Abstract:Abstarct: Increased computer users in high school make increasingly also the desire of students / i equal to know the type of computer components. With the many interests of students to know installation of computers, making…
making their enthusiasm higher in knowing the types of computer applications. Many factors influence for students on computer assembly, such as how component form, type of operating system, and how to install.
Keywords: Computer Components, Operating System
Abstak: Peningkatan pengguna komputer di sekolah SMA membuat makin meningkat pula keinginan siswa/i sederajat untuk mengetahui jenis komponen komputer. Dengan banyaknya minat siswa/i untuk mengetahui instalasi komputer, membuat antusias mereka semakin tinggi dalam mengetahui jenis aplikasi komputer. Banyak faktor yang mempengaruhi bagi siswa/i pada instalasi komputer, seperti bagaimana bentuk komponen, jenis sistem operasi, dan bagaimana cara instalasinya.
Kata Kunci : Komponen Komputer, Sistem Operasi,
Abstract:Abstract: The community of society is one of main activities required by a lecture as part of the tri dharma which aimed to apply and implement the scientific competence a lecturer to contribute positively especially for…
society needs. Vocational High School is a vocational school that is required to be ready to enter the world of work, therefore the SMK graduates are required to have the skills and knowledge that will be used in the workplace. Students of vocation especially in the majors of Software Engineering must have skills in computer science, such as programming skills. In the 2013 curriculum used by SMKN1 Air Joman, there are already programming subjects, but still local content and yet the discovery of mobile programming. Though mobile programming is currently one of the most popular programming, especially Android. This is not separated from the rapid development of the Android operating system, so people are competing to make the application. The advantages of android is its opensource and easy to develop, supported by a lot of android users including SMK students, so students can build and develop an android application and implement it on their respective devices so that it can be used as needed and not close possibly to be commercialized.
Keywords:programming, mobile programming, android
Abstrak: Pengabdian kepada masyarakat merupakan salah satu kegiatan wajib yang harus dilaksanakan oleh seorang dosen sebagai bagian dari tri dharma perguruan tinggi yang bertujuan untuk menerapkan dan mengimplementasikan kompetensi keilmuan yang dimiliki guna memberikan kontribusi positif bagi kebutuhan masyarakat. Sekolah Menengah Kejuruan (SMK) merupakan sekolah kejuruan yang dituntut untuk siap masuk ke dunia kerja, maka dari itu lulusan SMK diharuskan mempunyai Skill dan pengetahuan yang akan dipergunakan dalam dunia kerja. Siswa SMK terutama pada jurusan Rekayasa Perangkat Lunak harus memiliki keterampilan dalam ilmu komputer, seperti keterampilan programming. Pada kurikulum 2013 yang digunakan oleh SMKN1 Air Joman, sudah ada mata pelajaran programming, tapi masihbersifat muatan lokal dan belum ditemukannya pemrograman mobile. Padahal pemrograman mobile saat ini menjadi salah satu pemrograman yang paling diminati, khusunya Android. Hal ini tidak lepas dari pesatnya perkembangan sistem operasi Android tersebut, sehingga orang berlomba – lomba untuk membuat aplikasinya. Kelebihan dari android adalah sifatnya yang opensource dan mudah dikembangkan, didukung dengan pengguna android yang sangat banyak termasuk siswa-siswa SMK, dengan demikian para siswa bisa membangun dan mengembangkan sebuah aplikasi android dan mengimplementasikannya pada perangkat masing-masing sehingga bisa digunakan sesuai kebutuhan dan tidak menutup kemungkinan untuk bisa dikomersilkan.
Kata kunci:pemrograman, pemrograman mobile, android
Abstract:Abstract: Choosing the right elementary school is a crucial milestone for a child's future. However, the large number of school options in Asahan Regency with diverse criteria such as accreditation, facilities, fees, curriculum,…
riculum, and accessibility often makes it difficult for parents. Decision-making tends to be based on subjective word-of-mouth recommendations, which risks triggering bias. This research aims to develop an adaptive and objective web-based elementary school selection Decision Support System (DSS) framework to minimize such bias. The system is designed using a hybrid model that combines the Simple Multi-Attribute Rating Technique (SMART) method as a dynamic criteria weighting engine based on parents' preferences, and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank ten alternative schools. System testing was conducted through black-box testing functionality and empirical accuracy testing using Spearman Rank Correlation involving 40 respondents. The black-box testing results confirmed that all main system operations ran perfectly with a 100% success rate. Validity testing demonstrated very high accuracy, with a Spearman correlation coefficient of 0.89, demonstrating significant alignment between the system's recommendations and actual choices on the ground. Thus, the SMART-TOPSIS framework has proven reliable as a data-driven approach to helping parents choose the best elementary school.
