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Implementasi Dashboard Fact Checker Directory untuk Meningkatkan Kewaspadaan Terhadap Informasi Hoaks Aesyi, Ulfi Saidata; Cahyo, Puji Winar; Asnawi, Choerun
The Journal of Innovation in Community Empowerment Vol 7 No 2 (2025): Journal of Innovation in Community Empowerment (JICE)
Publisher : Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/jice.v7i2.1499

Abstract

Di era internet, berita hoaks menjadi masalah besar untuk menjaga kualitas informasi masyarakat. Literasi digital sangat penting untuk membantu orang mengenali dan menghindari berita palsu. Di SMK YPKK 1 Sleman, kegiatan pengabdian kepada masyarakat dilakukan melalui sosialisasi penggunaan Dashboard Fact Checker Directory untuk meningkatkan literasi digital. Tujuan dari kegiatan ini adalah agar siswa memahami cara membedakan Informasi hoaks dan bagaimana memanfaatkan teknologi untuk membantu literasi digital. Hal Tersebut digunakan untuk meningkatkan keterlibatan siswa, teknik interaktif seperti presentasi, simulasi penggunaan dashboard, dan diskusi aktif digunakan. Fakultas Teknik dan Teknologi Informasi Universitas Jenderal Achmad Yani Yogyakarta bekerja sama dengan mahasiswa dan dosen untuk membuat materi mudah dipahami siswa. Hasil kegiatan menunjukkan peningkatan pemahaman siswa tentang karakteristik berita hoaks dan kemampuan mereka untuk menggunakan dashboard untuk memeriksa kebenaran informasi. Hasil evaluasi setelah kegiatan menunjukkan peningkatan pemahaman peserta dalam mengidentifikasi berita hoaks dengan benar dan menunjukkan minat untuk menggunakan dashboard dalam aktivitas sehari-hari mereka. Kesimpulannya, sosialisasi ini membantu generasi muda menjadi lebih cerdas dalam menggunakan teknologi dan mengajarkan mereka cara memilah data secara kritis. Kegiatan ini diharapkan menjadi langkah awal menuju masyarakat yang lebih cerdas dan bijak dalam menggunakan teknologi saat ini.
Pemrograman Scratch untuk melatih logika dan meningkatkan keterampilan menciptakan animasi digital di SMP Negeri 4 Samigaluh Cahyo, Puji Winar; Aesyi, Ulfi Saidata; Asnawi, Choerun
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 7, No 2 (2024): Mei
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v7i2.1930

Abstract

Tantangan bagi para pendidik atau guru Sekolah Menengah Pertama (SMP) untuk dapat memberikan materi yang menarik dan mudah dipahami oleh peserta didik. Dikarenakan siswa SMP saat ini masuk kedalam golongan Generasi Z yang merupakan generasi dengan tingkat ketertarikan tinggi pada teknologi dan pembelajaran secara visual. Demi mendukung keterampilan siswa dalam menggunakan komputer dan menarik minat belajar dalam pembelajaran secara visual maka perlu dilakukan program peningkatan keterampilan penggunaan Scratch. Melalui implementasi program peningkatan keterampilan menggunakan Scratch tersebut memberikan dampak yang cukup positif. Kenaikan tersebut dibuktikan pada hasil pre-test dan post-test yang sudah dilakukan pada 59 peserta didik dan mengalami peningkatan pengetahuan mencapai 50%. Secara keseluruhan program peningkatan keterampilan berjalan dengan lancar akan tetapi perlu adanya praktik pembuatan animasi atau pembelajaran animasi secara berkala, agar siswa menjadi lebih terbiasa menggunakan Scratch.
A Comparison of K-Means and Agglomerative Clustering for Users Segmentation based on Question Answerer Reputation in Brainly Platform Cahyo, Puji Winar; Sudarmana, Landung
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 6 No. 2 (2021): November 2021
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (269.454 KB) | DOI: 10.21831/elinvo.v6i2.44486

