MEKAR : Journal Information System and Computer Application
Journal Information System and Computer Application (JICA) - [E-ISSN : 3110-1887] is a scientific journal published by PT Mekar Research and Publishing with the aim of providing a platform for the dissemination of research findings and scientific studies in the fields of information systems and computer applications. The journal facilitates the exchange of knowledge among academics, researchers, practitioners, and stakeholders in the area of information technology and computing. The journal's focus and scope include, but are not limited to: information system development, software engineering, information security, computer networks, web and mobile-based applications, big data, artificial intelligence, cloud computing, and other emerging technologies related to information systems and computer applications. All manuscripts submitted to JICA undergo a double-blind peer review process, in which both the reviewers and the authors remain anonymous to ensure an objective and high-quality review. Journal Information System and Computer Application is published three times a year, in April, August, and December.
Analisis User Interface Website LMS-AKN Pacitan Menggunakan Metode VISAWI
This study evaluates the visual-interface quality of the LMS-AKN Pacitan website through the Visual Aesthetics of Websites Inventory (VISAWI), an instrument built specifically to capture how users perceive a site's visual appeal across four facets: Simplicity, Diversity, Colorfulness, and Craftsmanship. Using a quantitative descriptive design, data were gathered through a questionnaire completed by 39 active students who had used the LMS-AKN Pacitan platform for at least one semester. Findings place the website's overall interface quality in the “good” category, with an aggregate mean score of 3.69 on a five-point Likert scale. Craftsmanship recorded the highest score (3.91), followed by Simplicity (3.87), Diversity (3.55), and Colorfulness (3.42); all four facets fell within the “good” range, suggesting that the interface is straightforward, easy to navigate, and professionally presented. Even so, the comparatively lower Colorfulness and Diversity scores point to room for improvement in color choice and visual variety to further boost user engagement. This study contributes to the growing body of work on digital-learning interface design in higher education and offers practical recommendations for refining the UI toward a more attractive, comfortable, and effective learning experience. Subsequent research is encouraged to pair VISAWI with usability testing and to draw on a larger respondent pool for more generalizable conclusions.
Copyright (c) 2026 Candra Budi Susila, Desanty Ridzky, Pradityo Utomo (Author) https://creativecommons.org/licenses/by/4.0
Automated Decision Support System for Social Assistance Eligibility Based on House Images Using Deep Learning
Social assistance is one of the government programs aimed at improving the welfare of underprivileged communities. However, the process of determining eligible beneficiaries is still largely conducted manually, leading to subjectivity, inaccurate targeting, and time-consuming decision-making. This study proposes an automated decision support system for determining social assistance eligibility based on house images using Deep Learning and the Analytical Hierarchy Process (AHP). The proposed system consists of a house image classification model developed using the MobileNetV2 architecture, a web-based application developed with the Laravel framework, and the integration of image classification results with the AHP method. MobileNetV2 is employed to classify house conditions into eligible and ineligible categories while generating confidence scores. These confidence scores are converted into a 1–10 assessment scale and used as the House Condition criterion in the AHP calculation together with income, occupation, number of dependents, and house ownership. The study utilized a dataset of 300 house images for model training and evaluation. Experimental results show that the MobileNetV2 model achieved an accuracy of 74.00%. Furthermore, the developed system successfully integrates automatic house image classification with AHP-based decision-making, producing more objective, consistent, and accurate recommendations for social assistance recipients while assisting local governments in improving the efficiency and transparency of the beneficiary selection process.
Copyright (c) 2026 David Fernanda, Angga Prasetyo, Indah Puji Astuti (Author) https://creativecommons.org/licenses/by/4.0
Sistem Reservasi Online Barbershop Artjuna Capster Berbasis Web
Barbershop Artjuna Capster masih menerapkan reservasi layanan secara manual sehingga pelanggan harus datang langsung ke lokasi dan sering menghadapi antrian panjang. Penelitian ini merancang dan membangun sistem reservasi online berbasis web menggunakan metode Waterfall, UML dan ERD untuk perancangan, serta PHP dan MySQL untuk implementasi. Pengujian Black Box menunjukkan bahwa sistem mampu memfasilitasi pelanggan memilih layanan, memilih capster tersedia, dan melakukan reservasi tanpa bentrok jadwal, sehingga meningkatkan efisiensi pelayanan Barbershop Artjuna Capster.
