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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) ARSY : Jurnal Aplikasi Riset kepada Masyarakat JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Journal Software, Hardware and Information Technology Journal of Mathematics and Scientific Computing With Applications Jurnal Sains dan Teknologi Jurnal Masyarakat Indonesia Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Jurnal Ilmu Komputer dan Sistem Informasi Jurnal Tiyasadarma: Jurnal Pengabdian Kepada Masyarakat Management of Information System Journal Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Kemitraan dan Pengabdian
Lubis, Arif Ridho
Politeknik Negeri Medan
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Prediction of Cyberbullying in Social Media on Twitter Using Logistic Regression Prayudani, Santi; Adha, Lilis Tiara; Ariyani, Tika; Lubis, Arif Ridho
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9842

Abstract

As cases of cyberbullying on social media increase, there is a need for efficient measures to detect the vice. This research aims to establish the application of machine learning algorithms in analyzing text on social media to determine potentially harmful comments using logistic regression. The first and most important research question of this study is to assess the extent to which the model is capable of correctly identifying the comments that contain features of cyberbullying and those that do not. The data set included comments from different social media sites and was preprocessed before further analysis was conducted on it. Exploratory Data Analysis was applied in the study to establish relationships and textual features with bullying behavior. As with any other model, after training and testing the model, the results were analyzed using parameters like precision, precision, gain, and F1 statistics. The outcomes of this study revealed that the use of logistic regression models can give a fairly satisfactory level of accuracy in identifying cyberbullying. In light of this, this study underscores the need to use machine learning algorithms to minimize negative actions in cyberspace.
Penerapan Aplikasi Pintar Tani Untuk Peningkatan Pemasaran Pertanian Pada Eco Farm di Desa Kelambir V Hasan Putra, Purwa; Julham, Julham; Lubis, Arif Ridho; Azanuddin, Azanuddin; Selvida, Desilia
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 5 No. 4 (2024): Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN) Edisi September - Desembe
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v5i4.4328

Abstract

Program Pengabdian Penerapan Aplikasi Pintar Tani bertujuan untuk membantu membuka wawasan petani agar semakin leluasa dalam mengolah lahan dan hasil pertanianya. Aplikasi Pintar Tani diharapkan dapat digunakan untuk berbagi ilmu tentang pertanian dan perternakan serta dapat mengoptimalkan pemasaran dari berbagai hasil pertanian. Belum adanya pemanfaatan teknologi informasi dengan maksimal dan masih minimnya pengetahuan masyarakat terhadap digitalisasi pemasaran produk pertanian dan perternakan. Sedangkan target khususnya adalah untuk pemberian aplikasi Pintar Tani, pemberian pelatihan penggunaan aplikasi, dan mengoptimalkan pemasaran hasil dari pertanian dan perternakan. Metode yang digunakan terdiri dari 4 tahapan yaitu: dimulai dari Tim Pengabdian Pintar Tani memahami permasalahan mitra, dari hasil analisis data, Menyusun solusi-solusi yang akan dilakukan untuk mengatasi permasalahan mitra, melaksanakan solusi-solusi yang ditawarkan dan terakhir melaukan publikasi pada media massa cetak,online, artikel ilmiah pada jurnal nasional sebagai luaran wajib, dan HKI (hak cipta) sebagai luaran tambahan.
WEB-BASED MANAGEMENT INFORMATION SYSTEM WITH CODEIGNITER FRAMEWORK Nst, Fifi Anggiani Br; Lubis , Arif Ridho; Sembiring, Boni Oktaviani
Journal of Mathematics and Scientific Computing With Applications Vol. 3 No. 1 (2022)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v3i1.58

Abstract

The need for shelter becomes very needed at this time, especially people from outside the city who want to work or continue their education to other cities. So that the need for boarding houses to increase and demand by many people. The system that is running on the full boarding house is still done manually where, there is no system that can help in managing his boarding house, where people who want boarding must come directly to see the facilities they have, room status and costs. And there is no system that can help the owner in managing boarding house payments. The development of this system uses the waterfall method. Web-based full boarding management information system can manage boarding payment data and tenant data management.
PKM DIGITALISASI SISTEM PRESENSI SISWA MELALUI APLIKASI DI MADRASAH ALIYAH SUNGGAL DESA TANJUNG GUSTA KEC SUNGGAL KAB DELI SERDANG SUMATERA UTARA Putra, Purwa Hasan; Julham, Julham; Lubis, Arif Ridho; Tasril, Virdyra; Mughnyanti, Mayang; Selvida, Desilia
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 2 (2025): Desember 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i2.5385

