Article Per Year (5 Year)
p-Index From 2021 - 2026
5.273
P-Index
This Author published in this journals
All Journal CESS (Journal of Computer Engineering, System and Science) Jurnal ULTIMATICS Jurnal Sistem Komputer dan Informatika (JSON) Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Penelitian, Pendidikan dan Pengajaran: JPPP Djtechno: Jurnal Teknologi Informasi Ar-Rasyid: Jurnal Pendidikan Agama Islam Educenter: Jurnal Ilmiah Pendidikan sudo Jurnal Teknik Informatika Hello World Journal of General Education and Humanities Blend Sains Jurnal Teknik Factory Jurnal Industri, Manajemen dan Rekayasa Sistem Industri Jurnal Ilmu Komputer dan Sistem Informasi Hanif Journal of Information Systems Polyscopia EDUCENTER JURNAL PENDIDIKAN Tsabit Jurnal Informatika Dan Tekonologi Komputer
Mhd. Basri
Universitas Muhammadiyah Sumatera Utara
Religion 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 Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

Published : 41 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 41 Documents
Search

 1   2   3   4   5 
Implementasi Internet of Things Berbasis Website dalam Pemesanan Jasa Rumah Service Teknisi Komputer dan Jaringan Komputer Sari, Indah Purnama; Batubara, Ismail Hanif; Basri, Mhd.; Hazidar, Al Hamidy
Blend Sains Jurnal Teknik Vol. 1 No. 2 (2022): Edisi Oktober
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (304.809 KB) | DOI: 10.56211/blendsains.v1i2.136

Abstract

Pada website pemesanan jasa rumah teknisi atau di sebut dengan service computer dan jaringan computer atau di kenal internet merupakan website yang di rancangkan untuk menerima booking service untuk toko rumah teknisi computer dan jaringan internet. Pada kali ini website yang di rancangkan agar bisa mencatat riwayat servis dari PC Desktop, Laptop dan pada masalah jaringan computer. Aplikasi ini dibuat menggunakan bahasa pemrogramman Web, PHP dan HTML yang digunakan adalah MySQL dan xampp. Aplikasi ini memiliki 2 aktor yaitu Pelanggan, dan Teknisi. Hasil dari penelitian ini memberikan sistem pemesanan jasa rumahteknisi komputer berbasis web yang mudah, cepat dan akurat serta dapat diakses melalui berbagai gadget yang tersambung jaringan internet.
Pembelajaran Pemrograman berbasis Machine Learning sebagai Upaya Peningkatan Computational Thinking Sari, Indah Purnama; Zulherry, Andi; Basri, Mhd.; Hayani, Wirda
Jurnal Penelitian, Pendidikan dan Pengajaran: JPPP Vol 6, No 3 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jppp.v6i3.28679

Abstract

Kemampuan computational thinking merupakan kompetensi esensial yang harus dimiliki oleh peserta didik dalam menghadapi perkembangan teknologi digital dan kecerdasan buatan. Namun, pembelajaran pemrograman konvensional masih berfokus pada sintaks dan prosedur, sehingga belum optimal dalam mengembangkan kemampuan berpikir komputasional secara menyeluruh. Penelitian ini bertujuan untuk menganalisis efektivitas pembelajaran pemrograman berbasis machine learning dalam meningkatkan kemampuan computational thinking. Metode penelitian yang digunakan adalah kuasi-eksperimen dengan desain pretest–posttest control group. Subjek penelitian terdiri atas mahasiswa program studi pendidikan komputer yang dibagi ke dalam kelas eksperimen dan kelas kontrol. Kelas eksperimen menerapkan pembelajaran pemrograman dengan pendekatan machine learning melalui pengenalan konsep data, pelatihan model, serta evaluasi hasil prediksi, sedangkan kelas kontrol menggunakan pembelajaran pemrograman konvensional. Instrumen penelitian berupa tes computational thinking yang mencakup aspek dekomposisi, pengenalan pola, abstraksi, dan perancangan algoritma. Hasil penelitian menunjukkan adanya peningkatan signifikan kemampuan computational thinking pada kelas eksperimen dibandingkan kelas kontrol. Temuan ini mengindikasikan bahwa integrasi machine learning dalam pembelajaran pemrograman mampu mendorong mahasiswa untuk berpikir analitis, logis, dan sistematis. Dengan demikian, pembelajaran pemrograman berbasis machine learning berpotensi menjadi strategi inovatif dalam pendidikan komputer untuk meningkatkan kualitas pembelajaran dan kesiapan peserta didik menghadapi era kecerdasan buatan.
Comparative Analysis of the Performance of VGG16 and ResNet50 Architectures in Multi-Class Classification of Rice Plant Diseases Based on Convolutional Neural Networks (CNN) Aditya, Krisna; Basri, Mhd.
Tsabit Journal of Computer Science Vol. 2 No. 2 (2025): December Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/tsabit55