Abstract

Brainly is a question and answer (Q&A) site that students can use as a media for questions and answers. Students can also use Brainly to find and share educational information that helps students solve their homework problems. In Brainly, users can answer questions according to their interests. However, it could be that the interest is not necessarily following the competencies possessed. It causes many answers to the questions given not to have a high rating because the answers given are of low quality to be prioritized as the main answer. This study aims to apply the K-Means and Agglomerative Clustering methods to segment users based on the reputation of the answerers by conducting clustering based on track records in answering questions on mathematics subjects. This study used the number of the brightest scores and the number of answers that did not get a rating as the basic features for clustering. The comparison between the two methods used is based on the Silhouette Score, representing the quality of the clustering results, calculated by applying the Silhouette Coefficient method. This study result indicates that the K-Means method gives better results than the Agglomerative Clustering. The Silhouette Score generated by the K-Means method is higher at 0.9081 than the Agglomerative Clustering method, which is 0.8990, which produces two clusters or two segments.
Sentimen Topik Menggunakan Regresi Logistik dan Alokasi Dirichlet Laten sebagai Model Analisis Kepuasan Pelanggan Cahyo, Puji Winar; Aesyi, Ulfi Saidata; Santosa, Bagas Dwi
JURNAL INFOTEL Vol 16 No 1 (2024): February 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i1.1081

Abstract

Buying and selling goods now is more interesting through e-commerce or marketplaces because of the ease of carrying out online transactions. Each transaction usually generates a response from the customer. The transaction response on the Shopee platform is still in paragraph form and needs to be more specific. Therefore, this research aims to build a model analysis of customer satisfaction using the best algorithm between support vector machine (SVM), random forest, and logistic regression. This research method uses sentiment classification with logistic regression because the logistic regression algorithm has the best accuracy, with an accuracy of 90.5. Meanwhile, the SVM algorithm achieved an accuracy of 90.4, and random forest reached 90.2. The three algorithms were tested three times, splitting data train:test at 80:20, 70:30, and 60:40. The best results were obtained by splitting data at 60:40. The best model is used to predict data without labels. The prediction produces 12,844 positive sentiment comment data, 112 negative sentiment comment data, and 70 neutral sentiment comment data. The results of this research continued to topic modeling using latent dirichlet allocation (LDA) to generate a trending topic of customer satisfaction on sales products. Implications of discussing each trend topic can be used as a reference for improving products and services, especially in communicating with customers.
Analisis dan Penanganan Insiden Siber SQL Injection Menggunakan Kerangka NIST SP 800-61R2 dan Algoritma Klusterisasi K-Means Asnawi, Choerun; Hariyadi, Dedy; Aesyi, Ulfi Saidata; Cahyo, Puji Winar
Jurnal Komtika (Komputasi dan Informatika) Vol 7 No 2 (2023)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v7i2.10527

Abstract

Based on the OWASP Top Ten document in 2021, attacks or vulnerabilities in an application in the form of injection still rank in the top 3. SQL Injection attacks are still classified as injection vulnerabilities so they need special attention from Information & Communication Technology Managers. Badan Siber dan Sandi Negara (BSSN) has published a document related to preventing SQL Injection attacks. However, the document has not included a cyber attack analysis process that uses the K-Means clustering approach. So in this research, a collaborative method of handling cyber attacks in the form of SQL Injection is proposed using the NIST SP 800-61R2 framework as a fundamental for handling cyber attacks and K-Means clustering. Before analyzing cyber attacks, it is better to use a framework or standardization that applies globally. Based on the research conducted, the K-Means clustering algorithm can help cybersecurity analysts in the process of analyzing cyber attacks that occur. The result of this research is that the optimal value is obtained that cyber attacks in the form of SQL Injection, namely 3 clusters. The hope of the research can facilitate cybersecurity analysts in analyzing cyber attacks that are poured into reports to parties in need
METODE FULL COSTING DAN COST PLUS DALAM HARGA JUAL USAHA MIKRO KECIL DAN MENENGAH Nusa, Gerlan Haha; Sulistiyantoro, David; Cahyo, Puji Winar; Zahara, Inna; Himawan, Arif
Journal of Economic, Bussines and Accounting (COSTING) Vol. 9 No. 1 (2026): COSTING : Journal of Economic, Bussines and Accounting
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/xcanpp60

Abstract

The problem faced by MSMEs is the lack of recording the costs incurred in determining prices. The aim of the research is for MSMEs to find out the cost of production using the full costing method and determine the desired profit using the cost-plus approach. With this determination, it is hoped that it can be used to make various decisions regarding selling prices. The research method used is descriptive qualitative to analyze the data. The research results show that the selling price of beverage products at full costing and cost-plus is lower than the price determined by Omah Pakis. Meanwhile, for food products, the full costing and cost-plus calculations are higher compared to the prices determined by Omah Pakis. The conclusion of this research is that costs are only charged to the elements of raw material and labor costs so that the information on determining selling prices is incomplete. As a result of incomplete cost information data being available, the decisions taken by the owner of Omah Pakis only focus on the short term. Omah Pakis can group production costs by determining the markup to determine the selling price using the cost-plus method.