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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING BAREKENG: Jurnal Ilmu Matematika dan Terapan 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 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 Advance Sustainable Science, Engineering and Technology (ASSET)
Lubis, Arif Ridho
Politeknik Negeri Medan
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Veterinary

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Pelatihan Canva Untuk Guru-Guru Di SMA Swasta Amir Hamzah Medan Sumatera Utara Gunawan, Gunawan; Lubis, Arif Ridho; Kadri Yusuf; Achmad Yani
Jurnal Masyarakat Indonesia (Jumas) Vol. 3 No. 01 (2024): Jurnal Masyarakat Indonesia (Jumas)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jumas.v3i01.74

Abstract

In order to improve the quality of teaching and learning activities and the competence of teachers, teachers must make teaching materials with computer media such as presentation slides and learning videos. The solution offered is to provide training for teachers to be more competent in making interactive teaching materials using computer program media, namely Canva. The proposed Community Partnership Service target is Amir Hamzah Medan private high school located on Jl. Meranti no.1, Sekip Village, Medan Petisah District, Medan Municipality, North Sumatra Province. The output produced is publication on mass media and video on social media.
Human blood group type detection prototype focusing on agglutinin using microcontroller based photodiode Lubis, Arif Ridho; Harefa, Hafid Rahman; Al-Khowarizmi, Al-Khowarizmi; Julham, Julham; Lubis, Muharman; Rahmat, Romi Fadillah
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7007

Abstract

Blood is a fluid in the body that mainly serves as a medium for transporting various substances in the body. Detection of human blood group types with this microcontroller utilizes dark and light properties. The dark character appears due to agglomeration, while the light nature arises because of no agglomeration, for this to happen, a liquid reagent is needed. Administration of this liquid uses the aviator's breathing oxygen (ABO) system, which consists of reagent a, reagent b, and reagent c and mixing it with blood on the test paper. The number of blood samples in each reagent is based on blood lancet. Furthermore, the sensors used to detect these properties are photodiode and light emitting diode (LED) each of 3 pieces. The Arduino Uno is used to process sensor input while at the same time producing displayed human blood group type on the display screen. The test is carried out involving 12 blood samples and a medical officer. Medical officer are tasked reading directly the results of mixing between reagents and blood samples, after that are compared with the system. The results show that the deviation of the system reading is 0.167 for the sensor reading distance with the sample as far as 0.5 cm.
Braille letter recognition in deep convolutional neural network with horizontal and vertical projection Rahmat, Romi Fadillah; Purnamawati, Sarah; Mardianto, Willy; Faza, Sharfina; Sulaiman, Riza; Nadi, Farhad; Lubis, Arif Ridho
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7222

Abstract

Brail is a written mode of communication utilized by individuals with visual impairments to engage in interpersonal exchanges. The braille writing system consists of patterns printed on specialized paper that feature embossed dots. Braille documents enable the visually impaired to acquire knowledge and information exclusively through the application of their sense of contact. Comprehending braille is not a simple undertaking, particularly for the general populace. Because braille is not a required subject in Indonesian education, the majority of the population lacks proficiency in the language. This may therefore result in a minor communication barrier between visually impaired individuals and non-impaired individuals. In order to address this challenge, the present study employs digital image processing via the deep convolutional neural network (DCNN) technique to facilitate comprehension of braille document contents by non-braille speakers. This study employs a deep learning technique that is highly accurate, effective at image processing, and capable of recognizing complex patterns. This study employed the following image processing methods: grayscaling, filtering, contrast enhancement, thresholding, morphological operation, and resizing. Following testing in this investigation, it was determined that the proposed method accurately identifies embossed braille images with a precision of 99.63%.
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%.
Predictive Analytics for IMDb Top TV Ratings: A Linear Regression Approach to the Data of Top 250 IMDb TV Shows Husna, Meryatul; Purba, Lampson Pindahaman; Rinaldy, Muhammad Eri; Lubis, Arif Ridho
Journal of Applied Informatics and Computing Vol. 8 No. 1 (2024): July 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i1.7600