Abstract

Abstract: The Community Service Activity of Digitalizing Student Attendance System through Application was carried out at Sunggal Islamic High School, Tanjung Gusta Village, Sunggal District, Deli Serdang Regency, North Sumatra as an effort to improve the efficiency and accuracy of student attendance recording which was previously still done manually. The web-based digital attendance system developed by the PKM team from Medan State Polytechnic allows teachers and administrative staff to record student attendance quickly, securely, and can be accessed in real-time. The recording process which previously took 7 minutes per class can be cut to 2 minutes per class. The implementation method of the activity includes observing school needs, designing and developing the application, training for teachers and staff, and mentoring during implementation. The results of the activity show that this system not only improves work efficiency but also helps improve the digital literacy of teachers and school staff. Keyword: Digitalization, Attendance, Students, MAS Aliyah Sunggal Abstrak: Kegiatan Pengabdian Kepada Masyarakat Digitalisasi Sistem Absensi Siswa Melalui Aplikasi dilaksanakan di SMA Islam Sunggal, Desa Tanjung Gusta, Kecamatan Sunggal, Kabupaten Deli Serdang, Sumatera Utara sebagai upaya untuk meningkatkan efisiensi dan akurasi pencatatan kehadiran siswa yang sebelumnya masih dilakukan secara manual. Sistem absensi digital berbasis web yang dikembangkan oleh tim PKM dari Politeknik Negeri Medan ini memungkinkan guru dan tenaga administrasi untuk mencatat kehadiran siswa secara cepat, aman, dan dapat diakses secara real-time. Proses pencatatan yang sebelumnya membutuhkan waktu 7 menit per kelas dapat dipangkas menjadi 2 menit per kelas. Metode pelaksanaan kegiatan meliputi observasi kebutuhan sekolah, perancangan dan pengembangan aplikasi, pelatihan bagi guru dan tenaga kependidikan, serta pendampingan selama pelaksanaan. Hasil kegiatan menunjukkan bahwa sistem ini tidak hanya meningkatkan efisiensi kerja tetapi juga membantu meningkatkan literasi digital guru dan tenaga kependidikan sekolah. Kata kunci: Digitalisasi, Absensi, Siswa, MAS Aliyah Sunggal 
Optimization of Convolutional Neural Network for Classification of Hydroponic Vegetable Cultivation Using Machine Learning Lubis, Arif Ridho; Prayudani, Santi; Putra, Purwa Hasan; Lase, Yuyun Yusnida
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v7i1.7231

Abstract

In an effort to apply applied product innovation and support the improvement of hydroponic vegetable cultivation, it is based on several things. Among them are changes in the texture of the year, stems and vegetable quality. At this time the problems faced by hydroponic vegetable pickers, especially banyumas village youth organizations who have UMKM hydroponic vegetable cultivation. This situation will have an impact on problems and losses that result in a lack of yield and quality of harvested vegetables if not resolved quickly. The results of this study resulted in optimal accuracy performance in the classification of hydroponic vegetables with CNN, this study also successfully classified normal vegetables with vegetables affected by disease. This research produces accuracy in the first test 73% and the second test 92%.
Analisis Metode Trend Moment Sebagai Peramalan (Forecast) Penjualan UMKM Dimsum Tessya Fakhta Tri Nasution; Arif Ridho Lubis; Alkhowarizmi
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 2 No. 1 (2023): Januari 2023
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v2i1.39

Abstract

Sales is a business activity that is based on a strategy or plan that is useful to increase sales of the products produced. One of the strategies developed is to predict the number of products for Micro, Small and Medium Enterprises (MSMEs). The problem that often occurs in MSMEs is the supply of the number of products that have excess stock as experienced by MSMEs Dimsum Khanzaku. This resulted in many expired products and caused considerable losses. Therefore we need a calculation in predicting the amount of inventory so that there is no excess stock that can cause losses. As for one method of data mining in forecasting or predicting is Trend Moment. In this case, the Trend Moment Method is used to forecast sales of dimsum products in the coming month using previous sales data, to find out how many products should be supplied and sold for the following month. Sales data was taken from May 2019 to April 2021. The results obtained were sales that occurred in June 2021 for a 31 Kg company, thus presenting an inaccurate prediction of only 25%. The average yield on sales from May 2021 to February 2022 is 25%.
Optimization of principal component analysis and k-nearest neighbors in cultivation area classification red onion Arif Ridho Lubis; Purwa Hasan Putra; Fahdi Saidi Lubis
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 6: December 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i6.27103

