Jurnal Komputer dan Elektro Sains is a peer-reviewed international journal that publishes high-quality research in computational science, artificial intelligence, cognitive engineering, and emerging digital technologies. The journal provides a platform for researchers, academics, and practitioners to disseminate innovative theories, methodologies, algorithms, and engineering applications that advance intelligent computing and digital innovation. It welcomes original research articles and review papers covering a broad range of topics, including artificial intelligence, machine learning, deep learning, data science, computer vision, natural language processing, intelligent systems, cognitive computing, Internet of Things (IoT), cybersecurity, cloud computing, edge computing, robotics, software engineering, computational modeling, decision support systems, human–computer interaction, and other interdisciplinary areas related to computer, electrical, and cognitive engineering. Published twice a year in March and September by Sultan Publisher, the journal is committed to disseminating rigorous, innovative, and impactful research that addresses contemporary scientific and industrial challenges through advances in computational intelligence and engineering technologies.
Analisis Data Tracer Study Alumni Menggunakan Business Intelligence Untuk Evaluasi Kinerja Lulusan
Tracer study merupakan instrumen penting dalam evaluasi mutu pendidikan tinggi karena memberikan gambaran kinerja lulusan di dunia kerja. Namun, pengelolaan data tracer study masih sering dilakukan secara manual, terpisah, dan belum didukung visualisasi yang diperbarui secara berkala. Penelitian ini menawarkan kebaruan melalui integrasi arsitektur ETL (Extract, Transform, Load) dan data warehouse, keterkaitan indikator kinerja lulusan dengan evaluasi kurikulum berbasis Outcome Based Education (OBE), serta pengujian penerimaan pengguna (User Acceptance Testing/UAT) untuk mengukur kebermanfaatan sistem. Penelitian bertujuan mengembangkan sistem Business Intelligence (BI) untuk menganalisis data tracer study alumni dan mendukung evaluasi kinerja lulusan berbasis bukti. Metode yang digunakan adalah Research and Development (R&D), meliputi analisis kebutuhan, perancangan data warehouse, ETL, implementasi dashboard BI, serta evaluasi melalui UAT. Data berasal dari 150 alumni lulusan 2023 dengan total sampling, dan 127 data dinyatakan valid setelah pembersihan. Hasil menunjukkan validitas data sebesar 84,67%, keterserapan kerja 82,67%, median masa tunggu 1 bulan, dan rata-rata 3,3 bulan. Dashboard BI mampu menyajikan informasi interaktif untuk mendukung evaluasi kurikulum berbasis OBE serta pengambilan kebijakan berbasis data dan penyusunan dokumen akreditasi.
Copyright (c) 2026 Wawan Kurniawan, Boy Yuliadi, Asep Wasid, M.Hudzaifah Al Islamy, Indrian Tri Husada https://creativecommons.org/licenses/by-sa/4.0/
Implementasi Adaptive Neuro Fuzzy Inference System (ANFIS) Untuk Prediksi Konsumsi Energi Listrik Rumah Tangga
Konsumsi energi listrik pada rumah tangga terus mengalami peningkatan seiring bertambahnya penggunaan peralatan elektronik dalam aktivitas sehari-hari. Kondisi tersebut mendorong perlunya suatu metode yang mampu memperkirakan kebutuhan energi listrik secara akurat sehingga penggunaan energi dapat dikelola dengan lebih efisien. Penelitian ini bertujuan menerapkan metode Adaptive Neuro-Fuzzy Inference System (ANFIS) untuk memprediksi konsumsi energi listrik rumah tangga berdasarkan data hasil pemantauan menggunakan prototipe. Pengambilan data dilakukan selama 30 hari melalui sistem monitoring berbasis Arduino yang terintegrasi dengan sensor PZEM-004T, sensor DHT, Python, dan web sehingga mampu merekam parameter tegangan, arus, daya, energi listrik, suhu, serta kelembapan secara berkala. Data yang diperoleh kemudian melalui tahapan pembersihan, normalisasi menggunakan min-max scaling, pembagian data menjadi data pelatihan sebesar 70% dan data pengujian sebesar 30%, dilanjutkan dengan proses pembentukan serta pelatihan model ANFIS menggunakan fungsi keanggotaan segitiga. Tingkat kinerja model dianalisis menggunakan nilai Mean Absolute Error (MAE), Root Mean Square Error (RMSE), dan Mean Absolute Percentage Error (MAPE). Hasil pengujian menunjukkan bahwa model mampu mengikuti pola perubahan konsumsi energi listrik dengan tingkat kesalahan yang relatif rendah. Nilai MAE yang diperoleh sebesar 3,64, RMSE sebesar 5,64, dan MAPE sebesar 5,90%, sehingga tingkat akurasi model termasuk dalam kategori sangat baik. Berdasarkan hasil tersebut, metode ANFIS dinilai mampu memberikan prediksi konsumsi energi listrik rumah tangga secara andal serta berpotensi mendukung upaya penghematan dan pengelolaan energi listrik yang lebih efektif.