Abstract

In the era of a growing entertainment industry, understanding audience preferences and predicting the financial performance of entertainment products such as films and television shows has become increasingly important. Previous research has demonstrated various approaches in understanding the factors that influence the financial performance of entertainment products. However, there is still a need for research to investigate other aspects of film and television show evaluation. This study aims to explore the contribution of linear regression in analysing the ratings and financial performance of IMDb's top TV shows. Through the incorporation of various data-informed and interpretative approaches, it is expected to gain a deeper understanding of the factors that influence the success of a television show. Using data from the Top 250 IMDb TV Shows, a predictive analysis was conducted to understand the relationship between the number of episodes and IMDb ratings. The results of the information showed a negative relationship between the number of episodes and IMDb rating, with the linear regression model predicting a decrease in IMDb rating as the number of episodes increases. Implications of this research include recommendations for content creators to consider both quality and quantity of content in the development of TV shows.
IMPLEMENTASI SISTEM PREDIKSI GAYA BELAJAR MAHASISWA MENGGUNAKAN NAÏVE BAYES BERBASIS WEB Lase, Yuyun Yusnida; Syafli, Sekar Arini; Fatmi, Yulia; Prayudani, Santi; Lubis, Arif Ridho; Haryadi, Haryadi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2327

Abstract

Aplikasi ini dibuat untuk memprediksi  gaya belajar mahasiswa, menggunakan algoritma naïve bayes, dibandingkan dengan algoritmanya naïve bayes sangat baik dalam  proses klasifikasi, untuk melakukan prediksi dimasa depan algoritma ini menggunakan probabilitas dan statistik. Data yang digunakan berupa data demografis mahasiswa seperti semester/tingkat studi, data gaya belajar seperti visual, kinestetik, auditori, dan data preferensi belajar seperti preferensi belajar visual, preferensi belajar auditori, dan preferensi belajar kinestetik. Metode pembelajaran yang diamati untuk menentukan gaya belajar metode synchoronous.  Sampel data yang digunakan adalah mahasiswa program studi teknologi rekayasa perangkat lunak. Bahasa yang digunakan dalam membuat aplikasi ini menggunakan  PHP dan database MySQL. Aplikasi ini nantinya dapat membantu tenaga pendidik dapat menyusun strategi pembelajaran yang sesuai dengan gaya belajar mahasiswa sehingga proses pembelajaran dapat berjalan dengan efektif dan efesien.
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 | Full PDF (1892.394 KB) | DOI: 10.53806/jmscowa.v2i2.58

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.
Modification of Multilayer Perceptron Using Detection Rate Model for Prediction of Nominal Exchange Rate Al-Khowarizmi Al-Khowarizmi; Romi Fadillah Rahmat; Michael J Watts; Akrim Akrim; Arif Ridho Lubis; Muhammad Basri
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (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.v6i2.6117

Abstract

An artificial neural network (ANN) is a network of a group of units to be processed which is modeled based on the behavior of human neural networks. ANN has one of its tasks, namely prediction. Multilayer perceptron (MLP) is one of the ANN methods that can be prediction all of data. Where the prediction needs to be reviewed because the prediction process does not always run normally. So, it takes a good measurement accuracy in order to get an accuracy sensitivity. The accuracy technique in this paper is carried out using Mean Absolute Percentage Error (MAPE) based on absolute error and detection rate. The results obtained with absolute error achieve an accuracy of 99.73% while the accuracy based on the detection rate achieves an accuracy of 99.49%. this can be seen in the case of the prediction of (Indonesian Rupiah) IDR exchange rate against United State Dollar (USD) with the MLP algorithm by testing using MAPE to achieve sensitivity with absolute error.
Pelatihan Perhitungan Harga Pokok pada Pengusaha Anggur di Desa Bangun Sari Kecamatan Tanjung Morawa Kabupatem Deli Serdang Sumatera Utara Rini Indahwati; Rahmadani, Rahmadani; Nurhaflah Soraya; Arif Ridho Lubis; Nurlinda
JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Vol. 6 No. 2 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v6i2.2347