Abstract

This research aims to increase the effectiveness in classifying shallot cultivation areas through the combined application of principal component analysis (PCA) and k-nearest neighbors (KNN) methods. Shallot is an important agricultural commodity, and identification of optimal areas for its cultivation is essential to support food self-sufficiency. Onion cultivation is generally done in the highlands. One of the areas with shallot cultivation in North Sumatra Province is Berastagi, Karo Regency. This research was conducted by determining the spatial extent of upland land. In the use of data there are 2 types of data that will be used: land suitability dataset and land condition dataset for each region. The PCA method is utilized to simplify the data structure by reducing the number of dimensions and removing insignificant attributes, while KNN was used to classify regions based on their suitability for shallot cultivation. This research produces a classification map that can be used to identify the most optimal areas for shallot cultivation. The test results with the regional spatial dataset using precision, recall and fi-score testing accuracy value 0.92%, and macro avg value 0.94%, weighted avg value 0.93%.
PKM DIGITALISASI SISTEM PRESENSI SISWA MELALUI APLIKASI DI MADRASAH ALIYAH SUNGGAL DESA TANJUNG GUSTA KEC SUNGGAL KAB DELI SERDANG SUMATERA UTARA Purwa Hasan Putra; Julham Julham; Arif Ridho Lubis; Virdyra Tasril; Mayang Mughnyanti; Desilia Selvida
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol. 5 No. 2 (2025): Desember 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i2.5385

Abstract

Abstract: The Community Service Activity of Digitalizing Student Attendance System through Application was carried out at Sunggal Islamic High School, Tanjung Gusta Village, Sunggal District, Deli Serdang Regency, North Sumatra as an effort to improve the efficiency and accuracy of student attendance recording which was previously still done manually. The web-based digital attendance system developed by the PKM team from Medan State Polytechnic allows teachers and administrative staff to record student attendance quickly, securely, and can be accessed in real-time. The recording process which previously took 7 minutes per class can be cut to 2 minutes per class. The implementation method of the activity includes observing school needs, designing and developing the application, training for teachers and staff, and mentoring during implementation. The results of the activity show that this system not only improves work efficiency but also helps improve the digital literacy of teachers and school staff. Keyword: Digitalization, Attendance, Students, MAS Aliyah Sunggal Abstrak: Kegiatan Pengabdian Kepada Masyarakat Digitalisasi Sistem Absensi Siswa Melalui Aplikasi dilaksanakan di SMA Islam Sunggal, Desa Tanjung Gusta, Kecamatan Sunggal, Kabupaten Deli Serdang, Sumatera Utara sebagai upaya untuk meningkatkan efisiensi dan akurasi pencatatan kehadiran siswa yang sebelumnya masih dilakukan secara manual. Sistem absensi digital berbasis web yang dikembangkan oleh tim PKM dari Politeknik Negeri Medan ini memungkinkan guru dan tenaga administrasi untuk mencatat kehadiran siswa secara cepat, aman, dan dapat diakses secara real-time. Proses pencatatan yang sebelumnya membutuhkan waktu 7 menit per kelas dapat dipangkas menjadi 2 menit per kelas. Metode pelaksanaan kegiatan meliputi observasi kebutuhan sekolah, perancangan dan pengembangan aplikasi, pelatihan bagi guru dan tenaga kependidikan, serta pendampingan selama pelaksanaan. Hasil kegiatan menunjukkan bahwa sistem ini tidak hanya meningkatkan efisiensi kerja tetapi juga membantu meningkatkan literasi digital guru dan tenaga kependidikan sekolah. Kata kunci: Digitalisasi, Absensi, Siswa, MAS Aliyah Sunggal 
Machine Learning-Based Predictive System for Cultural Heritage Site Condition Assessment Arif Ridho Lubis; Ali Basrah Pulungan
Management of Information System Journal Vol 4 No 3: Juli 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/mis.v4i3.2897