Abstract

Rice plant diseases significantly affect crop productivity and food security, making early and accurate disease detection essential for effective agricultural management. Recent advances in deep learning, particularly Convolutional Neural Networks (CNN), have demonstrated strong potential in image-based plant disease classification. This study presents a comparative analysis of the performance of VGG16 and ResNet50 architectures for multi-class classification of rice plant diseases using CNN-based approaches. A dataset of rice leaf images representing multiple disease classes and healthy conditions was collected and preprocessed through image resizing, normalization, and data augmentation to enhance model generalization. Both pre-trained models were fine-tuned using transfer learning to adapt them to the rice disease classification task. Model performance was evaluated using standard metrics, including accuracy, precision, recall, F1-score, and confusion matrix analysis. The experimental results show that both architectures achieve high classification performance; however, ResNet50 demonstrates superior accuracy and better generalization capability compared to VGG16, particularly in handling complex disease patterns and intra-class variations. Meanwhile, VGG16 offers a simpler architecture with faster convergence and lower computational complexity. The findings of this study provide insights into the selection of appropriate CNN architectures for rice plant disease classification and support the development of intelligent decision support systems in precision agriculture.
Development of a Decision Support System to Determine Best-Selling Menu Canteen Employees of the Bank Indonesia Representative Office in North Sumatra Province using the Topsis Method Adhari, M. Rizki; Basri, Mhd.
Tsabit Journal of Computer Science Vol. 2 No. 2 (2025): December Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/tsabit60

Abstract

The availability of accurate sales information is essential for supporting managerial decision-making in institutional food services. At the Bank Indonesia Representative Office in North Sumatra Province, determining the best-selling menu for employee canteen services is still largely based on manual evaluation, which may lead to inefficiencies and subjective judgments. This study aims to develop a Decision Support System (DSS) to identify the best-selling canteen menu using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The system evaluates menu alternatives based on multiple criteria, including sales volume, price, menu availability, and employee preferences. Data were collected from historical sales records and questionnaires distributed to canteen employees. The TOPSIS method was applied to rank menu alternatives by calculating their relative closeness to the ideal positive and ideal negative solutions. The DSS was implemented as a computerized system to facilitate data processing, ranking, and visualization of decision results. The results show that the proposed system is able to objectively determine the best-selling menu and provide consistent rankings compared to conventional methods. The developed DSS improves accuracy, efficiency, and transparency in menu evaluation, thereby supporting better planning and inventory management for the employee canteen. This study demonstrates that integrating multi-criteria decision-making methods into a DSS can effectively enhance decision quality in institutional food service management.
Perancangan Aplikasi Monitoring Kehadiran Pegawai Menggunakan RFID Zulherry, Andi; Sari, Indah Purnama; Basri, Mhd.
sudo Jurnal Teknik Informatika Vol. 4 No. 4 (2025): Edisi Desember
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/sudo.v4i4.1571

Abstract

Kehadiran pegawai merupakan aspek penting dalam manajemen sumber daya manusia yang berpengaruh terhadap produktivitas dan kinerja organisasi. Sistem pencatatan kehadiran manual yang masih digunakan pada banyak instansi memiliki kelemahan seperti rentan terhadap manipulasi data, membutuhkan waktu lama dalam pengolahan, dan tingkat akurasi yang rendah. Penelitian ini bertujuan merancang aplikasi monitoring kehadiran pegawai berbasis teknologi Radio Frequency Identification (RFID) yang dapat meningkatkan efisiensi dan akurasi pencatatan kehadiran. Metode pengembangan sistem menggunakan pendekatan waterfall yang meliputi tahap analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Sistem yang dirancang terdiri dari perangkat keras berupa RFID reader, kartu RFID sebagai identitas pegawai, dan perangkat lunak berbasis web untuk monitoring dan pelaporan. Hasil perancangan menunjukkan bahwa sistem dapat melakukan pencatatan kehadiran secara otomatis, real-time, dan akurat. Data kehadiran tersimpan dalam database yang dapat diakses oleh administrator untuk keperluan monitoring dan pembuatan laporan. Sistem ini diharapkan dapat membantu manajemen dalam pengambilan keputusan terkait kehadiran pegawai dan meningkatkan kedisiplinan pegawai melalui sistem monitoring yang lebih efektif dan transparan.
Analysis of Determining Public Speaking Skill Levels of Junior High School Students Using the TOPSIS Method at Phatnawitya School, Yala, Thailand Wirawan, Zaky Soleh; Basri, Mhd.
Journal of General Education and Humanities Vol. 5 No. 2 (2026): April
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/gehu.v5i2.1098

