategic planning establishes specific objectives, such as integrating information systems in academic and non-academic operations, overseeing school data management, enhancing infrastructure management efficiency, and boosting competitiveness by developing a web-based school support system for information and promotional purposes. Aligning the information system's strategies with the school's business strategies will aid in accomplishing these objectives. Developing information system strategies necessitates alignment with the organization's existing business strategies. This research examines the strategic information system planning process, specifically employing the Ward-Peppard technique. This approach facilitates a more comprehensive comprehension of the firm before developing a strategic plan. It involves doing a SWOT analysis, Value Chain analysis, Porter's Five Forces analysis, and McFarlan's strategic grid analysis as recommendations for the proposed information system strategies.
Algoritma Gated Recurrent Unit untuk Prediksi Harga Indeks Penutupan Saham LQ45 Danestiara, Venia Restreva; Setiana, Elia; Akbar, Imannudin; Hidayah, Taufik
Jurnal Accounting Information System (AIMS) Vol. 7 No. 1 (2024)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v7i1.814

Abstract

The Indonesia Stock Exchange (IDX) states that stocks, including LQ45 stocks, which constitute the stock market index for the IDX, have become one of the preferred investment options for the public. Investors need to have accurate analysis and information to gain significant profits as stock prices fluctuate due to company performance, industry factors, changes in interest rates, liquidity, global market conditions, market sentiment, and investor psychology. The Gated Recurrent Unit algorithm is suitable for application on historical stock data sets because they are time series data, can be computed and compared on a numerical scale. This algorithm is a variant of the Long Short-Term Memory algorithm or other types of processing modules for Recurrent Neural Networks. The data set used consists of closing price data or close features, comprising a training data set of 4,406 data and a test data set of 1,889 data that have undergone data preparation using various techniques, including data cleansing, data scrubbing, data splitting, data normalization, and data reshaping. The results showed that the Gated Recurrent Unit algorithm is the right strategy because it obtains a good evaluation of model performance, namely MSE of 0.0009; RMSE of 0.17325 and MAE of 0.0207.
Prediksi Penyakit Paru Menggunakan Algoritma Deep Neural Network Danestiara, Venia Restreya; Fadhilah, Agung Nur
In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Vol 21 No 1 (2022): In Search
Publisher : LPPM UNIBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/insearch.v22i1.955

Abstract

Lung diseases, including tuberculosis (TB) and lung cancer, are major health issues in Indonesia with high incidence and mortality rates. Early and accurate diagnosis is crucial to increase the chances of patient recovery. This research aims to develop a predictive model for lung diseases using the Deep Neural Network (DNN) algorithm. The dataset used in this study consists of 30,000 health records obtained from the Kaggle website, with 52% of the data indicating the presence of lung diseases. The research process includes data collection, data pre-processing, DNN model development, and model evaluation using a confusion matrix. The results show that the developed predictive model achieved an accuracy of 94%, with high precision and recall values for both positive and negative classes. The model evaluation indicates that it is capable of identifying lung disease cases with a low error rate
Deep Neural Network untuk Klasifikasi Influenza Danestiara, Venia Restreya; Abdillah, Muhammad Syaddad
In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Vol 21 No 2 (2022): In Search
Publisher : LPPM UNIBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/insearch.v21i2.956

Abstract

In facing the global threat posed by the Influenza virus, similar to COVID-19, which has the potential to cause pandemics with serious impacts on public health and the economy, this research implements a Deep Learning algorithm for the classification of Influenza viruses based on a dataset containing various characteristics of the virus. The dataset has undergone preprocessing steps, including the removal of irrelevant columns, handling of missing values, and encoding of categorical variables. A Deep Neural Network (DNN) model was developed and trained using cross-validation techniques to enhance performance. Evaluation results show a high level of accuracy in the classification of Influenza viruses. This study concludes that Deep Learning algorithms are effective in classifying Influenza viruses.
Optimasi Penggunaan Teknologi Dan Akses Digital Untuk Pendidikan Lanjutan Pada Kober Nurul Ikhlas Nursyanti, Reni; Setiana, Elia; Marwondo; Restreva Danestiara, Venia; Prakarsa, Graha; Ikhsan Nur, Muhammad; Teofilus Hendrawan, Yesaya
Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) Vol. 3 No. 2 (2024): Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) (Edisi Oktober)
Publisher : Pusat Studi Teknologi Informasi Fakultas Ilmu Komputer Universitas Bandar Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jpmtb.v3i2.114

Abstract

Pemerintah, khususnya Dinas Pendidikan, semakin mendorong pemanfaatan teknologi dalam mendukung pendidikan lanjutan. Salah satu langkah konkret yang diambil adalah implementasi sistem Penerimaan Peserta Didik Baru (PPDB). Inisiatif ini menjadi bagian dari upaya untuk meningkatkan efisiensi dan aksesibilitas dalam proses pendidikan. Melalui PPDB online, calon siswa dan orang tua dapat mengakses informasi dan melakukan pendaftaran tanpa harus datang ke lokasi secara fisik. Hal ini memungkinkan partisipasi yang lebih luas dan meminimalkan hambatan administratif. Penerapan teknologi dalam PPDB online juga membawa dampak positif dalam hal transparansi. Meskipun Prosedur pendaftaran dan kriteria seleksi menjadi lebih jelas dan terdokumentasi dengan baik, tetapi dalam prosesnya orang tua siswa masih banyak yang belum mengerti penggunaan teknologi dan alur sistem PPDB Onlie serta apa saya yang perlu dipersiapkan saak mengakses teknologi tersebut, sehingga PKM ini diadakan agar dapat pengoptimalisasi penggunaan teknologi sekaligus mengedukasi orang tua siswa untuk dapat lebih efektif dalam menggunakan teknologi terutama akses digital untuk Pendidikan lanjutan.
Algoritma k-Nearest Neighbor Classifier untuk Prediksi Curah Hujan di Kabupaten Bandung Venia Restreva Danestiara
SisInfo Vol 5 No 1 (2023): SisInfo
Publisher : Universitas Informatika dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (365.293 KB) | DOI: 10.37278/sisinfo.v5i01.566

Abstract

Implementasi algoritma k-Nearest Neighbor Classifier dengan teknik Data Mining pada prediksi curah hujan dapat membantu mayoritas masyarakat di Kabupaten Bandung yang memiliki mata pencaharian di bidang pertanian. Himpunan data berasal dari BMKG (Badan Meteorologi, Klimatologi, dan Geofisika) Bandung dengan jangkauan waktu antara Januari 2005 hingga Desember 2016 yang terdiri dari enam atribut, yaitu: penyinaran matahari, kelembapan, angin, temperatur, uap dan curah hujan. Hasil pencarian tetangga terdekat adalah atribut curah hujan dari lima kategori kelas, yaitu: tidak hujan, hujan ringan, hujan sedang, hujan lebat dan hujan sangat lebat, yang dihitung menggunakan euclidean distance. Penelitian ini melakukan pengujian akurasi dengan tiga partisi himpunan data dan penggunaan sepuluh nilai k yang berbeda. Akurasi-akurasi yang didapatkan sangat baik dengan akurasi tertinggi sebesar 97,92% untuk nilai k={3,5} pada partisi himpunan data latih dan uji masing-masing 50%. Nilai k, jumlah himpunan data dan data latih berpengaruh dalam pencarian tetangga terdekat.