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All Journal JURNAL PENGABDIAN KEPADA MASYARAKAT JTT (Jurnal Teknologi Terpadu) Jurnal Informatika IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Mantik Penusa JIPN (Journal of Informatics Pelita Nusantara) Martabe : Jurnal Pengabdian Kepada Masyarakat JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Sains dan Teknologi TRIDARMA: Pengabdian Kepada Masyarakat (PkM) JATI (Jurnal Mahasiswa Teknik Informatika) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) MEANS (Media Informasi Analisa dan Sistem) Journal of Soft Computing Exploration INCODING: Journal of Informatics and Computer Science Engineering Bulletin of Information Technology (BIT) Kode : Jurnal Bahasa Archive: Jurnal Pengabdian Kepada Masyarakat PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Journal of Artificial Intelligence and Engineering Applications (JAIEA) Innovative: Journal Of Social Science Research Sasambo: Jurnal Abdimas (Journal of Community Service)
Insan Taufik
Universitas Negeri Medan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Pengembangan Aplikasi Perkuliahan Interaktif dengan Fitur Pemilihan Posisi Duduk Mahasiswa untuk Meningkatkan Interaksi Insan Taufik; Kana Saputra S; Fevi Rahmawati Suwanto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9308

Abstract

Penelitian ini mengembangkan sistem manajemen pembelajaran digital dengan fitur pemilihan posisi duduk mahasiswa secara manual berbasis antarmuka visual untuk meningkatkan efektivitas interaksi dosen-mahasiswa dalam lingkungan hybrid. Sistem yang dikembangkan mengintegrasikan tiga peran utama (admin, dosen, dan mahasiswa) dengan fitur unggulan pemantauan posisi duduk mahasiswa melalui grid interaktif. Metode pengembangan menggunakan pendekatan Agile melalui tahapan analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Hasil penelitian menunjukkan bahwa sistem berhasil dibangun dengan arsitektur multi-role yang mencakup modul manajemen kursus, sesi interaktif, presensi real-time, dan dashboard pemantauan. Pengujian fungsional dengan 44 responden mahasiswa menunjukkan semua modul berjalan dengan baik, sementara kuesioner kepuasan pengguna menghasilkan skor rata-rata 4,6 (dari skala 5). Sistem ini memberikan solusi inovatif untuk menciptakan lingkungan pembelajaran yang lebih personal dan interaktif, khususnya dalam konteks kelas besar perguruan tinggi.
Prediksi Penjualan Produk Makanan dan Minuman Ringan pada PT. Sinar Niaga Sejahtera Menggunakan Metode Holt-Winters Berbasis Website Lubis, M. Revano Ananda; Taufik, Insan; Al Idrus, Said Iskandar; Arnita, Arnita; Syahputra, Hermawan
INCODING: Journal of Informatics and Computer Science Engineering Vol 5, No 2 (2025): INCODING OKTOBER
Publisher : Mahesa Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34007/incoding.v5i2.1024

Abstract

PT. Sinar Niaga Sejahtera is a food and beverage distribution company that still relies on conventional methods to determine stock levels, often facing inventory management challenges due to fluctuations in market demand. This study aims to predict sales of the 15 best-selling products at the Tebing Tinggi branch using the Holt-Winters method, based on a website that provides historical sales data from January 2021 to December 2024. The research stages include problem identification, data collection, application of the Holt-Winters method, model evaluation using Mean Absolute Percentage Error (MAPE), and implementation of a website-based system. The results of the study on one product, Garuda Atom Original, show optimal parameters of α = 0.1, β = 0, and γ = 0.8 with an MAPE value of 5,703115%, which is classified as very good. The implementation of a website-based sales prediction system makes it easier for administrators to manage product data, record sales data, and obtain prediction results in the form of informative graphs and tables, thereby helping the company reduce the risk of overstocking or understocking and supporting more effective data-driven decision-making.
Classification of Purple Passion Fruit Ripeness Levels Using Convolutional Neural Network (CNN) Siregar, Mochammad Gani Alfa Alkhoiri; Said Iskandar Al Idrus; Hermawan Syahputra; Insan Taufik; Kana Saputra S
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1787