Abstract

Evaluating junior high school students' public speaking skills often faces the challenge of subjectivity, especially in international schools where manual assessment lacks mathematical rigor. This study applied the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with manual calculations to objectively rank 28 students from Phatnawitya School, Yala, Thailand, based on seven Canva presentation criteria: Eye Contact, Body Language, Poise, Subject Knowledge, Fluency, Pronunciation, and Comprehension. Using a descriptive quantitative approach, purposive sampling targeted one top-tier class as the sample population. Teachers' Excel assessment data were analyzed using TOPSIS through decision matrix formation, normalization, weighted normalization, ideal solution determination, distance calculation, and preference assessment. The results showed that Salsabil Hayitahe ranked first (V=0.65) and Muhammadsharif Seng last (V=0.36), proving the effectiveness of TOPSIS in providing transparent, bias-free ranking. The conclusions confirm the suitability of manual TOPSIS for multi-criteria educational evaluation, without software dependence, and recommend its wider application across various classes.
Analisis Penilaian Kinerja Siswa untuk Menentukan Siswa Terbaik di Sekolah Melalui Metode Naive Bayes di Songsermsasana School, Hat Yai Dina Salsabila; Mhd. Basri
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 6 No. 1 (2026): Maret : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v6i1.10620

Abstract

Conventional student performance evaluation at Songsermsasana School, Hat Yai, Thailand, relies on subjective academic scores, lacking systematic integration of multidimensional indicators. This study aims to analyze Naive Bayes classifier application for objective outstanding student determination using secondary performance data. Employing quantitative non-experimental design, the research utilized 100 purposively selected student records covering academic grades (0-100), attendance (0-100%), attitude (1-3 scale), extracurricular participation (0-1), and achievements (0-1). Data preprocessing involved numerical encoding followed by Naive Bayes probabilistic classification based on Bayes' Theorem, evaluated through confusion matrix metrics. Results demonstrate 90% accuracy and 100% recall, successfully identifying all outstanding students without false negatives despite three false positives. The model confirms Naive Bayes effectiveness for transparent, data-driven decision-making in educational assessment. Findings support implementation as school decision support systems while recommending hybrid algorithms for future enhancements.
Perbandingan Algoritma MOORA dan Profile Matching pada Sistem Pemilihan Pupuk untuk Tanaman Porang Farid Akbar Siregar; Fatma Sari Hutagalung; Mhd Basri
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 1 (2023): September 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6772

Abstract

Porang plants have long been utilized as a source of carbohydrates, fats, proteins, minerals, vitamins, and dietary fiber, which are exported as raw materials for various industries. In recent years, porang plants have become a highly profitable export commodity. One of the critical factors influencing porang plant production is fertilization. The timely, precise dosage, and correct method of fertilization determine the effectiveness of the fertilizer applied. MOORA considers various criteria in a balanced manner. Its ability to optimize the ratios between these criteria enables a more comprehensive selection of fertilizers. Profile Matching can be effective when specific criteria need to be emphasized over others. However, this method may not yield optimal decisions when several criteria carry significant weight. This research aims to determine the best type of fertilizer by applying a Decision Support System (DSS) and provides the benefit of assisting farmers in determining the most suitable fertilizer types for each phase of porang growth.In this study, a comparison was made between the MOORA and Profile Matching algorithms in the context of fertilizer selection for porang plants, using 7 fertilizer alternatives and 6 criteria types. Based on the research results, it can be concluded that both algorithms produce relatively similar outcomes, but the Profile Matching algorithm has a faster processing time compared to the MOORA algorithm in determining results. The contributions of this research include the development of a fertilizer selection system to help farmers optimize the growth and harvest of their crops. It also contributes to scientific literature and the comparison of algorithms, which can assist scientists and practitioners in selecting the most appropriate algorithms for similar problems in the future.
Teacher discipline assessment with Mamdani Fuzzy Logic decision support system on attendance data at Phatnawitya School Yala Muhammad Zulfahmi Khairullah; Mhd. Basri
Educenter : Jurnal Ilmiah Pendidikan Vol. 5 No. 1 (2026): Educenter: Jurnal Ilmiah Pendidikan (In press)
Publisher : ARKA INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/educenter.v5i1.1850