Keywords: decision support system; elementary school; SMART; TOPSIS
Abstrak: Memilih sekolah dasar yang tepat merupakan tonggak awal krusial bagi masa depan anak. Namun, banyaknya pilihan sekolah di Kabupaten Asahan dengan keberagaman kriteria seperti akreditasi, fasilitas, biaya, kurikulum, dan aksesibilitas sering kali menyulitkan orang tua. Pengambilan keputusan pun cenderung didasarkan pada rekomendasi subjektif dari mulut ke mulut, yang berisiko memicu bias. Penelitian ini bertujuan mengembangkan kerangka kerja Sistem Pendukung Keputusan (SPK) pemilihan sekolah dasar berbasis web yang adaptif dan objektif guna meminimalkan bias tersebut. Sistem dirancang menggunakan model hibrida yang mengombinasikan metode *Simple Multi-Attribute Rating Technique* (SMART) sebagai mesin pembobotan kriteria dinamis sesuai preferensi orang tua, serta metode *Technique for Order of Preference by Similarity to Ideal Solution* (TOPSIS) untuk memeringkat sepuluh sekolah alternatif. Pengujian sistem dilakukan melalui uji fungsionalitas *black-box testing* dan uji akurasi empiris menggunakan Korelasi Peringkat Spearman dengan melibatkan 40 responden. Hasil *black-box testing* mengonfirmasi seluruh operasi utama sistem berjalan sempurna dengan tingkat keberhasilan 100%. Uji validitas menunjukkan akurasi sangat tinggi dengan koefisien korelasi Spearman sebesar 0,89, membuktikan keselarasan signifikan antara rekomendasi sistem dan pilihan nyata di lapangan. Dengan demikian, kerangka SMART-TOPSIS ini terbukti andal sebagai pendekatan berbasis data untuk membantu orang tua memilih sekolah dasar terbaik.
Kata kunci: sekolah dasar; sistem pendukung keputusan; SMART; TOPSIS
Abstract:Abstract: The development of Artificial Intelligence (AI) in education provides significant opportunities for supporting the development of English teaching materials in elementary schools. However, the wide variety of available…
vailable AI tools makes it difficult for teachers to select the most appropriate tools for their instructional needs. This study aims to analyze and generate recommendations for AI utilization using a Decision Support System (DSS) based on the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. The AHP method is used to determine the weight of criteria based on their importance, while the SAW method is applied to rank alternative AI tools. This study involves teachers at SDN 15 Padang Genting in identifying criteria and evaluating alternatives. The results show that the proposed DSS model is capable of generating appropriate AI tool recommendations based on predefined criteria. This approach contributes to more objective and systematic decision-making in utilizing AI for developing English teaching materials in elementary education.
Keywords: analytical hierarchy proces; artificial intelligence; decision support system; simple additive weighting; teaching materials
Abstrak: Perkembangan Artificial Intelligence (AI) dalam pendidikan memberikan peluang dalam penyusunan bahan ajar Bahasa Inggris di sekolah dasar. Namun, banyaknya pilihan tools AI menyebabkan guru mengalami kesulitan dalam menentukan tools yang paling sesuai dengan kebutuhan pembelajaran. Penelitian ini bertujuan untuk menganalisis dan menghasilkan rekomendasi pemanfaatan AI menggunakan Sistem Pendukung Keputusan (SPK) berbasis metode Analytical Hierarchy Process (AHP) dan Simple Additive Weighting (SAW). Metode AHP digunakan untuk menentukan bobot kriteria berdasarkan tingkat kepentingannya, sedangkan metode SAW digunakan untuk melakukan perangkingan alternatif tools AI. Penelitian ini melibatkan guru di SDN 15 Padang Genting dalam proses identifikasi kriteria dan penilaian alternatif. Hasil penelitian menunjukkan bahwa model SPK mampu menghasilkan rekomendasi tools AI yang sesuai dengan kebutuhan pengguna berdasarkan kriteria yang telah ditentukan. Pendekatan ini memberikan kontribusi dalam mendukung pengambilan keputusan yang lebih objektif dan sistematis dalam pemanfaatan AI untuk penyusunan bahan ajar Bahasa Inggris di sekolah dasar.
Kata kunci: analisis proses hierarki; bahan ajar; kecerdasan buatan; sistem pendukung keputusan; simple additive weighting.
