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All Journal Jurnal Informatika dan Teknik Elektro Terapan ELINVO (Electronics, Informatics, and Vocational Education) Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Teknologika CSRID
Cepi Rahmat Hidayat
Universitas Perjuangan Tasikmalaya
Religion Agriculture, Biological Sciences & Forestry Arts Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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ANALISIS PERBANDINGAN FRAMEWORK FRONT-END JAVASCRIPT SOLIDJS DAN VUEJS PADA PENGEMBANGAN WEBSITE INTERAKTIF Moch Fikri Khoirurrizal; Cepi Rahmat Hidayat; Ruuhwan Ruuhwan
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 2 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i2.4106

Abstract

Abstrak. Penelitian ini membandingkan performa dan efisiensi antara dua framework front-end JavaScript, yaitu SolidJS dan VueJS, dalam pengembangan website interaktif. Menggunakan metode kuantitatif dengan pengujian lapangan, penelitian ini menganalisis waktu proses dan penggunaan sumber daya dari kedua framework. Hasilnya menunjukkan bahwa SolidJS memiliki performa dan efisiensi yang lebih baik daripada VueJS dalam mayoritas skenario pengujian kecuali skenario. Analisis statistik juga menunjukkan perbedaan yang signifikan antara kedua framework. Sebagai rekomendasi, SolidJS layak dipertimbangkan bagi pengembang website interaktif, meskipun VueJS memiliki stabilitas yang lebih baik.Keywords: Framework; Front-End; JavaScript; SolidJS; VueJS.
PENERAPAN DATA MINING CLASSIFICATION UNTUK PENENTUAN JENIS BANTUAN SOSIAL MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Shinta Siti Sundari; Evi Dewi Sri Mulyani; Cepy Rahmat Hidayat; Dede Syahrul Anwar; Teuku Mufizar
Computer Science Research and Its Development Journal Vol. 16 No. 1 (2024): February 2024
Publisher : LPPM Universitas Potensi Utama

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Abstract

The social assistance program is a program held by the government as an effort to overcome poverty. Mekarjaya Village is one of the villages running the program. In carrying out this social assistance process, there are obstacles in terms of collecting data on its citizens because there are often discrepancies in the recipient data collected by the community with the type of assistance. To make it easier to determine the appropriate type of social assistance, an analysis of the data on the recipients of the social assistance is needed. The data analysis method in this research uses Data Mining including Data Selection and Preprocessing, while the classification method uses the Naïve Bayes Classifier. Testing using the Confusion Matrix produces an accuracy of 94.53% with a comparison of training data and testing 80:20. With this model, it is hoped that village officials can determine the type of social assistance that is appropriate for the community.
Empowerment of Posyandu Cadres in Tuguraja Village with Digitalization and Creative Health Innovations Shinta Siti Sundari; Evi Dewi Sri Mulyani; Teuku Mufizar; Ayu Rahmawati; Agus Supriatman; Rudi Hartono; Cepi Rahmat Hidayat; Dede Syahrul Anwar
ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 8 No. 1 (2025): ABDIMAS UMTAS: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Muhammadiyah Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35568/abdimas.v8i1.5587

Abstract

One type of community-based health initiative that are planed and organized from, by, for and with the community is called Posyandu. The involvement of cadres is also essential to the success of Posyandu operations, they are responsible for establishing a connection between the community and health professionals or specialist  and helping to assisting and identify health needs. Cadres are also required to be able to provide information for health institutions that may not be able to reach the community directly, especially regarding Toddlers and the Elderly. With the development of technology towards digital, where the data management process is already based on Information Systems, it can provide ideas for cadres to use information systems as a tool to help their activity processes. The problems faced by cadres today are the lack of understanding regarding the use of digitalization as a medium for managing data and how to operate and maintain it. Meanwhile, in its current development, all stakeholders involved with Posyandu are already using the application. so we want to provide direct training regarding application use and maintenance, by conducting interviews and observations first . The results of the activities that have been carried out obtained results that with socialization and training regarding the importance of innovation with digitalization in posyandu services, they were able to understand and implement what was conveyed by the PKM team and could be realized optimally
SISTEM INFORMASI GEOGRAFIS (SIG) UNTUK PEMETAAN POTENSI DAN MANAJEMEN SUMBER DAYA DESA WISATA DI KABUPATEN TASIKMALAYA Cepi Rahmat Hidayat; Teuku Mufizar; Ariel Ivan Al-Hakim; Alfiyah Adwa
Jurnal Teknologika Vol 16 No 1 (2026): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v16i1.663

Abstract

Tasikmalaya Regency, located in West Java Province, has 92 Tourism Villages, but only 5 villages have developed status and the remaining 87 are still in the pilot status. Pilot villages have potential that has not been optimally managed and minimal visits, indicating an urgent need for tools to map and manage this potential so that they can be upgraded to a sustainable tourism destination. This study aims to design and build a Geographic Information System (GIS) for Potential Mapping and Resource Management of Tourism Villages in Tasikmalaya Regency, using the Waterfall software development model. This GIS is designed to visualize geospatial data on locations, assets, and potential categories of 87 pilot villages in an integrated manner. The web-based information system was successfully developed, proven by Black Box testing showing that the application runs as expected. Furthermore, the System Usability Scale (SUS) test produced a score of 75.5 (category "Good"), which indicates a high level of acceptability and ease of use. The implementation of GIS is expected to be a strategic solution for the Tourism Office and tourism village managers to identify, develop, and prioritize potential efficiently, in order to accelerate the improvement of the classification of tourism village status in Tasikmalaya Regency
Sentiment Analysis of Cooking Oil Prices in Indonesia Using the Long Short-Term Memory Method Evi Dewi Sri Mulyani; Cepi Rahmat Hidayat; Teuku Mufizar; Shinta Siti Sundari; Dede Syahrul Anwar; Ruuhwan; Jamal Ma'ruf; M. Akbar Kasyfurrahman
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 10 No. 1 (2025): May 2025
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v10i1.73972

Abstract

The policy that was intensively discussed from early January to March 2022 was related to the setting and lifting of the Highest Retail Price for cooking oil, which was proven by the busy news on television, print media and social media. Many responses or speculations arise as a result of this policy. The importance of research on public speculation or sentiment analysis is to create a system model and find out how the public responds to government policy after the Highest Retail Price for cooking oil is determined and revoked, which ranges from February 4 to March 31 2022, as a benchmark and material. government considerations in making policy. The data that was collected in the period after the Maximum Retail Price (MRP) was set amounted to 904 datasets, and after the repeal of the MRP, it amounted to 874. Research can function as a basis for completing important information to support public policy decisions. The data is trained to obtain an optimal model and can predict sentiment with the Long Short-Term Memory (LSTM) model. To get the best model, random parameter testing was carried out using 80% of the training data and 20% of the validation dataset. The test results in fairly good accuracy with the softmax activation function, with an accuracy of 82.34%.
Co-Authors Agus Supriatman Alfiyah Adwa Ariel Ivan Al-Hakim Ayu Rahmawati Dede Syahrul Anwar Evi Dewi Sri Mulyani Jamal Ma'ruf M. Akbar Kasyfurrahman Moch Fikri Khoirurrizal Rudi Hartono Ruuhwan Shinta Siti Sundari Teuku Mufizar Teuku Mufizar