Copyright (c) 2026 Yogi Ramadani, Desmira Desmira, Dididk Aribowo https://creativecommons.org/licenses/by-sa/4.0/
Fusi Metadata dan Masked Mean–Max Pooling dengan DeBERTa-v3 untuk Klasifikasi Tweet Bencana
Klasifikasi tweet terkait bencana merupakan permasalahan penting dalam pemrosesan bahasa alami karena teks media sosial cenderung pendek, tidak baku, dan sering ambigu. Namun, pemanfaatan metadata dan optimasi ambang keputusan secara terpadu pada model transformer masih terbatas. Penelitian ini mengembangkan model klasifikasi biner dengan mengintegrasikan representasi kontekstual DeBERTa-v3, kata kunci, lokasi, dan metadata numerik tweet. Dataset terdiri atas 7.613 data latih dan 3.263 data uji. Teks dibentuk menjadi masukan terstruktur menggunakan penanda kata kunci, lokasi, dan isi tweet. Representasi token dipadatkan melalui masked mean–max pooling, kemudian digabungkan dengan fitur numerik. Model dilatih menggunakan stratified cross-validation, multi-sample dropout, dan optimasi threshold berdasarkan probabilitas out-of-fold. Kebaruan penelitian terletak pada demonstrasi empiris kontribusi metadata fusion, masked mean–max pooling, dan optimasi threshold berbasis out-of-fold dalam melengkapi representasi kontekstual DeBERTa-v3, yang diperkuat melalui evaluasi ablation terkontrol. Pengujian terhadap 15 konfigurasi menunjukkan bahwa DeBERTa-v3 metadata fusion dengan 3-fold out-of-fold ensemble menghasilkan skor F1 tertinggi sebesar 0,84063, melampaui DeBERTa-v3 metadata fusion dengan holdout sebesar 0,83971, DeBERTa-v3 mean–max sebesar 0,83695, DistilBERT sebesar 0,83450, dan GloVe–SVM sebesar 0,81581. Hasil ini menunjukkan bahwa integrasi metadata dan penentuan threshold berbasis out-of-fold efektif meningkatkan kinerja klasifikasi. Penelitian ini berpotensi mendukung penyaringan informasi bencana dari media sosial secara lebih akurat.
