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PENGARUH PEMBERIAN AIR REBUSAN DAUN SIRIH (PIPPER BETLE LINN) DALAM AIR MINUM TERHADAP BOBOT POTONG DAN PRESENTASE KARKAS KELINCI LOKAL Royadi, Royadi; Nur, Hanafi; Malik, Burhanudin
Jurnal Peternakan Nusantara Vol. 2 No. 2 (2016)
Publisher : Universitas Djuanda Bogor

Penelitian ini bertujuan untuk mengamati pengaruh pemberian air rebusan daun sirih dalam air minum terhadap bobot potong dan presentase karkas kelinci lokal. Penelitian dilaksanakan dari bulan April 2015 sampai dengan Mei 2015 . Lokasi penelitian yaitu di PT. Indoanilab yang berada di Kampung Carang Pulang Rt 04 Rw 06 Desa Cikarawang, Kecamatan Dramaga, Kabupaten Bogor, Jawa Barat. Ternak yang digunakan dalam penelitian ini adalah kelinci lokal lepas sapih yang berumur 2 bulan. Jumlah ternak yang digunakan sebanyak 24 ekor dengan bobot badan rata-rata 1,5 kg. Pakan yang digunakan adalah pakan komersil berbentuk pellet merk Indofeed K-03 super. Penelitian ini menggunakan Rancangan Acak Lengkap Faktorial (RALF), terdiri dari 6 perlakuan masing-masing 3 taraf dosis/jumlah daun sirih yang direbus dan 2 taraf waktu/lama perebusan dengan 4 ulangan. Adapun perlakuan yang digunakan dalam penelitian yaitu faktor pertama, lama perebusan sebanyak 2 taraf yaitu : R1 = 10 menit dan R2 = 20 menit. Faktor kedua, jumlah daun sirih sebanyak 3 taraf yaitu : S1 = 250 gram/liter, S2 = 200 gram/liter, S3 = 150 gram/liter. Peubah yang diamati adalah bobot potong, bobot karkas dan presentase karkas. Pengolahan data dianalisis menggunakan SPSS 21. Hasil penelitian dengan menggunakan uji Duncan menunjukan bahwa pemberian air rebusan daun sirih dalam air minum terhadap bobot potong dan presentase karkas kelinci lokal tidak berbeda nyata (P>0,05).

Analisis Sentimen Pemanfaatan Artificial Intelligence di Dunia Pendidikan Menggunakan SVM Berbasis Particle Swarm Optimization Saepudin, Atang; Aryanti, Riska; Fitriani, Eka; Royadi, Royadi; Ardiansyah, Dian
Computer Science (CO-SCIENCE) Vol. 4 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i1.2921

The utilization of Artificial Intelligence (AI) in the field of education in Indonesia has witnessed significant developments in recent years. The advancements in AI technology have opened up new opportunities to enhance the quality of education, and address various challenges faced by the Indonesian education system. This has naturally sparked diverse opinions and comments from the public, particularly on the social media platform X/Twitter. This research focuses on sentiment analysis of reviews expressed on the X/Twitter social media platform. The primary goal of this study is to develop an effective sentiment analysis method by leveraging the Support Vector Machine (SVM) algorithm optimized with Particle Swarm Optimization (PSO) for feature selection. In this research, user reviews from X/Twitter were collected and analyzed to identify positive or negative sentiments within the context of each comment. The SVM algorithm was used to classify sentiments based on similarity to comments with known sentiments. Feature Selection PSO was employed to optimize the parameters within SVM to enhance sentiment analysis accuracy. The results of sentiment analysis on comments or tweets on the X/Twitter social media platform using both SVM and PSO-based SVM algorithms indicated that the PSO-based SVM algorithm achieved a higher accuracy. The SVM algorithm with feature selection PSO produced accuracy 89.50%, precision 86.98%, recall 93.00%, and AUC 0.964. Meanwhile, the SVM algorithm had accuracy 87.50%, precision 85.46%, recall 90.50%, and AUC 0.956. This demonstrates that the use of feature selection PSO in the SVM algorithm is capable of improving the accuracy of the results.