Abstract

Cultural heritage preservation in North Sumatra faces challenges from manual, decentralized, and reactive site condition reporting. This study designs and develops a web-based Cultural Heritage Information System (CHIS) integrated with a Machine Learning (ML) prediction module for the Disbudparekraf of North Sumatra Province. The system is built using the CodeIgniter 4 framework with Role-Based Access Control (RBAC), MariaDB database, GIS integration via Leaflet.js, and a prediction module employing Random Forest Regressor with features including health score, structural integrity, physical integrity, authenticity, age factor, and maintenance score. Development follows the Waterfall model encompassing requirements analysis, design, implementation, black-box testing (47 test cases), and deployment. Results demonstrate successful integration of 12 historical assessment records from 10 priority heritage sites, generating 8 predictions with an average confidence score of 45.9% and automatic identification of high-risk sites such as Masjid Raya Al Mashun (confidence 51%). The system produces structured maintenance recommendations across three priority categories with specific timelines. The moderate confidence score reflects initial dataset limitations and is expected to improve with accumulating assessment data. This research contributes a replicable GIS-ML integration model for heritage conservation at the Indonesian local government level.
Quantifying the Causal Impact of Employment Trends on Academic Performance Using Time-Series and Public Interest Data in Indonesia Alif Noorachmad Muttaqin; Muharman Lubis; Tomi Mulhartono; Arif Ridho Lubis
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i4.2358

Abstract

This study quantifies the causal impact of employment trends on academic performance using a hybrid model of survey data and time-series public interest data from Google Trends in Indonesia. Employing Granger causality and regression analysis, the research investigates eight determinants of GPA and their relationship to labor indicators. A purposive sample of 40 respondents and secondary data from 2011–2019 were analyzed. Granger tests reveal significant one-way causality from employment to GPA indicators, particularly in parental monitoring (F = 7.06; p < 0.05) and learning motivation (F = 9.68; p < 0.05). Regression analysis supports these findings with R² values above 0.50. Results highlight the potential of integrating behavioral data into educational analytics. This research contributes methodological innovation by incorporating public interest data to explain academic outcomes, with implications for predictive modeling in education policy and planning.
Co-Authors A, Azanuddin Achmad Yani Adam, Hikmah Adwin Adha, Lilis Tiara Al Khowarizmi Ali Basrah Pulungan Alif Noorachmad Muttaqin Alkhowarizmi Arif Hamied Nababan Ariyani, Tika Azhar, Muhammad Fauzan Bister Purba Dini Oktarina Dwi Handayani Donny Sanjaya Efori Bu&#039;ulolo Elviawaty Muisa Zamzami Fachry Ferdiansyah Sembiring Fahdi Saidi Lubis Fatmi, Yulia Fawwaz, Mohammad Faris Faza, Sharfina Ferry Fachrizal - Firjatullah, Muhammad Gabriel Ardi Hutagalung Gunawan Gunawan Habibi Ramdani Safitri Harefa, Hafid Rahman Haryadi - Hidayatullah, Rafly Artha Hikmah Adwin Adam Husna, Meryatul Ilham Ramadhan Nasution Imani, Muhammad Rayyan Indri Sulistianingsih Irvan, Irvan Julham Julham Julham Julham Kamil, Idham Lampson Pindahaman Purba Luckyhasnita, Andam M.Pd, Akrim Mahyuddin K. M Nasution Mardianto, Willy Mayang Mughnyanti Mhd Faris Pratama Mhd Ikhsan P Siregar Michael J Watts Mughnyanti, Mayang Muhammad Basri Muhammad Luthfi Hamzah Muhammad Rafif Rasyidi Muharman Lubis Nadi, Farhad Nst, Fifi Anggiani Br Nurhaflah Soraya Nurlinda Opim Salim Sitompul Prayudani, Santi Purba, Lampson Pindahaman Purnamawati, Sarah Putra, Purwa Hasan Raditiansyah, Farhan Rahmadani Rahmadani Rahmadani Rahmadani Rian Syahputra Rina Anugrahwaty Rinaldy, Muhammad Eri Riza Sulaiman Rizki Syahputra Romi Fadillah Rahmat Salam, Azrizal Sarah Purnamawati Selvida, Desilia Sembiring, Boni Oktaviani Sibarani, Yous Syafli, Sekar Arini Syamsul Arifin Tasril, Virdyra Tessya Fakhta Tri Nasution Tomi Mulhartono Virdyra Tasril Weno Syechu Yulia Fatmi Yulia Fatmi Yusuf, Kadri Yuyun Yusnida Lase