Copyright (c) 2026 Budi Mukhamad Mulyo, Hazna At Thooriqoh, Ardhon Rakhmadi, Devi Ambarwati Puspitasari, Bayu Permana Sukma https://creativecommons.org/licenses/by-sa/4.0/
Comparative Analysis of VGG16, VGG19, and EfficientNetB5 Architectures for Image-Based Banana Ripeness Classification
Banana ripeness classification is an important task in agriculture and food processing that supports automatic and objective sorting processes. Advances in deep learning, particularly Convolutional Neural Networks (CNNs), have demonstrated high capability in image classification tasks. This research aims to analyze and compare the performance of three CNN architectures, namely VGG16, VGG19, and EfficientNetB5, for image-based banana ripeness classification, considering both classification performance and computational efficiency. The dataset used was the Banana Ripeness Classification Dataset, consisting of 1,080 images categorized into three classes: unripe, ripe, and overripe. The dataset was divided into training (70%), validation (15%), and testing (15%) sets. All models were implemented using a transfer learning approach with ImageNet pretrained weights and trained for 30 epochs using the Adam optimizer. Model performance was evaluated using accuracy, precision, recall, and F1-score, while computational performance was assessed based on the total number of parameters, model size, and average inference time per image. The results show that VGG16 and VGG19 achieved the best classification performance, obtaining an accuracy of 99.38%, precision of 0.99, recall of 0.99, and F1-score of 0.99. In contrast, EfficientNetB5 achieved an accuracy of 91.36%, precision of 0.92, recall of 0.91, and F1-score of 0.91. In terms of computational performance, VGG16 contained 15.24 million parameters, with a model size of 58.2 MB and an average inference time of 32.6 ms per image. VGG19 contained 20.29 million parameters, with a model size of 77.4 MB and an average inference time of 39.8 ms per image, while EfficientNetB5 contained 30.50 million parameters, with a model size of 116.8 MB and an average inference time of 45.7 ms per image. These findings demonstrate that VGG16 and VGG19 provide superior classification performance compared with EfficientNetB5 on the utilized dataset, while VGG16 also offers the lowest computational requirements among the evaluated architectures. Therefore, VGG16 represents a promising architecture for developing an accurate and computationally efficient image-based banana ripeness classification system for automated sorting applications.
Copyright (c) 2026 Didin Adri, Rando Rando, Wa Ode Vivi Murwati https://creativecommons.org/licenses/by-sa/4.0/
Perancangan sistem informasi manajemen bengkel motor berbasis web menggunakan metode waterfall
Pengelolaan data pada bengkel motor skala kecil di Kabupaten Bogor masih dilakukan secara manual melalui buku catatan, sehingga menimbulkan kesalahan pencatatan, kesulitan penelusuran riwayat servis, ketidaksesuaian stok suku cadang, serta lambatnya penyusunan laporan. Penelitian ini bertujuan merancang dan mengimplementasikan sistem informasi manajemen bengkel motor berbasis web bernama Home Garage yang mengelola data operasional secara terintegrasi dan menghasilkan laporan secara otomatis. Penelitian menggunakan pendekatan kualitatif dengan desain studi kasus tunggal pada satu bengkel motor. Informan dipilih secara purposif dan data dikumpulkan melalui observasi, wawancara semiterstruktur, serta dokumentasi, kemudian dianalisis menggunakan model Miles dan Huberman. Kelemahan sistem berjalan diidentifikasi menggunakan kerangka PIECES dan diturunkan menjadi sembilan kebutuhan fungsional, dimodelkan dengan Unified Modeling Language, lalu dikembangkan menggunakan metode Waterfall dengan PHP Native dan basis data MySQL. Pengujian dilakukan menggunakan Black Box Testing dengan teknik equivalence partitioning dan boundary value analysis terhadap 32 kasus uji yang terdiri atas 23 skenario positif dan 9 skenario negatif, termasuk kondisi stok tidak mencukupi, kuantitas tidak valid, pembatalan transaksi, dan kegagalan penyimpanan. Seluruh kasus uji berperilaku sesuai spesifikasi dan konsistensi antara data servis, data detail servis, dan stok suku cadang tetap terjaga. Kontribusi penelitian terletak pada penempatan relasi servis–detail servis–suku cadang sebagai inti rancangan basis data sehingga pemutakhiran stok menjadi konsekuensi otomatis dari pencatatan servis, bukan pekerjaan pencatatan terpisah. Penelitian ini membuktikan kebenaran fungsional sistem, bukan besaran peningkatan efisiensi: waktu proses, kegunaan, penerimaan pengguna, keamanan, dan kinerja belum diukur, dan temuan bersifat spesifik pada kasus yang diteliti sehingga tidak digeneralisasi ke seluruh bengkel motor.