Qualitative Analysis of Transparency Efforts in Public Policy at the Village Level Royadi, Royadi; Afnan, Dikhorir; Wildanu, Eka
Jurnal Polisci Vol 1 No 1 (2023): vol 1 no 1 September 2023
Publisher : ann4publisher@gmail.com

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62885/polisci.v1i1.57

Qualitative Analysis of Transparency Efforts in Public Policy in Cikeduk Village, Depok District, Cirebon Regency, West Java, Indonesia. This research will explore various efforts made by Cikeduk Village officials in encouraging openness and transparency in the implementation of public policies. This research will analyze the information mechanisms provided, responses to public feedback, as well as changes in the level of government transparency and citizen participation in policy processes. Qualitative method as a research procedure that produces descriptive data in the form of written or spoken words of people and observable behavior. According to them, this approach is directed at the setting and the individual holistically. The result of this study is that public trust in the performance of the Cikeduk village apparatus is quite positive. This is marked by the sustainability of village government programs that as a whole can run smoothly. The performance of the village apparatus in providing the best service to the community is also considered reliable. The conclusion is that the village head must really be a leader for the entire community, not the leader of some groups, families, descendants, certain religions and tribes and so on. Community leader means a leader who is close to the community, protects, protects and at the same time serves his community.

PENERAPAN SISTEM INFORMASI AKADEMIK BERBASIS WEB MENGGUNAKAN METODE RAPID APPLICATION DEVELOPMENT Fitriani, Eka; Royadi, Royadi; Ardiansyah, Dian; Saepudin, Atang; Aryanti, Riska
Journal of Information System, Applied, Management, Accounting and Research Vol 8 No 4 (2024): JISAMAR (September-November 2024)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v8i4.1551

The world of technology is advancing rapidly in all fields every day, including education. Systems that support information delivery are now presented in applications or web platforms. SMK Negeri Pertanian requires an adequate information system to convey academic information to students and teachers and to manage student data at the school. To address this issue, it is necessary to implement a web-based academic information system at SMK Negeri Pertanian using the Rapid Application Development (RAD) method for system development. The Rapid Application Development (RAD) method was chosen because it emphasizes speed and flexibility, allowing the application to be completed more quickly. The developed academic information system will manage and display information such as teacher data, student data, subject data, grades, teaching schedules, and other academic-related information. The result of this implementation is an effective and efficient web-based information system for delivering academic information to students and teachers.

IMPLEMENTASI MODEL WATERFALL PADA SISTEM INFORMASI OPERASIONAL CAR BOOKING Royadi, Royadi; Ardiansyah, Dian; Saepudin, Atang; Aryanti, Riska; Fitriani, Eka
JURSIMA Vol 10 No 3 (2022): Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.492

Pada era globalisasi saat ini yang sangat dibutuhkan yaitu teknologi yang guna untuk menghasilkan informasi yang akurat dan cepat. Pihak perusahaan sering terjadi permasalahan terutama pihak pengelola kendaraan yaitu kesulitan dalam pendataan kendaraan operasional perusahaan karena masih menggunakan sistem yang manual dan memudahkan saat pembuatan laporan yang akan disampaikan pada pimpinan. Dengan masalah tersebut, maka dibuatkan suatu rancangan sistem informasi berbasis web yang dapat menangani masalah penggunaan kendaraan operasional perusahaan dengan tujuan pengolahan data kendaraan dapat lebih rapih dan tersimpan pada suatu database. Aplikasi Perancangan Operasional Pemesanan Mobil berbasis web ini menggunakan Framework laravel 7.0 dan pemrograman bahasa menggunakan PHP 7, HTML, Bootstrap 5 dan Javascript. Data dasar yang digunakan adalah Sqlservel 2012. Metode pengembangan perangkat lunak yang digunakan yaitu model waterfall. Hasil dari sistem yang dibuat sangat memudahkan pengelola kendaraan operasional dalam proses pendataan penggunaan kendaraan operasional perusahaan menjadi lebih efektif dan efisien dibandingkan dengan proses yang masih dilakukan secara manual sehingga dalam proses pembuatan laporan juga lebih mudah dan optimal.Kata Kunci: Sistem Informasi, Pemesanan Mobil, Laravel

Implementasi Sistem Informasi Inventory Barang di Sekolah Berbasis Website Menggunakan Metode Rapid Application Development Royadi, Royadi; Ardiansyah, Dian; Saepudin, Atang; Aryanti, Riska; Fitriani, Eka
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 6, No 1: JUNI 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v6i1.6433