Abstract

Program pengabdian masyarakat melalui Independent Thematic Community Service Collaboration (I-TCSC) ini bertujuan untuk menyelesaikan masalah mitra terkait peningkatkan kemampuan Mitra dalam melakukan perhitungan harga pokok produksi sehingga memudahkan bagi mitra dalam menyelesaikan permasalahan akuntansinya terutama terkait perhitungan harga pokok. Pengabdian Masyarakat ini penting bagi mitra untuk meningkatkan lagi usaha dan pada akhirnya akan mampu meningkatkan penghasilan melalui perhitungan harga pokok yang terstandar. Luaran yang ditargetkan adalah peningkatkan kemampuan mitra sehingga mitra menjadi lebih mandiri dan mampu meningkatkan pengelolaan keuangan terutama dalam menetapkan harga pokok produksi yang sesuai dengan standar serta meningkatkan kesejahteraan petani anggur. Target yang ingin dicapai adalah Mitra mampu menghitung harga pokok produksi dan pengelolaan keuangan.
Perbandingan Kinerja Model Pembelajaran Mesin Random Forest dan K-Nearest Neighbor (KNN) untuk Prediksi Risiko Kredit pada Layanan Pinjaman Online Prayudani, Santi; Sibarani, Yous; Salam, Azrizal; Lubis, Arif Ridho
Journal Software, Hardware and Information Technology Vol 5 No 2 (2025)
Publisher : Jurusan Sistem Informasi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/shift.v5i2.204

Abstract

This study aims to compare the performance of two popular machine learning algorithms, Random Forest and K-Nearest Neighbor (KNN), in predicting creditworthiness in online lending systems. The research uses the publicly available Loan Approval Prediction Dataset from Kaggle, which contains borrower profiles such as employment status, number of dependents, annual income, loan amount, loan term, and credit score. Data preprocessing included cleaning, handling missing values, outlier removal, and transformation through normalization and encoding. The dataset was divided into 80% training data and 20% testing data. Random Forest was configured with 100 decision trees and unlimited depth, while KNN used an optimal k value of 5 determined by grid search. Model performance was evaluated using accuracy, precision, recall, and F1-score. The results showed that Random Forest outperformed KNN with consistently higher values (97%) across all metrics, demonstrating strong stability and superior pattern recognition capabilities. KNN, with an accuracy of 89%, still showed good performance and can be considered a lightweight alternative for simpler applications.
Co-Authors A, Azanuddin Achmad Yani Adam, Hikmah Adwin Adha, Lilis Tiara Al Khowarizmi Ardi Hutagalung, Gabriel Ariyani, Tika Azhar, Muhammad Fauzan Dewi Wulandari Dini Oktarina Dwi Handayani Elviawaty Muisa Zamzami Fatmi, Yulia Fawwaz, Mohammad Faris Faza, Sharfina Firjatullah, Muhammad Gabriel Ardi Hutagalung Gunawan Gunawan Habibi Ramdani Safitri Harefa, Hafid Rahman Haryadi - Hidayatullah, Rafly Artha Hikmah Adwin Adam Hikmah Adwin Adam Husna, Meryatul Ilham Ramadhan Nasution Imani, Muhammad Rayyan Irvan, Irvan Julham Julham Julham Julham Kamil, Idham Lampson Pindahaman Purba Lase, Yuyun Lubis, Fahdi Saidi Luckyhasnita, Andam M.Pd, Akrim Mahyuddin K. M Nasution Mardianto, Willy Mhd Faris Pratama Michael J Watts Mughnyanti, Mayang Muhammad Basri Muhammad Luthfi Hamzah Muhammad Rafif Rasyidi Muharman Lubis Mulhartono, Tomi Muttaqin, Alif Noorachmad 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 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 Yulia Fatmi Yulia Fatmi Yusuf, Kadri Yuyun Yusnida Lase