Copyright (c) 2026 Ananda Farhan Zaini, Teri Mengkasrinal, Hidayatul Ichwan https://creativecommons.org/licenses/by-sa/4.0/
Pengembangan Sistem Informasi Penjualan dan Pemesanan Kue Berbasis Web Menggunakan Framework Laravel pada UMKM Maria Kue
Digitalisasi UMKM kuliner rumahan masih terhambat oleh proses penjualan yang terfragmentasi antara kanal promosi informal, perhitungan manual, dan pencatatan berbasis kertas. Kajian terhadap sistem penjualan berbasis Laravel terdahulu menunjukkan sebagian besar berhenti pada modul katalog dan pemesanan, sedangkan verifikasi pembayaran beban administratif terbesar pada UMKM yang bertumpu pada transfer bank manual masih ditangani di luar sistem. Celah inilah yang diangkat penelitian ini. Penelitian bertujuan merancang, membangun, dan mengevaluasi aplikasi penjualan dan manajemen toko berbasis web pada UMKM Maria Kue menggunakan Framework Laravel dengan arsitektur Model-View-Controller (MVC). Pengembangan menggunakan model Prototyping melalui lima iterasi terdokumentasi yang masing-masing memiliki tujuan, kriteria evaluasi, umpan balik, dan perubahan sistem tercatat sehingga proses penelitian dapat direplikasi. Kebaruan penelitian terletak pada integrasi rekonsiliasi pembayaran transfer bank berbasis webhook Moota ke dalam siklus status pesanan sebagai alternatif berbiaya rendah terhadap payment gateway komersial, disertai pemodelan keterlacakan dari kebutuhan pengguna hingga artefak implementasi. Pengujian dilakukan melalui Black Box Testing atas 12 skenario positif dan negatif serta User Acceptance Test (UAT) dengan kuesioner Likert 1–5 sebanyak 15 butir pada dimensi Usability, Information Quality, dan System Quality. Seluruh skenario fungsional berstatus valid, dan UAT terhadap 10 responden memperoleh skor 692 dari 750 atau 92,27% (rerata 69,20; simpangan baku 1,32; koefisien variasi 1,90%). Sempitnya sebaran skor menunjukkan penerimaan yang konsisten antarperan pengguna, bukan sekadar nilai agregat yang tinggi. Secara praktis sistem memadatkan alur manual enam langkah menjadi satu alur terpusat; secara metodologis penelitian menyediakan kerangka pelaporan iterasi Prototyping yang dapat diadopsi pada pengembangan sistem informasi UMKM lain.
Copyright (c) 2026 Reginaldus Dambuk, Verdi Yasin, Hidayatul Icwan, Anton Zulkarnain Sianipar https://creativecommons.org/licenses/by-sa/4.0/
Analisis komparatif efisiensi listrik dan termal sistem panel surya konvensional dan berpendingin thermoelectric cooler (TEC)
Kebutuhan energi listrik yang terus meningkat serta keterbatasan energi fosil mendorong pengembangan energi terbarukan, khususnya energi surya melalui teknologi photovoltaic (PV). Namun, peningkatan suhu operasi akibat radiasi matahari menyebabkan penurunan efisiensi listrik panel surya. Penelitian ini bertujuan untuk menganalisis efektivitas Thermoelectric Cooler (TEC) sebagai sistem pendingin aktif pada panel surya serta pengaruhnya terhadap kinerja listrik dan termal sistem. Metode yang digunakan adalah analisis komparatif kuantitatif antara sistem photovoltaic konvensional dan photovoltaic dengan pendingin TEC. Penelitian dilakukan menggunakan panel surya monocrystalline 50 Wp yang diuji pada kondisi lingkungan terbuka. Parameter yang dianalisis meliputi suhu permukaan panel, tegangan, arus, daya keluaran, Net Electrical Efficiency, dan Coefficient of Performance (COP). Hasil penelitian menunjukkan bahwa penggunaan TEC menurunkan suhu panel secara signifikan, dari 45,57 °C menjadi 27,71 °C pada bagian atas dan dari 43,57 °C menjadi 29,86 °C pada bagian bawah panel. Penurunan suhu mencapai 39% dan 31% pada masing-masing bagian. Meskipun TEC memerlukan daya tambahan rata-rata sebesar 2,57 W, sistem menunjukkan nilai Net Electrical Efficiency sebesar 24,97% dan COP sebesar 6,14. Hasil ini menunjukkan bahwa TEC efektif meningkatkan performa termal panel surya, namun optimasi lebih lanjut masih diperlukan untuk meningkatkan efisiensi listrik keseluruhan sistem photovoltaic.