Copyright (c) 2026 Muhamad Hamim Madturochim Madjid, Pradityo Utomo, Daniel Wahyu Suprayoga Prabowo (Author) https://creativecommons.org/licenses/by/4.0
A Machine Learning and Reinforcement Learning Framework for Secure, Personalized Web Portofolios
Digital, web-based portfolios have become essential tools for students and job seekers to showcase technical skills. However, most current portfolios are static HTML/CSS sites, vulnerable to cyber attacks and unable to personalize content. This study introduces SecurePortfolio, a conceptual framework combining a machine learning security layer to block malicious traffic and a causal reinforcement learning module to adaptively recommend portfolio content. Simulation results show that the security component mitigates most threat vectors, while the personalization engine improves content relevance compared to static layouts. The framework offers a blueprint for intelligent, secure, and context-aware digital portfolios for graduates entering the workforce.
Copyright (c) 2026 Firman Sholehudin (Author) https://creativecommons.org/licenses/by/4.0
Comparative Analysis Of Star And Mesh Topologies In Computer Networks Based On Literature Study
The development of information technology requires the availability of computer networks that are fast, stable, secure, and easy to manage. One important factor in network design is the selection of a network topology that suits organizational needs. Network topology determines the relationships between devices, data communication paths, installation costs, and ease of maintenance. This study aims to analyze the comparison between two commonly used network topologies, namely Star and Mesh topologies, based on two scientific journals discussing their respective implementations. The research method uses a literature study with a descriptive comparative approach. The results of the study indicate that the Star topology has advantages in terms of ease of installation, low cost, simple management, and is suitable for small to medium-scale Local Area Networks (LAN). In contrast, the Mesh topology excels in redundancy with multiple alternative paths, fault tolerance, security, flexibility, and scalability, making it more suitable for modern wireless networks and environments requiring high network availability. The conclusion shows that there is no universally best topology; instead, the choice must be adjusted to user needs, budget, and implementation scale.
Copyright (c) 2026 Rizki Aditya Putra, Raffi Sulistyo Permana Putra, Zah Rahan Aprilianto (Author) https://creativecommons.org/licenses/by/4.0
Peran Jaringan Komputer dalam Mendukung Implementasi Internet of Things pada Berbagai Sektor Industri
Internet of Things (IoT) telah muncul sebagai pendorong utama transformasi digital lintas sektor yang mencakup layanan publik, industri, perawatan kesehatan, dan pertanian. Namun, keberhasilan penerapannya ditentukan oleh ketagguhan infrastruktur jaringan komputer yang menjadi fondasinya. Artikel ini mengkaji peran penting jaringan komputer dalam menopang ekosistem Internet of Things melalui studi terhadap 30 penelitian terkini (2020–2026), dengan penekanan pada desain, protokol komunikasi, keamanan, dan interoperabilitas. Metodologi yang digunakan adalah tinjauan pustaka yang komprehensif dengan fokus pada arsitektur jaringan, protokol komunikasi, keamanan, dan interoperabilitas.. Temuan studi ini menunjukkan bahwa kebutuhan daya dan pertimbangan geografis harus diperhitungkan saat memilih protokol jaringan (NB-IoT, LoRaWAN, dan Wi-Fi). Menurut laporan ini, penerapan IoT rentan terhadap kegagalan jika tidak didukung oleh standar jaringan yang kuat dan langkah-langkah keamanan berlapis. Pelaksanaan strategi terpadu dan kepatuhan terhadap persyaratan keamanan sangat penting bagi keberhasilan sistem IoT di Indonesia.