Abstract:Abstract: Job training is one of the government’s efforts to improve the quality of human resources so that they possess competencies that meet labor market demands. The process of selecting training participants at the…
e Department of Manpower of Asahan Regency is still carried out manually, which can lead to subjectivity and inefficiency in determining the most eligible candidates. This study aims to develop a decision support system using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to assist the selection process objectively and systematically. The study applies four evaluation criteria, namely education level, age, work experience, and interview, with a dataset consisting of 31 training candidates. The system is developed as a web-based application using PHP programming language and MySQL database. The TOPSIS method is applied through decision matrix normalization, weighting, determination of positive and negative ideal solutions, and preference value calculation to produce a ranking of candidates. The results show that the proposed system can provide objective recommendations for selecting training participants, improve the efficiency of the selection process, and support decision makers in producing more accurate and reliable decisions.
Keywords: decision support system; selection; training; TOPSIS.
Abstrak: Pelatihan tenaga kerja merupakan salah satu upaya pemerintah dalam meningkatkan kualitas sumber daya manusia agar memiliki kompetensi yang sesuai dengan kebutuhan dunia kerja. Proses pemilihan calon peserta pelatihan di Dinas Tenaga Kerja Kabupaten Asahan selama ini masih dilakukan secara manual sehingga berpotensi menimbulkan subjektivitas dan kurang efektif dalam menentukan peserta yang paling layak. Penelitian ini bertujuan untuk membangun sistem pendukung keputusan menggunakan metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) untuk membantu proses seleksi peserta pelatihan secara objektif dan sistematis. Penelitian ini menggunakan empat kriteria penilaian yaitu pendidikan, usia, pengalaman kerja, dan wawancara dengan jumlah data sebanyak 31 calon peserta pelatihan. Sistem dikembangkan berbasis web menggunakan bahasa pemrograman PHP dan database MySQL. Metode TOPSIS digunakan untuk melakukan normalisasi matriks keputusan, pembobotan, penentuan solusi ideal positif dan negatif, serta perhitungan nilai preferensi untuk menghasilkan perankingan peserta pelatihan. Hasil penelitian menunjukkan bahwa sistem yang dibangun mampu memberikan rekomendasi peserta pelatihan secara objektif, meningkatkan efisiensi proses seleksi, serta membantu pihak dinas dalam pengambilan keputusan yang lebih akurat.
Kata kunci: pelatihan; seleksi; sistem pendukung keputusan; TOPSIS.
Abstract:Abstract: One of the main challenges in digital image processing is limited resolution, which makes it difficult to preserve visual details when images are enlarged. Conventional methods such as Bilinear Interpolation are…
e commonly used for image upscaling; however, these approaches often produce blurred images, lose fine textures, and fail to reconstruct complex visual structures. This study aims to enhance digital image resolution by employing a deep learni based approach using a Low-Light Convolutional Neural Network (LLCNN) built upon a Deep Neural Network (DNN) architecture. The dataset used in this study is the DIV2K dataset, which consists of 1,000 high-resolution images. These images were downsampled using scaling factors of ×2, ×3, and ×4 to generate paired Low Resolution–High Resolution (LR–HR) data for training and evaluation. The proposed LLCNN is designed to extract important features such as edges, textures, and local patterns through multiple convolutional layers, followed by non-linear mapping to reconstruct high-resolution images more accurately. Quantitative performance evaluation was conducted using the Peak Signal-to-Noise Ratio (PSNR) and the Structural Similarity Index (SSIM). Model performance was evaluated quantitatively using the Peak Signal-to-Noise Ratio (PSNR) metric. Experimental results showed that the proposed method improved image quality compared to the bilinear method. These results indicate that the deep learning based approach effectively improves image sharpness and structural fidelity, thereby demonstrating its potential for digital image resolution enhancement.