Copyright (c) 2026 Rahmadinda Wahyu Gizela, Priyo Adi Sesotyo, Puri Muliandhi https://creativecommons.org/licenses/by-sa/4.0/
Evaluasi Ketersediaan Biomassa Pertanian untuk Implementasi Co-firing pada PLTU Batubara Jawa Tengah Periode 2025–2030 Berbasis Low Emissions Analysis Platform (LEAP)
Provinsi Jawa Tengah menanggung kapasitas PLTU batubara terbesar di Indonesia sebesar 10.222,40 MW, sementara fraksi energi baru terbarukan baru mencapai 21,08 % dari target RUED sebesar 21,32 % pada 2025. Penelitian ini mengevaluasi ketersediaan biomassa pertanian Jawa Tengah untuk co-firing pada delapan PLTU batubara periode 2025 sampai 2030 menggunakan perangkat lunak Low Emissions Analysis Platform (LEAP). Massa biomassa yang tersedia diestimasi menggunakan metode Residue to Product Ratio yang dikoreksi dengan collection factor, diproyeksikan dari data produksi BPS 2020–2024. Hasil proyeksi menunjukkan biomassa tersedia turun dari 16,81 juta ton pada 2025 menjadi 15,79 juta ton pada 2030. Enam skenario co-firing, mengombinasikan dua rasio massa (2 % dan 5 %) dengan tiga skenario nilai kalor biomassa, menghasilkan penurunan input energi panas maksimum sebesar 2,77 %, jauh di bawah batas toleransi operasional 3 % yang lazim diterapkan pada boiler eksisting. Skenario 5 % rata-rata menghindarkan emisi 2,98 juta ton CO2 ekuivalen per tahun dan menaikkan fraksi EBT sektor ketenagalistrikan menjadi 22,51 %, di atas ambang RUED. Penghematan biaya bahan bakar netto berkisar Rp 0,95 sampai Rp 5,86 triliun per tahun tergantung skenario harga batubara. Temuan ini menunjukkan bahwa surplus biomassa pertanian Jawa Tengah memadai untuk mendukung implementasi co-firing, baik secara teknis maupun ekonomi.