Abstract

Teacher discipline is a crucial factor in maintaining the quality of the learning process in schools; however, discipline assessment is often conducted subjectively and relies on rigid threshold values. This study aims to develop a decision support system based on Mamdani Fuzzy Logic to evaluate teacher discipline using attendance data. The research method includes fuzzification, Mamdani fuzzy inference, and defuzzification using the centroid method, with two input variables attendance and absence without permission (alpha) and one output variable in the form of a discipline score. The results indicate that teachers with attendance ≥90% and alpha ≤3 days are classified as “Very Good”, those with attendance between 80-89% fall into the “Good” to “Fair” categories, while attendance below 75% or alpha above 12 days is categorized as “Poor”. The fuzzy system produces consistent, stable, and flexible assessments through gradual value transitions. In conclusion, Mamdani Fuzzy Logic is effective as a more objective and realistic tool for evaluating teacher discipline compared to conventional threshold-based methods.
Decision analysis on the use of figma to improve learning effectiveness at Saengsattha School Thailand using the AHP Method Defri Aldi; Mhd. Basri; Lutfi Basit
Educenter : Jurnal Ilmiah Pendidikan Vol. 5 No. 1 (2026): Educenter: Jurnal Ilmiah Pendidikan (In press)
Publisher : ARKA INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/educenter.v5i1.2058

Abstract

The development of digital media-based learning requires the selection of platforms that are not only easy to use, but also capable of supporting interactivity, collaboration, and providing a real impact on learning outcomes. However, the selection of digital learning media in schools is often not based on systematic and measurable decision analysis. This condition creates a need for objective evaluation of the effectiveness of digital media used in the learning process. This study aims to analyze the effectiveness of using Figma as a digital learning medium at Saengsattha School in Thailand. This study uses a descriptive quantitative approach with data collection through a five-point Likert scale questionnaire involving 100 respondents, consisting of 10 teachers and 90 students. Data analysis was performed using the Analytical Hierarchy Process (AHP) method to determine the weight of importance of four main criteria, namely ease of use, interactivity, collaboration, and impact on learning outcomes and user satisfaction. The results showed that Figma obtained a final score of 4.06 and was categorized as effective, with the criteria of impact and user satisfaction as the most dominant factors. These findings indicate that Figma is suitable for use as a digital learning medium and that AHP can be a systematic method to support decision-making in selecting digital learning media in schools.
Co-Authors Abdul Fadlil Adhari, M. Rizki Aditya, Krisna Al Hamidy Al Khowarizmi Andi Zulherry Andi Zulherry Andi Zulherry Andy Satria Anis Badriah Anton Yudhana Baehaqi Barelvi, Ahmad Defri Aldi Dicky Apdilah Dina Salsabila Edy Rahman Syahputra Fadhlurrohman, Dimas Farid Akbar Siregar Fatma Sari Hutagalung G. Gunawan Halim Maulana Hasibuan, Wilda Rina Hayani, Wirda Hazidar, Al Hamidy Indah Purnama Sari Indah Purnama Sari Ismail Hanif Batubara Lutfi Basit Mahardika Abdi Prawira Manurung, Asrar Aspia Muhammad Zulfahmi Khairullah Nasution, Rahmad Kurniawan Nurul Hakiki Lubis Ok Muhammad Rehansyah Putra Panjaitan, Farhan Fadillah rahayu, Intan dwi Ramadhani, Fanny Raushan Dhamir Rosaldi Alfarizi RR. Ella Evrita Hestiandari Salsabila Humairoh Sihombing, Maissy Masitoh Syafrayani, Putri Rizki Syahri, Alfi Wirawan, Zaky Soleh Zaky, Naufal Zein, Liza Azzahra