Copyright (c) 2026 Puji Astuti Suryaningtyas, Dimas Ainur Pangestu, Afif Nur Wicaksono (Author) https://creativecommons.org/licenses/by/4.0
Decision Support System for Recommendation of Competition Types for Elementary School/Islamic Elementary School/Equivalent Students Using the TOPSIS Method
The selection of students to participate in competitions at the elementary school/Islamic elementary school/equivalent level has been done manually and subjectively, potentially causing inaccuracies in determining the type of competition that suits the students' abilities. This study aims to develop a web-based Decision Support System (DSS) using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method to recommend the right type of competition for elementary school/Islamic elementary school students in Parang District. This system was built using the PHP programming language and MySQL database, with four main criteria: academic grades (weighted 0.35), artistic grades (weighted 0.25), sports grades (weighted 0.20), and student interests (weighted 0.20). The system was developed using the waterfall method and testing was carried out using white box testing. The test results showed that the system was able to produce student rankings based on TOPSIS preference scores with a 100% accuracy rate compared to manual calculations. This system is expected to assist teachers in making decisions more objectively, systematically, and efficiently.
Copyright (c) 2026 Valentino Shidney Shidney, Fauzan Masykur, Dyah Mustikasari, Raveenthiran Vivekanantharasa (Author) https://creativecommons.org/licenses/by/4.0
Evaluation of the Kalman Filter Algorithm for IoT-Based Air and Light Quality Optimization
Health and productivity of poultry, chicken farms require an environment with ideal air and lighting conditions. The urgency of this research requires a real-time IoT system equipped with a Kalman Filter data processing algorithm to reduce sensor noise and improve reading accuracy, as manual monitoring is often inaccurate and slow. Research objectives: 1) Design an IoT system based on multi-parameter sensors (gas and light) to monitor the environmental conditions of chicken farms; 2) Implement a Kalman Filter to filter sensor data noise and produce stable and accurate readings; 3) Evaluate system performance through field tests by comparing filtered data with actual data. The outcomes achieved are proof of submission to a Sinta-accredited journal and intellectual property rights for the monitoring system developed. The implications of this research provide appropriate technological solutions for chicken farms to prevent economic losses due to suboptimal environments.
Copyright (c) 2026 Petrisia Widyasari sudarmadji, Diana Rachmawati (Author) https://creativecommons.org/licenses/by/4.0
Digitalisasi Perpustakaan Berbasis Qr Code Menggunakan Algoritma AES
Perpustakaan adalah lembaga sosial yang didirikan dan dipertahankan oleh masyarakat, sehingga perpustakaan merupakan barometer kemajuan suatu negara, proses peminjaman buku seperti registrasi dan penginputan masih bersifat manual, memakan waktu, rawan kesalahan, dan tidak efisien dalam mengelola data peminjaman. barcode telah terbukti efektif dalam mengelola pencatatan dan inventaris di banyak sektor, termasuk bisnis dan layanan publik, namun penggunaannya masih belum meluas. digitalisasi perpustakaan memberikan banyak manfaat dalam bidang keamanan, efisiensi, dan keakuratan data. Karena itu, sangat dianjurkan untuk menerapkan algoritma AES dalam sistem digitalisasi perpustakaan yang modern. Berbeda dengan sistem yang tidak menggunakan algoritma AES, data buku lebih rentan terhadap manipulasi atau kerusakan yang tidak terdeteksi. Risiko kesalahan manusia dalam proses pencatatan data masih tinggi karena masih memerlukan input manual. Sistem juga harus membandingkan semua data buku, yang memakan waktu cukup lama untuk diambil. Selain itu, kemungkinan terjadinya duplikasi data buku juga bisa terjadi bila tidak ada mekanisme untuk mendeteksi duplikat.