Copyright (c) 2026 Muhammad Ali Akbar Sholahuddin, Priyo Adi Sesotyo, Fahrudin Ahmad https://creativecommons.org/licenses/by-sa/4.0/
Lightweight CNN and Grad-CAM Integration for Interpreting Arabic Sign Language Hijaiyyah Letter Classification
Communication plays an important role in social life as a means of conveying information and building interactions between humans. For individuals who are deaf and mute, sign language serves as a visual communication medium that supports the process of conveying messages. One of the sign language systems is Arabic Sign Language (ArSL), which utilises the Hijaiyyah letters through the fingerspelling method to spell out certain terms or vocabulary. However, the limited understanding of sign language within society still poses a barrier to social interaction. This research develops an Arabic Sign Language (ArSL) Hijaiyyah letter classification system based on a Lightweight Convolutional Neural Network (CNN) with the aim of producing a model that has high performance and low computational requirements. Additionally, the Explainable Artificial Intelligence (XAI) method using Gradient-weighted Class Activation Mapping (Grad-CAM) is applied to enhance the transparency of classification results through the visualisation of important areas in the images. Based on the test results, the developed model achieved an accuracy of 0.84, a precision of 0.84, a recall of 0.84, an F1-score of 0.84 and a an Specificity of 0.99. The Grad-CAM visualisation results show that the model focuses on the relevant hand areas during the prediction process. The findings of this study indicate that the system is capable of performing classification with good and measurable performance, as well as supporting real-time sign language recognition with a short response time, thereby improving communication accessibility for individuals with disabilities.
Copyright (c) 2026 Akbar Sidqi, Ana Rizkiya https://creativecommons.org/licenses/by-sa/4.0/
Developing a Context-Aware Self-Assessment Model to Mitigate Phishing Vulnerabilities in Academic Institutions
Higher education institutions in Indonesia have emerged as primary targets for cyberattacks, particularly phishing, due to the high value of academic data and the inherent openness of information access. Conventional technical security approaches often fail to mitigate human error, which remains a critical vulnerability. This study aims to develop a phishing vulnerability detection model based on active participation (self-assessment) using the WiCanary platform to enable academic communities to measure their security risks independently. Employing a Research and Development (R&D) methodology, contextual phishing simulations were conducted on 100 respondents at the Budi Utomo Institute of Technology. The experimental results revealed an average vulnerability rate (Click Rate) of 22%, contrasted by a low Reporting Rate of only 7%. A significant gap was identified between theoretical knowledge and actual behavior, particularly among faculty members who exhibited the Dunning-Kruger Effect in response to administrative-themed scenarios. However, the implementation of the self-assessment model successfully enhanced knowledge retention and reduced vulnerability by 40% in subsequent testing. In conclusion, this model serves as an effective, persuasive, and sustainable early mitigation strategy to fortify the human firewall within academic environments.
Copyright (c) 2026 Andre Yuswanto, Budi Wibowo, Taufik Hidayat https://creativecommons.org/licenses/by-sa/4.0/
Transformasi Digital Diagnosis Penyakit GERD Melalui Sistem Pakar Menggunakan Certainty Factor
Penyakit Gastroesophageal Reflux Disease (GERD) adalah gangguan pencernaan kronis akibat meningkatnya asam lambung secara berlebih yang membutuhkan pengobatan dini untuk mencegah komplikasi serius. Keterbatasan akses ke tenaga medis spesialis seringkali menghambat proses diagnosis awal. Studi ini bertujuan mengembangkan sistem pakar berbasis web untuk mendiagnosis GERD menggunakan metode Certainty Factor berdasarkan data yang diperoleh dari pakar. Pengembangan sistem menggunakan metodologi Siklus Hidup Pengembangan Sistem Pakar (ESDLC), meliputi enam tahap: akuisisi persyaratan, akuisisi pengetahuan melalui wawancara terstruktur dengan dokter spesialis penyakit dalam untuk memperoleh gejala, aturan If-Then, serta bobot Measure of Belief (MB) dan Measure of Disbelief (MD), desain sistem mencakup basis pengetahuan dan mesin inferensi runut maju, implementasi menggunakan PHP dan MySQL, pengujian akurasi, serta dokumentasi. Hasil perhitungan Certainty Factor menghasilkan nilai kepercayaan yang mencerminkan tingkat kepastian diagnosis berdasarkan gejala yang dimasukkan pengguna. Pengujian terhadap 15 data uji menghasilkan akurasi 93,33%, presisi 88,89%, dan recall 100% untuk diagnosa GERD. Evaluasi kegunaan menggunakan System Usability Scale (SUS) menghasilkan skor rata-rata 78,5 (kategori Good). Hasil ini menunjukkan bahwa sistem mampu berfungsi sebagai instrumen pendukung keputusan klinis (CDSS) yang efektif, akurat, dan mudah diakses bagi masyarakat luas, meskipun cakupan data masukan masih perlu dikembangkan lebih lanjut.
