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All Journal Technomedia Journal JURNAL ABDIMAS TRIDHARMA MANAJEMEN Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB
Yulianto, Yogi
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media

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MOTIVASI UNTUK MEMBANGKITKAN SEMANGAT DALAM MENGHADAPI WABAH COVID 19 Krisnaldy, Krisnaldy; Inayah, Intan Nur; Fauziah, Almaidah; Meilani, Yosepha Lusiana; Dermawan, Yuda; Yulianto, Yogi
Jurnal Abdimas Tri Dharma Manajemen Vol. 2 No. 2 (2021): ABDIMAS April 2021
Publisher : Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/ABMAS.v2i2.p107-114.y2021

Abstract

Tujuan dari kegiatan Pengabdian Kepada Masyarakat ini adalah untuk melaksanakan salah satu Tri Dharma Perguruan Tinggi. Selain itu, melalui kegiatan Pengabdian Kepada Masyarakat ini mahasiswa diharapkan dapat memberikan kontribusi besar kepada pengembangan dan penerapan keilmuan dalam masyarakat. Metode kegiatan yang digunakan adalah tim pelaksana mengunjungi Karang Taruna Kelurahan Pamulang barat Kota Tangerang Selatan dan memberikan penyuluhan tanggal 21 Maret 2021. Kegiatan pengabdian dilakukan dengan cara memberikan penyuluhan mengenai apa yang perlu diperhatikan dalam menghadapi wabah covid 19 diantaranya memperhatikan kesehatan rohani , cara pola pikir, memilah informasi yang didapat dan dengan memberikan edukasi tentang motivasi. Masa pandemi covid-19 seperti ini, sangat mudah untuk mengalami kesulitan untuk mendapatkan motivasi. Di tengah situasi yang serba tidak pasti seperti sekarang ini orang-orang bisa dengan mudah mengalami putus asa yang tentunya hal ini juga bisa menyebabkan stres yang meningkat. Dengan memberikan penyuluhan, maka Karang Taruna memperoleh berbagai macam informasi dan strategi-strategi mengenai bagaimana untuk tetap produktif selama menghadapi wabah covid 19. Kata kunci : Motivasi, Pandemic Era
Implementasi Algoritma Boyer-Moore Pada Chatbot Wisata Yogyakarta salisah, Tuhfatus; Sari, Bunga Permata; Yulianto, Yogi; Hartanto, Anggit Dwi
Technomedia Journal Vol 5 No 1 Agustus (2020): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (737.792 KB) | DOI: 10.33050/tmj.v5i1.1189

Abstract

As the development of technology and increasing newcomers to the city of Yogyakarta, so that the need for information about tourism related in Yogyakarta is also higher. Yogyakarta tourism growth is increasing very rapidly every year as many local and foreign tourists visit the city known as the student town. Therefore, the author intends to build a chatbot that serves as a Virtual Assistant for Yogyakarta tourists. This chatbot is able to provide information to travellers through data stored on the system. The implementation and design of the software resulted in a chatbot built using the Boyer-Moore algorithm. The Boyer-Moore algorithm works by comparing patterns ranging from right to left, so this algorithm becomes an efficient search solution. If there is a pattern string mismatch then the pattern will move towards the left, this gesture will give information how many shifts to match the character that corresponds to the initial pattern. The Boyer-Moore algorithm has an edge over time finding patterns in larger file sizes. From the test results verification, validity submission, and prototype testing conducted on the chatbot system can run well according to the planning. Keywords : chatbot, boyer-moore, touris, tour
Named Entity Recognition dan Analisa Jarak dengan Formula Haversine pada P2P Lending yulianto, yogi; Maricha Oki Nur Haryanto, Erry; Dwi Insani, Fajar; Dwi Anggraeni, Meita; Anggono, Aji
Jurnal SIGMA Vol 16 No 2 (2025): September 2025
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v16i2.7135

Abstract

Named Entity Recognition (NER) is a core task in natural language processing for extracting structured entity information from text. However, funding descriptions on peer-to-peer lending platforms are largely unstructured. This limits reliable identification of funding categories and location-related entities required for subsequent analysis. This study addresses this problem by applying Named Entity Recognition to identify agricultural entities from peer-to-peer lending funding descriptions in Indonesia, combining it with distance analysis. The data used in this study was collected from peer-to-peer lending platforms in Indonesia using web crawling techniques with the Python Selenium library. The collected funding data was used to train and test a Named Entity Recognition model developed using the spaCy library, with entity labeling performed using the Beginning–Inside–Outside (BEIN–IND–OUTS) tagging scheme. Model performance was evaluated using a confusion matrix at the token level. The evaluation results showed that the proposed model achieved 83% accuracy, 94% precision, 82.7% recall, and a 90% F1 score, indicating its ability to detect agricultural entities from lighting descriptions. Furthermore, the collected data containing agricultural entities was processed using the Haversine formula to calculate the distance between the lender and the borrower's location. When compared to Google Maps, the average distance difference was 23.7 kilometers. These results demonstrate that Named Entity Recognition combined with distance analysis can support the preparation of peer-to-peer lending data for further decision-making.
Co-Authors Anggit Dwi Hartanto, Anggit Dwi Anggono, Aji Dermawan, Yuda Dwi Anggraeni, Meita Dwi Insani, Fajar Fauziah, Almaidah Haryanto, Emon Inayah, Intan Nur Krisnaldy, Krisnaldy Maricha Oki Nur Haryanto, Erry Meilani, Yosepha Lusiana salisah, Tuhfatus Sari, Bunga Permata Usman Wijaya