Copyright (c) 2026 Aprilia Cahyanti, Fauzan Masykur, Adi Fajaryanto Cobantoro (Author) https://creativecommons.org/licenses/by/4.0
Implementasi Metode SAW dalam Sistem Pendukung Keputusan untuk Seleksi Jasa Pengiriman Barang UMKM di Kota Blora
The rapid development of digital technology and the surge in e-commerce activities have made reliable goods delivery services a non-negotiable critical success factor for Micro, Small, and Medium Enterprises (MSMEs). However, the vast selection of logistics providers, each presenting distinct advantages and disadvantages, often leads to significant confusion for MSMEs, ultimately compromising their operational efficiency and negatively impacting customer satisfaction. Recognizing this crucial need for streamlined decision-making, this study was explicitly aimed at developing a Decision Support System (DSS) designed to provide objective, data-driven recommendations for selecting the optimal delivery service. We employed a rigorous quantitative research approach, utilizing the widely accepted Simple Additive Weighting (SAW) method for multi-criteria decision analysis. Data were meticulously collected through structured interviews with a substantial sample of 100 MSMEs located in Blora City. The subsequent analytical process systematically involved stages of data normalization, precise criteria weighting (covering aspects like cost, speed, and service quality), and accurate final ranking calculations. The empirical results definitively showed that J&T (A1) obtained the highest overall preference value of 32%, firmly establishing it as the best alternative based on the established criteria. It was closely followed by Lion Parcel (A4), TIKI (A3), and JNE (A2). This outcome strongly demonstrates that the SAW method is highly effective in generating objective, needs-tailored rankings for complex logistical choices. The study ultimately concludes that the successful implementation of this SAW-based DSS significantly improves the objectivity and efficiency of decision-making, empowering MSMEs to strategically align their logistics choices with key performance indicators like low cost, high speed, and excellent service quality, thereby demonstrably enhancing operational efficiency and expanding market reach.
Copyright (c) 2026 Joko Handoyo, Cevin Eris Setiawan (Author) https://creativecommons.org/licenses/by/4.0
Sistem Pendukung Keputusan Penentuan Dosen Pembimbing Skripsi Menggunakan Algoritma TOPSIS
Pemilihan dosen pembimbing merupakan tahapan penting dalam proses penyusunan skripsi mahasiswa. Namun, masih ada mahasiswa yang mengalami kesulitan dalam menentukan dosen pembimbing yang sesuai dengan topik penelitian yang diambil, sehingga seringkali pemilihan dilakukan secara subjektif berdasarkan kedekatan personal. Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan yang dapat membantu mahasiswa dalam menentukan dosen pembimbing secara lebih objektif. Sistem ini diimplementasikan menggunakan metode TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), dengan mempertimbangkan beberapa kriteria utama seperti bidang keahlian, pendidikan terakhir, jabatan fungsional, kuota bimbingan, dan minat dosen. Pengujian sistem dilakukan dengan metode blackbox untuk memastikan seluruh fitur berjalan sesuai fungsi. Hasil implementasi menunjukkan bahwa sistem mampu memberikan rekomendasi dosen pembimbing berdasarkan perhitungan nilai preferensi dari setiap alternatif. Dengan demikian, sistem ini diharapkan dapat mempermudah mahasiswa dalam proses pengambilan keputusan dan meningkatkan efisiensi serta kesesuaian dalam proses bimbingan skripsi.
Copyright (c) 2026 Jordi Yoga Pratama, Ghulam Asrofi Buntoro, Ismail Abdurrozzaq Zulkarnain (Author) https://creativecommons.org/licenses/by/4.0
Pengembangan Media Pembelajaran Interaktif Aljabar Boolean Dan Gerbang Logika Berbasis Android Menggunakan Metode Addie Di SMKN 1 Ngadirojo
Pembelajaran Aljabar Boolean dan Gerbang Logika di SMKN 1 Ngadirojo kerap mengalami kesulitan memahami konsep karena materi masih disampaikan secara abstrak dan statis. Hal ini menunjukkan perlunya media pembelajaran interaktif berbasis Android yang dapat meningkatkan pemahaman siswa. Penelitian ini bertujuan mengembangkan media pembelajaran interaktif berbasis Android untuk membantu siswa SMKN 1 Ngadirojo memahami materi Aljabar Boolean dan Gerbang Logika. Penelitian ini menggunakan model pengembangan ADDIE (Analysis, Design, Development, Implementation, Evaluation) secara sistematis. Hasil penelitian berupa aplikasi Android yang memuat modul materi Aljabar Boolean, simulasi gerbang logika, dan kuis interaktif sebagai evaluasi pemahaman. Pengujian fungsionalitas menggunakan metode black box menunjukkan bahwa seluruh fitur aplikasi berjalan sesuai spesifikasi dan tanpa kesalahan signifikan. Kesimpulannya, media pembelajaran berbasis Android yang dikembangkan ini layak digunakan dan diharapkan dapat membantu siswa memahami materi secara lebih interaktif dibandingkan dengan metode konvensional.