Copyright (c) 2026 Elfina Novalia, Apriade Voutama, Adhi Rizal https://creativecommons.org/licenses/by-sa/4.0/
Digital Forensics for Cyberattack Detection in VM Migration: A Conceptual Framework
Virtual machine (VM) migration is widely used in cloud environments because it helps systems stay flexible and use resources more efficiently. At the same time, it can introduce security concerns, especially when forensic investigation is needed. Most previous studies look at areas like intrusion detection or memory forensics, but they are usually treated separately and not in relation to VM migration. In this work, a digital forensic framework is proposed for VM migration scenarios. The idea is to bring several steps together, such as monitoring, collecting data, analyzing it, and reporting the findings. One important point is the migration phase itself, since system states are moving between hosts and some activities may not be fully visible during this process. The framework is discussed conceptually by looking at how these parts interact and how it can address some of the limitations found in earlier work. In general, combining detection and forensic analysis in this way can help make investigations more consistent. This study can also be used as a starting point for further work and practical use in cloud systems.
Copyright (c) 2026 Taufik Hidayat, Nadim Ibrahim https://creativecommons.org/licenses/by-sa/4.0/
Smart Aquaculture: Automated Fish Feeding with Blynk Alerts
Rapid developments in aquaculture have driven the need for efficient and sustainable feeding systems. This study presents the design and implementation of an automatic fish feeder using the Wokwi platform, integrated with the Blynk application. The system aims to deliver feed at optimal intervals and quantities, improving fish growth while minimizing waste. The research utilizes ESP32 as the main controller and servo motors to operate the feeder mechanism. Feeding schedules can be remotely controlled via the Blynk mobile app, allowing for flexible and precise feed management. Testing results indicate that the system consistently provides accurate feed portions at designated intervals, demonstrating reliability and ease of use. This automated feeder offers a cost-effective and environmentally friendly solution for aquaculture, reducing the labor and inefficiencies associated with manual feeding. Consequently, this innovation represents a significant advancement in aquaculture technology, promoting sustainable practices and enhancing overall operational efficiency.
Copyright (c) 2025 Budi Wibowo, Nida Pristyan Ramadhani, Fachri Alfianza, Febriano Anggawa Rizky, Taufik Hidayat https://creativecommons.org/licenses/by-sa/4.0/
Analisis Perencanaan Pencahayaan Alami dan Buatan Gedung Fakultas Teknik dengan Dialux
Perencanaan intensitas pencahayaan alami dan buatan yang efektif di ruang-ruang gedung, terutama ruang kelas dan ruang administrasi, sangat penting untuk memastikan kenyamanan visual serta efisiensi energi. Pencahayaan yang optimal mendukung kualitas pembelajaran dan mengurangi ketergantungan pada pencahayaan buatan yang boros energi. Penelitian ini bertujuan menganalisis perencanaan intensitas pencahayaan di lantai 1 Gedung Fakultas Teknik Universitas Darul 'Ulum Jombang menggunakan perangkat lunak Dialux serta mengidentifikasi faktor yang mempengaruhi distribusi pencahayaan di berbagai ruang. Data yang digunakan meliputi floor plan, hasil simulasi pencahayaan dari Dialux, dan pengukuran menggunakan lux meter. Hasil penelitian menunjukkan sebagian besar ruang di lantai 1 Gedung Fakultas Teknik memiliki pencahayaan alami yang kurang memadai. Penelitian ini menunjukan bahwa Ruang Wadek 1 memiliki intensitas pencahayaan alami hanya 1,8 lux, jauh di bawah standar SNI 300 lux. Sebaliknya, Ruang Kelas memiliki 9,2 lux, meskipun standar untuk ruang kelas adalah 350 lux. Simulasi menunjukkan pencahayaan alami di Mini Hall dan Ruang Arsip cukup baik, namun masih perlu perbaikan. Penambahan lampu LED Philips CoreLine Downlight gen5 DN142B 20S PSU-E/4000K WR 19-watt meningkatkan pencahayaan menjadi 429 lux di Ruang Wadek 1 dan 376 lux di Ruang Kelas, memenuhi standar SNI. Penelitian ini menyarankan perbaikan desain arsitektur dan integrasi pencahayaan alami dan buatan yang lebih efisien untuk meningkatkan kenyamanan visual serta mengurangi konsumsi energi.
