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All Journal Jurnal Armada Informatika Jurnal Pengabdian Masyarakat dan Riset Pendidikan Journal of Computer Science Artificial Intelligence and Communications
Sri Ramadhany
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Humanities Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Engineering Languange, Linguistic, Communication & Media Mathematics Other

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Analysis of Historical Student Visit Data Using Time Series Algorithm Sri Ramadhany; Sahara Abdy; Alfiarini
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 2 (2024): November 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i2.16

Abstract

The analysis of historical student visit data plays a critical role in understanding student behavior, optimizing campus resources, and enhancing service delivery in educational institutions. This study presents an analytical approach to examine patterns and trends in student visitations using a time series algorithm. By leveraging historical datasets from campus access logs, we aim to identify periodic behaviors, peak visitation times, and anomalies that may reflect special events or system irregularities. The research employs time series methods such as moving average, exponential smoothing, and ARIMA (AutoRegressive Integrated Moving Average) to forecast future student visit patterns based on previous trends. Data preprocessing, normalization, and visualization techniques are applied to ensure data quality and interpretability. The results demonstrate that student visits tend to follow specific weekly and monthly patterns, with increased activity near academic deadlines or events. The ARIMA model, in particular, shows strong predictive accuracy with minimal error margin. This analysis not only provides insights for administrative planning—such as scheduling staff, managing facilities, or enhancing security—but also serves as a foundation for developing intelligent decision-support systems. In conclusion, applying time series algorithms to historical student visitation data proves effective in predicting future trends, thereby supporting data-driven decision-making processes within educational institutions.
Implementasi Algoritma Perceptron dalam Penentuan Pola Pemilihan Panitia Pemungutan Suara (Studi Kasus: Kelurahan Pulo Brayan Bengkel) Sri Wahyuningsih; Raudhah; Sahara Abdy; Sri Ramadhany; Tomy Satria Alasi
Jurnal Armada Informatika Vol 7 No 2 (2023): Jurnal Armada Informatika : Edisi Desember
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v7i2.84

Abstract

Dalam beberapa pemilu terakhir, baik pemilihan legislatif dan eksekutif (presiden dan kepala daerah), isu penyelenggara yang diduga tidak independen dan kecurangan selalu mewarnai hasil pemilu. Kelurahan Pulo Brayan Bengkel adalah merupakan salah satu kelurahan di Kota Medan yang memiliki KPPS dibawah kendali KPU Kota Medan. Masalah yang terdapat dalam penelitian ini adalah faktor-faktor apa yang menjadi penyebab lemahnya panita pemungutan suara (PPS) dan kelompok penyelenggara pemungutan suara (KPPS), dan bagaimana proses rekrutment PPS dan KPPS untuk memperoleh pemilu yang berkualitas dan berintegrasi dikaitkan dengan pola rekrutmen dari penyelenggra pemilu. Jaringan Saraf Tiruan (Artificial Neural Networks) adalah salah satu cabang ilmu dari bidang ilmu kecerdasan buatan. Salah satu model jaringan JST adalah perceptron yang digunakan untuk mengenali pola karakter, simbol. Dengan menentukan nilai input, bobot, bias dan target atau ouput. Seleksi berkas, ujian tulis dan wawancara merupakan nilai input diubah kedalam bilangan biner yang terdiri dari angka 0 dan 1. Nilai bobot akan berubah pada setiap iterasi perulangan. Nilai bias juga akan berubah pada setiap interasi perulangan sampai target/output tercapai. Target atau target dari pelatihan ini adalah diterima atau tidak diterima yang dikonversikan ke biner menjadi 1 dan 0. Pengujian perceptron menggunakan software Matlab. Hasil dari pengujian target/output tercapai pada epoch ke-3.
Optimalisasi Pemasaran Produk Olahan Makanan melalui Penerapan Strategi Digital Marketing bagi UMKM di Medan Hendra Jonathan Sibarani; Yenni; Nora Anisa Br Sinulingga; Sari Mariahma Nova Sipayung; Sri Ramadhany; Sahara Abdy; Denni; Errie Margery; Ali Syah Putra; Debora Tambunan
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.3827

Abstract

The development of digital technology has significantly changed product marketing patterns, including for Micro, Small, and Medium Enterprises (MSMEs). It is known that many MSME food processing actors in Medan Marelan District have not been able to take advantage of the potential of digital marketing optimally in developing their businesses. The main problems faced include limited knowledge about digital marketing strategies, lack of ability to manage business social media, and lack of understanding of the importance of digital content-based promotion. This Community Service Activity (PKM) aims to empower food processing MSME actors in Medan Marelan through training and assistance in the implementation of digital marketing strategies to increase marketing reach and product competitiveness. The method of implementing activities includes the socialization stage, theoretical training on the basic concepts of digital marketing, direct practice of creating business accounts, creating promotional content, using marketplaces and social media, and evaluating the results of mentoring. The results of the activity showed that participants experienced an increase in knowledge and skills in the application of digital marketing. Business actors are starting to be able to create and manage business accounts independently, create attractive promotional content, and utilize various digital platforms such as Instagram, Facebook, and TikTok to expand the market.
Co-Authors Alasi, Tomy Satria Alfiarini Ali Syah Putra Debora Tambunan Denni Errie Margery Hendra Jonathan Sibarani Nora Anisa Br. Sinulingga Raudhah Sahara Abdy Sari Mariahma Nova Sipayung Yenni