Copyright (c) 2026 Yofhi Fauda Pradana Yofhi, Ismail Abdurrozzaq Zulkarnain (Author) https://creativecommons.org/licenses/by/4.0
Implementasi Metode Simple Additive Weighting (SAW) Untuk Pemilihan Supplier Pakan Ternak Pada Toko Pakan Selo
In the business world, particularly in the livestock feed trade, selecting the right supplier is a crucial factor in maintaining business continuity. However, the supplier selection process is often carried out manually and subjectively, which increases the risk of decision-making errors. This is evident in the case of selecting the best livestock feed supplier at Toko Pakan Selo. This study utilizes a Decision Support System (DSS) employing the Simple Additive Weighting (SAW) method, as Simple Additive Weighting (SAW) is capable of evaluating various alternatives based on multiple criteria, such as feed price, feed quality, delivery accuracy, distance to location, and product availability. The system developed is expected to enhance the effectiveness, efficiency, and objectivity of the supplier selection process. Furthermore, the system aims to replace the traditional manual method with a web-based digital solution. The results of system testing indicate that the system is capable of assisting Toko Pakan Selo in identifying the best supplier and supporting the stability of livestock feed supply. Based on black-box testing, the system functions as intended.
Copyright (c) 2026 Ega Arya Chalandra Daniswara, Pradityo Utomo, Sukadi (Author) https://creativecommons.org/licenses/by/4.0
DETEKSI PENYAKIT DAUN TANAMAN STROBERI MENGGUNAKAN YOLOV8 PENDEKATAN BERBASIS DEEP LEARNING DI TAWANGMANGU
Deteksi dini penyakit pada daun stroberi merupakan langkah strategis dalam upaya peningkatan produktivitas pertanian, khususnya di kawasan dataran tinggi seperti Tawangmangu. Penelitian ini bertujuan untuk mengembangkan dan mengevaluasi performa model YOLOv8 untuk mendeteksi lima kelas utama kondisi daun stroberi secara real-time. Dataset lokal dikumpulkan langsung dari kebun stroberi di Tawangmangu dan dianotasi menggunakan format YOLO. Proses pelatihan mencakup augmentasi data dan pembagian dataset, kemudian dievaluasi menggunakan metrik akurasi, presisi, recall, F1-score, dan mean Average Precision (mAP). Pengujian model di Google Colab menunjukkan performa tinggi dengan nilai evaluasi mAP@0.5 sebesar 99.2% dan mAP@0.5:0.95 sebesar 94.5%. Pengujian lapangan menerapkan implementasi website STROBIKA menunjukkan akurasi rata-rata sebesar 84,6%, dan mampu mengidentifikasi tiga penyakit utama daun stroberi (Leaf Blight, Leaf Spot, dan Tipburn) secara cepat dan akurat. Meskipun terdapat tantangan dalam mengklasifikasikan daun sehat dan objek non-stroberi, sistem ini menunjukkan potensi tinggi untuk diterapkan dalam pertanian berbasis deep learning di dunia nyata.