Keywords: deep neural network; image resolution; low-light convolutional neural network; machine learning
Abstrak: Permasalahan utama dalam pengolahan citra digital adalah keterbatasan resolusi yang menyebabkan detail visual sulit dipertahankan ketika citra diperbesar. Metode konvensional seperti Bilinear Interpolation masih banyak digunakan, namun sering menghasilkan citra buram, kehilangan tekstur halus, serta tidak mampu merekonstruksi struktur visual yang kompleks. Penelitian ini bertujuan untuk meningkatkan kualitas resolusi citra digital dengan memanfaatkan pendekatan deep learning berbasis Low-Light Convolutional Neural Network (LLCNN) yang dibangun di atas arsitektur Deep Neural Network (DNN). Data yang digunakan dalam penelitian ini berasal dari dataset DIV2K, yang terdiri dari 1000 citra beresolusi tinggi. Citra tersebut diturunkan menjadi resolusi rendah menggunakan faktor downsampling ×2, ×3, dan ×4 untuk membentuk pasangan data Low Resolution–High Resolution (LR–HR) sebagai data pelatihan dan pengujian. LLCNN dirancang untuk mengekstraksi fitur-fitur penting seperti tepi, tekstur, dan pola lokal melalui beberapa lapisan konvolusi, kemudian melakukan pemetaan non-linear guna merekonstruksi citra resolusi tinggi secara lebih presisi. Evaluasi performa model dilakukan secara kuantitatif menggunakan metrik Peak Signal-to-Noise Ratio (PSNR). Hasil eksperimen menunjukkan bahwa metode yang diusulkan mampu meningkatkan kualitas citra dibandingkan metode bilinear. Hasil ini membuktikan bahwa pendekatan berbasis deep learning efektif dalam meningkatkan ketajaman dan kesesuaian struktur citra digital.
Kata kunci: deep neural network; low-light convolutional neural network; machine learning; resolusi citra
Abstract:Abstract: Bakery MSMEs in Kisaran City play a significant role in the local economy, but their distribution data is still managed manually, making it difficult to access and analyze. This study aims to develop a WebGIS-based…
ased Geographic Information System to map and manage bakery MSME data digitally and in an integrated manner. The research methods include field surveys, spatial and non-spatial data collection, system design using UML, development with Leaflet.js and MySQL, and testing using the blackbox method. The results show that the resulting system is capable of displaying interactive maps with location details, business information, and an easy-to-use search feature. This system makes it easier for the government, business actors, and the public to access MSME information and supports data-based economic development planning. With the output in the form of publications in accredited journals, this research is expected to be an effective solution for MSME data management in other regions.
Keyword: bakery; mapping; MSME; WebGIS
Abstrak: UMKM toko roti di Kota Kisaran memiliki peran penting dalam perekonomian lokal, namun data persebarannya masih dikelola secara manual sehingga sulit diakses dan dianalisis. Penelitian ini bertujuan mengembangkan Sistem Informasi Geografis berbasis WebGIS untuk memetakan dan mengelola data UMKM toko roti secara digital dan terintegrasi. Metode penelitian meliputi survei lapangan, pengumpulan data spasial dan non-spasial, perancangan sistem menggunakan UML, pengembangan dengan Leaflet.js dan MySQL, serta pengujian menggunakan metode blackbox. Hasil penelitian menunjukkan sistem yang dihasilkan mampu menampilkan peta interaktif dengan detail lokasi, informasi usaha, dan fitur pencarian yang mudah digunakan. Sistem ini mempermudah pemerintah, pelaku usaha, dan masyarakat dalam mengakses informasi UMKM, serta mendukung perencanaan pembangunan ekonomi berbasis data. Dengan luaran berupa publikasi pada jurnal terakreditasi, penelitian ini diharapkan menjadi solusi efektif untuk pengelolaan data UMKM di daerah lain.
Kata kunci; pemetaan; toko roti; UMKM; WebGIS
Abstract:Abstract: The global transition towards sustainable food systems faces significant challenges in vegetarian food supply chains, including transparency issues, distribution inefficiencies, and quality verification problems.…
s. This research proposes VegeChain development, a decentralized marketplace ecosystem based on smart contracts designed to transform vegetarian food supply chains and accelerate Meatless, Balanced, Green (MBG) program adoption. Using mixed-method methodology integrating blockchain system design, stakeholder analysis, and economic simulation, this research develops a comprehensive technology framework combining blockchain transparency, smart contract automation, and sustainable tokenomics with novel mathematical models. The system implements dynamic pricing algorithms based on Automated Market Maker (AMM) mechanisms, multi-objective optimization for supply chain efficiency, and reputation-based consensus protocols. Simulation results demonstrate that VegeChain implementation can improve supply chain efficiency by 35%, reduce food waste by 28%, and increase consumer trust by 42% measured through validated stakeholder satisfaction surveys (n=456) using 5-point Likert scales with statistical significance p<0.001. Technical innovations include Byzantine Fault Tolerant consensus with 99.9% reliability, gas optimization achieving 67% cost reduction, and real-time quality verification algorithms with 98.7% accuracy.