Pengelolaan data inventaris barang di lingkungan sekolah masih banyak dilakukan secara manual, sehingga rentan terhadap kesalahan pencatatan, kehilangan data, dan sulitnya akses informasi. Penelitian ini bertujuan untuk mengimplementasikan sistem informasi inventory berbasis website sebagai solusi digital yang dapat meningkatkan efisiensi dan akurasi dalam pengelolaan inventaris. Perkembangan teknologi informasi yang pesat ini dengan penerapan sistem informasi berbasis web yang dapat digunakan untuk mengelola data inventaris secara terstrutur dan rapi. Metode Rapid Application Development (RAD) digunakan dalam pengembangan sistem ini karena mampu mempercepat proses pembuatan aplikasi melalui tahapan prototyping dan keterlibatan aktif pengguna. Sistem yang dihasilkan memungkinkan pencatatan, pemantauan, dan pelaporan data inventaris secara real-time dan terstruktur. Hasil implementasi menunjukkan bahwa sistem dapat mempercepat alur kerja, memudahkan akses informasi, serta meningkatkan transparansi dan akuntabilitas. Dengan demikian, penggunaan metode Rapid Application Development (RAD) dalam pengembangan sistem inventory berbasis web terbukti efektif dalam memenuhi kebutuhan manajemen inventaris di sekolah secara lebih modern dan efisien.

Analisis Sentimen Pemanfaatan Artificial Intelligence di Dunia Pendidikan Menggunakan SVM Berbasis Particle Swarm Optimization Saepudin, Atang; Aryanti, Riska; Fitriani, Eka; Royadi, Royadi; Ardiansyah, Dian
Computer Science (CO-SCIENCE) Vol. 4 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i1.2921

The utilization of Artificial Intelligence (AI) in the field of education in Indonesia has witnessed significant developments in recent years. The advancements in AI technology have opened up new opportunities to enhance the quality of education, and address various challenges faced by the Indonesian education system. This has naturally sparked diverse opinions and comments from the public, particularly on the social media platform X/Twitter. This research focuses on sentiment analysis of reviews expressed on the X/Twitter social media platform. The primary goal of this study is to develop an effective sentiment analysis method by leveraging the Support Vector Machine (SVM) algorithm optimized with Particle Swarm Optimization (PSO) for feature selection. In this research, user reviews from X/Twitter were collected and analyzed to identify positive or negative sentiments within the context of each comment. The SVM algorithm was used to classify sentiments based on similarity to comments with known sentiments. Feature Selection PSO was employed to optimize the parameters within SVM to enhance sentiment analysis accuracy. The results of sentiment analysis on comments or tweets on the X/Twitter social media platform using both SVM and PSO-based SVM algorithms indicated that the PSO-based SVM algorithm achieved a higher accuracy. The SVM algorithm with feature selection PSO produced accuracy 89.50%, precision 86.98%, recall 93.00%, and AUC 0.964. Meanwhile, the SVM algorithm had accuracy 87.50%, precision 85.46%, recall 90.50%, and AUC 0.956. This demonstrates that the use of feature selection PSO in the SVM algorithm is capable of improving the accuracy of the results.

Sentiment Analysis of E-Grocery Application Reviews Using Lexicon-Based and Support Vector Machine Aryanti, Riska; Fitriani, Eka; Royadi, Royadi; Ardiansyah, Dian; Saepudin, Atang
Jurnal Riset Informatika Vol. 6 No. 3 (2024): June 2024
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v6i3.301

This research aims to conduct sentiment analysis of e-grocery application reviews using the Support Vector Machine (SVM) algorithm. Sentiment analysis is used to distinguish between positive and negative reviews by users who have provided reviews so that an evaluation of the services offered can be made. This research uses scraping techniques to obtain all the needed review data, focusing only on reviews of the Segari and Sayurbox applications. Datasets were collected from reviews using a library in Python, namely, google-play-scraper, obtained by the sayurbox application 4235 reviews and the segari application 5575. The dataset collected does not yet have a label, and the labeling process is impossible to perform manually by looking at the reviews one by one because it takes a long time and requires an expert in the field of language who can interpret the reviews and group them into positive and negative sentiments. Therefore, the sentiment-labeling process applies a lexicon-based method that works based on the inset lexicon dictionary by calculating each review's polarity value. The analysis process of this research uses the SVM algorithm because the SVM method has been proven to provide consistent and accurate results in various classification tasks, including sentiment analysis. The results show that the lexicon-based method and SVM produce good accuracy in determining the sentiment of e-grocery reviews, with a vegetable box application accuracy rate of 94%. In comparison, the segari application accuracy rate reached 97%.

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