Copyright (c) 2025 Efi Mukaromah, Fauzan Masykur, Adi Fajaryanto Cobantoro (Author) https://creativecommons.org/licenses/by/4.0
Implementasi Text Mining Pada Analisis SentimenPemain Naturalisasi Timnas Indonesia Dengan Algoritma Naïve Bayes dan Support Vector Machine (SVM)
Sepak bola adalah olahraga paling populer dan banyak dimainkan diseluruh dunia, termasuk Indonesia. FIFA menjadi sebuah lembaga tertinggi yang mengatur segala urusan sepak bola. FIFA banyak memiliki agenda kompetisi sepak bola seperti piala dunia. PSSI sebagai anggota dari FIFA berkesempatan untuk turut serta dalam turnamen yang diadakan oleh FIFA. Piala dunia menjadi mimpi yang terus didambakan oleh seluruh pecinta sepak bola tanah air. Salah satu strategi federasi sepak bola Indonesia yaitu PSSI untuk meningkatkan prestasi tim nasional adalah melalui program naturalisasi pemain asing. Tujuan dari program tersebut tidak lain adalah untuk memperkuat performa timnas agar bisa bersaing untuk merebutkan asa tampil di ajang piala dunia 2026. Program naturalisasi ini memicu berbagai respons dari masyarakat, terutama melalui media sosial twitter. Opini publik yang disampaikan melalui platform tersebut dapat dianalisis untuk mengetahui sentimen masyarakat terhadap kebijakan naturalisasi. Penelitian ini bertujuan untuk melakukan analisis sentimen terhadap cuitan pengguna Twitter mengenai pemain naturalisasi timnas Indonesia dengan menggunakan metode Naïve Bayes dan Support Vector Machine (SVM). Proses analisis mencakup tahapan pengumpulan data, pra-pemrosesan, dan klasifikasi sentimen menjadi dua kategori sentimen, yaitu positif dan negatif. Hasil penelitian menunjukkan Naïve Bayes memiliki tingkat akurasi yang lebih tinggi dibandingkan Support Vector Machine. Akurasi Naïve Bayes sebesar 76,23%, sedangkan SVM memiliki tingkat akurasi sebesar 70,29%. Selain itu, model Naïve Bayes juga lebih unggul dalam nilai precision, recall, dan f1-score dibandingkan dengan SVM. Naïve bayes memiliki nilai 78,43% untuk precision, 75,47% untuk recall, dan 76,93% untuk f1-score. Sementara itu, SVM memiliki nilai presisi sebesar 76,74%, recall sebesar 62,26%, dan f1-score sebesar 68,73%. Berdasarkan hasil tersebut, dapat disimpulkan bahwa metode Naïve Bayes lebih efektif dalam mengklasifikasikan sentimen masyarakat terhadap program naturalisasi pemain timnas Indonesia.
Copyright (c) 2025 Fajar Tri Widodo, Moh. Bhanu Setyawan (Author) https://creativecommons.org/licenses/by/4.0
A Decision Support System For Roof Tile SelectionUsing AHP In The Bedingin Roof Tile Industrial Center
Selecting the appropriate roof tile based on house specifications and user preferences is often a challenge, especially when facing a wide variety of available products. This study aims to design and develop a web-based Decision Support System (DSS) to assist in selecting roof tiles at the Genteng Bedingin Industry Center in Ponorogo. The method used is the Analytic Hierarchy Process (AHP), which allows for pairwise comparison among criteria and subcriteria and evaluates consistency in decision-making. The system considers six main criteria: tile type, price, batten spacing, kluntung size, thickness, and ease of installation, with weights that can be adjusted directly by users. Usability testing using the System Usability Scale (SUS) method involving 15 respondents resulted in a score of 92.48%, indicating that the system is highly user-friendly and delivers logical, needs-based recommendations. This system has proven to be effective in providing accurate and relevant tile selection recommendations and has potential for broader industrial implementation.
Copyright (c) 2026 Ryan Erlangga Ardiansyah, Jamilah (Author) https://creativecommons.org/licenses/by/4.0
OPTIMASI JARINGAN RT/RW NET MENGGUNAKAN SOFTWARE DEFINED NETWORK DAN LOAD BALANCING
Meningkatnya kebutuhan akan akses internet yang stabil dan cepat, terutama di lingkungan RT/RW Net yang melayani pelanggan rumah tangga dengan berbagai kebutuhan seperti streaming dan pengunduhan, memunculkan tantangan dalam pengelolaan lalu lintas jaringan, terutama ketika menggunakan lebih dari satu penyedia layanan internet (ISP). Penelitian ini mengusulkan penerapan arsitektur Software Defined Networking (SDN) sebagai solusi untuk mengatasi masalah distribusi trafik yang tidak merata melalui mekanisme loadbalancing. SDN memberikan kontrol PDF dan fleksibel dalam pengelolaan jaringan, memungkinkan pengaturan lalu lintas secara dinamis dan efisien. Implementasi dilakukan dengan menggunakan pengontrol OpenDaylight dan perangkat MikroTik sebagai router yang dikonfigurasi mendukung protokol OpenFlow untuk loadbalancing dua ISP. Hasil pengujian menunjukkan adanya peningkatan pada parameter Quality of Service (QoS) seperti throughput, delay, jitter, dan packet loss. Dengan penerapan SDN dan loadbalancing setelah dilakukan pengujian dengan QoS didapat hasil rata-rata dari masing-masing parameter yaitu, untuk throughput dengan rata-rata 8,36 mbps , untuk parameter packet loss didapat hasil rata-rata 0.09% , untuk delaynya dengan rata-rata 39 ms dan parameter jitter dengan rata-rata 12,67 ms. Dari semua hasil pengujian parameter diatas membuktikan adanya peningkatan kualitas jaringan dibandingkan dengan sebelum penerapan SDN dan loadbalancing.