Keywords: smart contracts; supply chain optimization; automated market makers; blockchain technology; sustainable tokenomics
Abstract:Abstract: The development of information technology encourages businesses to take over digital systems in business operations, even in the sales process. The Point of Sales (POS) system is the leading solution for recording…
ing transactions, managing stock, and creating sales reports efficiently. This study aims to develop a POS application based on a website and make it easier for administrators to manage sales transactions, making them faster and more efficient. This system is made with a structured Agile Development method, requirements, design, development, testing, deployment, and implementation. The framework used is the Laravel framework, with system testing conducted using BlackBox. The test results show that the system is on track and that the efficiency of the transaction and reporting process can be increased. A web-based basis allows users to manage their business more easily in real time because this application is flexible and can be used on various devices.
Keywords: agile model;laravel;point of sales; websites
Abstrak: Pengembangan teknologi informasi mendorong bisnis untuk mengambil alih sistem digital dalam operasi bisnis, bahkan dalam proses penjualan. Sistem Point of Sales (POS) adalah solusi utama untuk merekam transaksi, mengelola stok dan membuat laporan penjualan secara efisien. Tujuan dari penelitian ini adalah untuk mengembangan aplikasi POS berdasarkan situs web dan memudahkan administrator dalam mengelola transaksi penjualan, membuatnya lebih cepat dan lebih efisien. Sistem ini dibuat dengan metode Agile Development yang terstruktur, requirement, design, development, testing, deployment, dan implementation serta kerangka kerja yang digunakan yaitu framework Laravel dengan pengujian sistem menggunakan Blackbox. Hasil pengujian menunjukkan bahwa sistem berada di jalur dan bahwa efisiensi proses transaksi dan pelaporan dapat meningkat. Dengan berbasis web memungkinkan pengguna untuk lebih mudah mengelola bisnisnya secara real time, karena aplikasi ini fleksibel melalui berbagai perangkat.
Kata kunci: model agile;laravel;point of sales;website
Abstract:Abstract: Non-performing loans remain one of the main challenges faced by cooperatives, particularly when the loan eligibility assessment process is still conducted manually. This traditional approach tends to be time consuming,…
nsuming, subjective, and prone to inaccurate decisions. This study aims to develop a predictive model for borrower eligibility using the Support Vector Machine (SVM) algorithm as a more efficient and objective machine learning-based solution. A total of 1,000 loan history records were processed using RapidMiner software, taking into account variables such as salary, years of employment, loan amount, monthly installment, employment status, monthly expenses, number of dependents, housing status, age, and collateral value. The model’s performance was evaluated using a confusion matrix and classification metrics including accuracy, precision, recall, and kappa. The results indicate that the SVM model achieved an accuracy of 90.05%, precision of 90.13%, recall of 90.05%, and f1 score of 90,08%, reflecting a strong performance in classifying borrower eligibility. The application of this method makes a significant contribution to the development of data driven decision support systems within cooperative environments. This finding expands the scientific understanding in the field of microfinance and supports the implementation of artificial intelligence technologies in making decisions that are more precise, rapid, and accurate.
Keywords: cooperative; eligibility prediction; machine learning; non-performing loan; SVM
Abstrak: Kredit macet merupakan salah satu permasalahan utama yang dihadapi koperasi, terutama ketika proses penilaian kelayakan peminjam masih dilakukan secara manual. Pendekatan ini cenderung lambat, subjektif, dan berisiko menghasilkan keputusan yang kurang akurat. Penelitian ini bertujuan untuk membangun model prediksi kelayakan peminjam menggunakan algoritma Support Vector Machine (SVM) sebagai solusi berbasis machine learning yang lebih efisien dan objektif. Sebanyak 1.000 data riwayat pinjaman diolah menggunakan tools RapidMiner dengan mempertimbangkan variabel: gaji, lama bekerja, besar pinjaman, angsuran per bulan, status pegawai, pengeluaran bulanan, jumlah tanggungan, status rumah, umur, dan nilai jaminan. Evaluasi model dilakukan menggunakan confusion matrix dan metrik klasifikasi seperti akurasi, presisi, recall, dan kappa. Hasil menunjukkan bahwa model SVM mencapai akurasi 90,05%, presisi 90,13%, recall 90,05%, dan f1 score 90,08%, yang mencerminkan performa model yang sangat baik dalam mengklasifikasikan kelayakan peminjam. Penerapan metode ini memberikan kontribusi penting dalam pengembangan sistem pendukung keputusan berbasis data di lingkungan koperasi. Temuan ini memperluas wawasan keilmuan di bidang keuangan mikro dan mendukung penerapan teknologi kecerdasan buatan dalam pengambilan keputusan yang lebih tepat, cepat, dan akurat.
Kata Kunci: koperasi; kredit macet; machine learning; prediksi kelayakan; SVM