Abstract

Passiflora edulis Sims (purple passion fruit) is a fruit that offers numerous health benefits and possesses high economic value. However, the manual assessment of ripeness by traders tends to be subjective and inconsistent, leading to post-harvest losses of up to 50%. This study developed a classification model for determining the ripeness level of purple passion fruit using a Convolutional Neural Network (CNN) and implemented it in a web-based application. The CNN model was designed to classify four ripeness stages (unripe, half-ripe, ripe, and rotten) with the addition of a non-passion-fruit class to enhance the system’s robustness. The dataset consisted of 2,000 images divided into five classes: four ripeness levels of purple passion fruit (unripe, half-ripe, ripe, and rotten) and one non-passion-fruit class as a comparator. All images were in JPG and PNG formats. The CNN architecture comprised four convolutional layers with 16, 32, 64, and 128 filters, respectively. Evaluation of various data-splitting ratios (80:20, 70:30, 60:40) and learning rates (0.001, 0.0001, 0.01) showed that the optimal configuration was achieved at a ratio of 80:20 with a learning rate of 0.001, resulting in a training accuracy of 96.72% and a testing accuracy of 95.76%, with a loss value of 0.1811. Validation using 5-Fold Cross Validation produced an average accuracy of 95.40%. The model was integrated into a web application developed using Flask and JavaScript, deployed on the PythonAnywhere cloud platform, enabling users to upload images and automatically obtain ripeness predictions to assist traders in sorting fruits more quickly and accurately.
Co-Authors Abdul Ghofur Abdul Ghofur Adisaputera, Abdurrahman Ahmad Landong Alfattah Atalarais Amran Sitohang Andriyani S, Rahayu Antonius Purba Arjon Samuel Sitio Arnita Arnita Arnita Arnita Chairunisah Chairunisah, Chairunisah Dinda Farahdilla Dharma Dinda Kartika Fachry Abda El Rahman Farhan Ramadhan, Haikal Fevi Rahmawati Suwanto Fitra, Awaludin Fristy Riandari Hafiz Harahap, Fauzan Hasugian , Paska Marto Hermawan Syahputra Ihsan Zulfahmi Irham Ramadhani Isda Pramuniati Izwita Dewi Kana Saputra S Kuraini, Atifa Nuzulul Latifah Hasibuan, Najwa Lili Tansliova Lubis, Afiq Alghazali Lubis, M. Revano Ananda MANSUR AS Mhd Hidayat Mhd Hidayat Mohammed Hafizh Al-Areef Muhammad Noer Fadlan Muhammad, Fachrezzy Muthmainnah, Inna Nadilla Putri, Rezkya Nasution, Hamidah . Niska, Debi Yandra Nurliani Manurung Pane, M Iqbal Anata Pane, Yeremia Yosefan Parapak, R Putri Angela Pinem, Josua Purba, Boy Hendrawan Putri, Rezkya Nadilla Raiyan Fairozi Said . Iskandar Samosir, Wahyu Ardiantito Saragih, Vinny Ramayani Sasalia S, Putri Simamora, Elmanani Sinaga, Marlina Setia Siregar, Angginy Akhirunnisa Siregar, Ary Prandika Siregar, Mochammad Gani Alfa Alkhoiri Sri Mulyana SUSIANA Syawali, Yusfi Syifa Cendikia, Yolanda Tarigan, Yosua Yosephine Tengku Ratna Soraya Tiopan Pandapotan Purba, Yeremia TONNI LIMBONG Trisnawati Hutagalung Wahabi Hasibuan, Rahman Warjaya, Angga Wete Polili, Andi Wete Polili, Andi Yulita Molliq Rangkuti Yulita Molliq Rangkuti Zulfahmi Indra, Zulfahmi