Article Per Year (5 Year)
p-Index From 2021 - 2026
0.751
P-Index
This Author published in this journals
All Journal The IJICS (International Journal of Informatics and Computer Science) Journal of Computer Networks, Architecture and High Performance Computing Ulead : Jurnal E-pengabdian Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif
Tarigan, Nera Mayana Br
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Other

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
PKM PEMBUATAN APLIKASI DAN PELATIHANPENGGUNAAN APLIKASI PENILAIAN KINERJA GURU SMK 2 DELIMA SARI TIGA JUHAR Tarigan, Eviyanti Br; Tarigan, Nera Mayana Br; Sinaga, Bosker; Simamora, Erli Susanti
Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif Vol. 2 No. 1 (2024): Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif
Publisher : PT. Gelora Cipta Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Perkembangan teknologi informasi tidak hanya berperan dalam bidang bidang perekonomian, dan bidang pertanian namun juga bidang pendidikan sudah menggunakan teknologi. SMK 2 Delima Sari Tiga Juhar dalam penggunaan teknologi informasi masih belum maksimal contohnya belum adanya penggunaan teknologi khususnya aplikasi dalam penilaian kinerja guru sehingga setiap akhir semester tidak ada pemacu guru-guru untuk menjadi yang terbaik. Kurangnya sosialisasi dalam pemanfaatan aplikasi mengakibatkan aplikasi penilaian kinerja guru belum dibangun di SMK 2 Delima Sari Tiga Juhar. Pelatihan penggunaan juga harus dilakukan agar terbiasa dengan tool-tool aplikasi yang disediakan. Hal inilah yang melatar belakangi tim pengabdian untuk memberikan sosialisasi pelatihan “PKM Pembuatan Aplikasi dan Pelatihan Penggunaan Aplikasi Penilaian Kinerja Guru SMK 2 Delima Sari Tiga Juhar”. Kegiatan ini dilaksanakan di SMK 2 Delima Sari Tiga Juhar dengan metode sosialisasi dan praktik langsung dalam penggunaan aplikasi. Pembuatan aplikasi dapat membantu pihak SMK 2 Delima Sari Tiga Juhar dalam penilaian kinerja guru. Aplikasi dilakukan pelatihan dan admin yang ditugaskan dalam mengelolap apalikasi dapat dan cepat menggunakan aplikasi tersebut. Dari pernyataan tersebut bahwa aplikasi yang dibangun mudah untuk dipahami dan dapat mengelola data penilaian guru.
PKM Pembuatan Dan Pelatihan Aplikasi Pemilihan Bibit Lele Terbaik Tarigan, Nera Mayana Br; Barus, Eviyanti Br; Sinaga, Bosker; Sembiring, Abdi Agustianta; Siregar, Nurika Sari
ULEAD : Jurnal E-Pengabdian Volume 4 Nomor 2 Januari 2025
Publisher : Fakultas Ilmu Komputer, Universitas Katolik Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/ulead.v4i2.4616

Abstract

Program Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk mendukung para pembudidaya ikan lele dalam memilih bibit unggul dengan memanfaatkan aplikasi berbasis teknologi. Kendala utama yang sering dihadapi adalah minimnya pemahaman dalam menentukan kualitas bibit yang baik, sehingga berpengaruh terhadap rendahnya tingkat keberhasilan dalam budidaya. Kegiatan ini mencakup pengembangan serta pelatihan penggunaan aplikasi yang dirancang untuk membantu proses seleksi bibit lele berdasarkan sejumlah kriteria, seperti ukuran, kesehatan, dan tingkat kelincahan ikan. Pelaksanaan program dilakukan dalam beberapa tahapan, mulai dari perancangan aplikasi, pengujian, hingga sosialisasi dan pelatihan kepada pembudidaya. Berdasarkan hasil pelaksanaan, aplikasi yang dikembangkan terbukti mampu meningkatkan efisiensi dalam pemilihan bibit serta memperluas wawasan peserta mengenai karakteristik bibit lele berkualitas. Dengan demikian, program ini diharapkan dapat memberikan kontribusi positif terhadap peningkatan produktivitas dan keberlanjutan usaha budidaya lele di kalangan masyarakat.
Analysis of Detergent Inventory Stock at Luch Laundry Using the Linear Regression Method Sinaga, Bosker; Tarigan, Nera Mayana Br; Marpaung, Rahmadina; Zamili, Kristof Rian
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5396

Abstract

Inventory stock management is an important aspect in the laundry business to ensure smooth operations and minimize costs. Laundry Detergent shortages or overstocks can cause service disruptions and unnecessary additional costs. Therefore, a method is needed that can help predict stock needs accurately, one of which is the linear regression method. The data used includes historical data on detergent use and other factors that influence demand over several time periods. Through linear regression analysis, a predictive model can be built to estimate detergent needs in the future, so that stocks can be managed more efficiently. Research Method, namely the survey research method, is a research method carried out using surveys or direct data collection from Laundry Luch. The method/algorithm used to analyze the data is the linear regression method. The aim of this research is to apply the linear regression method in detergent inventory stock and to carry out analysis using the linear regression method in detergent inventory stock. The research results from the data that have been collected show that the predicted stock of detergent supplies for Laundry Luch in January 2025, with an estimated total usage of 111 boxes of detergent and a target usage of 95 boxes of detergent, is 129 boxes of detergent. The research conclusion is that the linear regression method provides real benefits in supporting data-based decision making.
Implementation of K-Nearest Neighbor Algorithm for Scientific Determination of Aid Recipients at STM Agape Sinaga, Dedi Candro Parulian; Siahaan, R. Fanry; Tarigan, Nera Mayana Br; Lubis, Rodiah Hannum; Amallia, Dwi Novia
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 3 (2025): November
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i3.9484

Abstract

Providing assistance to underprivileged families is an important social effort to enhance community welfare; however, the selection of aid recipients often encounters problems such as subjectivity, unstructured data, and time inefficiency when conducted manually. This study aims to develop and evaluate a decision support system for determining aid recipients at STM Agape using the K-Nearest Neighbor (KNN) algorithm to improve accuracy and objectivity in the selection process. The research methodology employed a quantitative classification approach, where data were collected from families based on predefined criteria, including family income, number of dependents, housing conditions, and the occupation of the head of the household. The dataset was divided into training and testing data, and all attributes were normalized prior to processing. The KNN algorithm was applied using Euclidean distance to measure similarity between data instances, classifying each family into “eligible” or “ineligible” categories. The results indicate that the proposed system achieved higher classification accuracy and more consistent decision outcomes compared to manual selection methods. Additionally, the implementation of KNN reduced processing time and minimized subjective bias in determining aid recipients. These findings demonstrate that the KNN-based system is effective as a decision support tool, enabling STM Agape to distribute social assistance in a more targeted, objective, transparent, and efficient manner.
Co-Authors Amallia, Dwi Novia Barus, Eviyanti Br Bosker Sinaga Lubis, Rodiah Hannum Marpaung, Rahmadina Sembiring, Abdi Agustianta Siahaan, R. Fanry Simamora, Erli Susanti Sinaga, Dedi Candro Parulian Siregar, Nurika Sari Tarigan, Eviyanti Br Zamili, Kristof Rian