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Aplikasi Kamus Bahasa Lembak Bengkulu Berbasis Android Menggunakan Algoritma Raita Nindyawati Nindyawati; Rozali Toyib; M Husni Rifqo; Eka Sahputra
Jurnal Sistem Informasi dan E-Bisnis Vol 3, No 2 (2021): Juli
Publisher : JUSIBI (Jurnal Sistem Informasi dan E-Bisnis)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (652.899 KB)

Abstract

Penggunaan Bahasa Lembak dalam kehidupan sehari khususnya suku Lembak sendiri semakin luntur akibat pengaruh globalisasi bahasa asing dan kurangnya perhatian orang tua dalam membudidayakan anak dan keturunannya, sehingga tidak mampu menguasai bahasa leluhurnya. Untuk mempercepat proses pencarian kosakata pada aplikasi kamus berbasis android maka diperlukan sebuah algoritma Raita yaitu salah satu metode dalam pencarian dengan mencocokan pola kata dari sebuah string dengan pola kata yang ingin dicari. Dengan menggunakan algoritma Raita waktu yang dibutuhkan untuk pencaraian terjemahan bahasa Indonesia ke lembak dan sebaliknya hanya sedikit dan dapat berlangsung dengan cepat.
Penerapan Metode Monte Carlo pada Simulasi Prediksi Jumlah Calon Mahasiswa Baru Universitas Muhammadiyah Bengkulu Yovi Apridiansyah; Ringgo Dwika Putra; Eka Sahputra
Jurnal Processor Vol 17 No 2 (2022): Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2022.17.2.1224

Abstract

Dengan adanya sistem simulasi prediksi jumlah mahasiswa baru ini, diharapkan dapat memprediksi jumlah mahasiswa baru yang masuk pada setiap tahun kedepan nya. Menerapkan metode Monte Carlo dan juga menerapkan aplikasi simulasi prediksi dapat mempermudah dalam menentukan jumlah penerimaan mahasiswa baru pada Universitas Muhammadiyah Bengkulu. Pengumpulan data yang dilakukan dengan cara obeservasi secara langsung ke objek dengan mengambil sampel data yang sudah ada di tahun 2015 – 2019. Dalam penelitian ini digunakan metode monte carlo untuk prediksi calon mahasiswa baru. Tujuan dari penelitian ini untuk mengetahui jumlah calon mahasiswa baru, yang diharapkan hasilnya dapat memberikan informasi dan masukan bagi pihak perguruan tinggi dalam membuat kebijakan kedepannya. Dari hasil pengujian ini didapatkan hasil bahwa dengan menerapkan metode monte carlo dapat memprediksi jumlah calon mahasiswa baru, dengan metode monte carlo dan tingkat akurasi sebesar 92.49 %.
Pelatihan Pengoperasian Microsoft Word dan Microsoft Excel Bagi Perangkat Desa dan Remaja di Desa Simpang Ketenong Kecamatan Kerkap Kabupaten Bengkulu Utara Khairullah; Eka Sahputra; Erwadi, Yetman
JURNAL ABDIMAS SERAWAI Vol. 3 No. 3 (2023): Jurnal Abdimas Serawai (JAMS)
Publisher : Program Studi Administrasi Fakultas Ilmu Sosial dan Ilmu Politik Universitas Muhammadiyah Bengkulu 

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jams.v3i3.5806

Abstract

Simpang Ketenong Village, Kerkap District, is classified as a self-sufficient village, with the characteristics that it has started using communication tools and technology, is not isolated and has fairly smooth traffic routes between villages and cities. (Saputera et al., 2021) Service is a process, this process produces a product in the form of a service, which is then provided to customers. Good service will also have a good impact on customers in the form of customer satisfaction, in line with findings in the field that the local village community and youth have begun to understand the importance of technology for convenience in daily work and can even support careers in the future. Along with the current development of communication technology, it has also encouraged village officials and youth in Simpang Ketenong village to be able to understand and operate computers to make work easier, both for village administration and other needs. Referring to the situation analysis above, the service team together with partners justified that the priority problems experienced by partners and the priorities agreed to be resolved were related to: the lack of skill of village officials and Simpang Ketenong Village Youth in operating computers, especially in typing and lack of understanding of how to use them. excel. Through this PKM program the team wants to contribute to providing skills to village officials and youth in the Simpang Ketenong Village area, Kerkap District, North Bengkulu Regency to be proficient in using Microsoft Word and Microsoft Excel applications. Based on the partner's problems, the solution that will be provided in this activity is to hold Microsoft Word and Microsoft Excel Operation Training, then an evaluation will be held of village officials and local teenagers will be able to be competent in the training process that has been carried out. The targets of this Community Service are time efficiency during service, reducing data errors in reporting the performance of village officials, being able to store village databases simply, increasing knowledge for village officials and youth so that they can learn about information systems through computer media.
Analisis sentimen publik terhadap calon presiden 2024 di instagram menggunakan metode naïve bayes Tamara Cindy Samsita Rani; Eka Sahputra
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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Abstract

In this research, an analysis of public sentiment towards presidential candidate pairs in Indonesia in 2024 was carried out via the social media Instagram. Indonesia itself is one of the countries with the highest number of Instagram users. One of the Instagram posts that is currently in the public spotlight found on the kompascom, najwashihab, and detikcom accounts which post news about the 2024 presidential candidate pairs. In these comments there are various kinds of comments ranging from positive things such as support to negative things such as commenting on the shortcomings of each candidate pair, for this reason text classification is carried out to find out public opinion about the presidential candidate pair. The comment classification process in this research uses the Naïve Bayes algorithm to determine positive, neutral and negative values from thousands of comments. The method that will be applied uses the Python programming language with confusion matrix testing to determine the level of accuracy in the model. Based on the test results, it can be concluded that the use of the Naïve Bayes algorithm used as a classification method in comment-based sentiment analysis on Instagram has a relatively good accuracy rate with an average accuracy of more than 60%.