Copyright (c) 2025 Fikri Muhamad, Fauzan Masykur, Adi Fajaryanto Cobantoro (Author) https://creativecommons.org/licenses/by/4.0
ANALISIS OPTIMASI QUEUE TYPE DALAM MIKROTIK ROUTER OS V7.15 PADA JARINGAN INTERNET DI SMP NEGERI 6 SUDIMORO
Dalam era digital, akses internet yang cepat dan stabil menjadi kebutuhan utama, khususnya di lingkungan pendidikan. SMP Negeri 6 Sudimoro menghadapi kendala dalam pengelolaan trafik jaringan internet, yang berdampak pada performa pembelajaran daring. Penelitian ini bertujuan untuk menganalisis pengaruh penerapan algoritma antrian queue type CoDel, FQ-CoDel, dan CAKE pada Mikrotik RouterOS v7.15 terhadap kualitas layanan jaringan (Quality of Service/QoS), serta menentukan algoritma yang paling optimal. Metode yang digunakan adalah pendekatan kuantitatif dengan pengujian parameter QoS seperti throughput, delay, jitter, dan packet loss berdasarkan standar TIPHON. Data dikumpulkan menggunakan aplikasi Wireshark dan dikonfigurasi melalui Winbox. Hasil pengujian menunjukkan bahwa algoritma FQ-CoDel memberikan performa terbaik dengan nilai throughput tertinggi tanpa peningkatan jitter maupun delay. Berdasarkan hasil tersebut, FQ-CoDel direkomendasikan sebagai queue type yang paling efektif untuk diterapkan pada jaringan internet sekolah. Implementasi algoritma ini diharapkan dapat meningkatkan efisiensi jaringan serta mendukung kelancaran kegiatan belajar mengajar berbasis digital.
Copyright (c) 2025 Daras Fadila, Adi Fajaryanto Cobantoro (Author) https://creativecommons.org/licenses/by/4.0
Rancang Bangun Sistem Pendukung Keputusan untuk Pemilihan Tema Tugas Akhir Mahasiswa Manajemen Informatika Universitas Merdeka Madiun
Abstract: - Students in the Informatics Management Study Program at Universitas Merdeka Madiun must complete a Final Project (TA) as part of their graduation requirements. However, choosing a project topic that matches their interests and abilities can be difficult. To help solve this problem, a web-based Decision Support System (DSS) was developed using the Weighted Sum Model (WSM). This study focuses on designing and developing a system to assist students in selecting appropriate final project topics more efficiently and objectively. The WSM method is used to assess several theme options based on a set of established criteria. The system was built using the Waterfall development model, which involves analysis, design, implementation, testing, and maintenance stages. Black Box Testing was conducted to verify the system's functionality. The application supports two user roles: administrators and students. Administrators manage the system’s data, including criteria, theme options, evaluations, and user accounts. Students can view recommended project topics and update their profiles. Testing showed a 100% success rate, indicating the system’s reliability. By using this DSS, students can make more informed decisions about their final project themes, improving both the selection process and the overall quality of their research through the use of educational technology.
Copyright (c) 2025 Alexander Kenzy Pinaring Gusti, pradityo Utomo, Sukadi (Author) https://creativecommons.org/licenses/by/4.0