Copyright (c) 2025 Muhammad Aziz, Muhlasin Muhlasin, Machrus Ali https://creativecommons.org/licenses/by-sa/4.0/
Design of Prototype Temperature and Humidity Control System for Oyster Mushroom Barns Integrated with ThingsBoard for Real-Time Monitoring
Oyster mushrooms grow optimally at 24-27°C and 80-95% relative humidity. Environmental conditioning through manual spraying water in the mushroom barn in the morning and evening is considered less effective and requires high effort. The application of technology in mushroom cultivation can help control temperature and humidity automatically. This study aims to design an automatic control system to regulate temperature and humidity in oyster mushroom farms. The research was conducted at an altitude of 125 meters above sea level with an automatic control system that has a setpoint temperature of 24-27 ° C and humidity of 80-95%. The test was conducted in a 4 × 2 × 2 m mushroom barn with a capacity of 600 mushroom bag logs. The performance test results showed that the daily temperature and humidity without control ranged from 24.10-35.19 °C and 64.28-99.90%. In contrast, with automatic control, daily temperature and humidity were recorded between 25.10-30.09 °C and 80.84-99.90%. This study shows that the automatic control system Effectively maintains optimal environmental conditions for oyster mushroom growth.
Copyright (c) 2025 Riko Adytia Anggara, Budi wibowo, Muhamad Riko Arafi, Mudrika Afdila https://creativecommons.org/licenses/by-sa/4.0/
Risk Analysis of Bruteforce Attacks on Webserver with Telegram Notifications
In today's digital era, server security is a top priority for many organizations. Intrusion Detection Systems (IDS) such as Fail2ban, have proven effective in protecting servers from threats by monitoring logs and blocking suspicious IP addresses. This paper discusses the implementation of Fail2ban integrated with Telegram notifications, how it works, testing, and results showing improvements in detecting and responding to attacks. Server ssh brute force attacks pose considerable risks to web servers and have potentially severe consequences. Implementing strong preventive measures, continuous monitoring, and leveraging Telegram notifications for real-time alerts significantly improved the organization’s security posture. These combined efforts ensure robust and responsive detection of brute force attacks. Fail2ban was able to quickly discover the IP address from which the attacker performed the brute force attack and took preventive action by blocking the attacker's Ip for 3 failed login attempts within a specified time limit of 3600 s.
Copyright (c) 2025 Budi Wibowo, Luqman Hafiz https://creativecommons.org/licenses/by-sa/4.0/
Design and Evaluation of an Automatic Roof Drive Prototype in Optimizing Tomato Cultivation
This study introduces the design and evaluation of an automatic roof drive prototype aimed at optimizing tomato cultivation. Developed to address the challenges of erratic weather, the system seeks to enhance the efficiency of tomato farming. The prototype integrates a weather sensor, microcontroller, and roof drive mechanism, allowing it to operate automatically based on real-time environmental conditions. Effectiveness was assessed through field trials measuring key growth parameters such as plant height, fruit number, and fruit quality. Results indicate that the automatic roof drive system significantly improves both the productivity and quality of tomato crops. Additionally, the system effectively mitigates losses due to extreme weather conditions, including heavy rain and excessive heat. These findings highlight the potential of automated roof drive technology to support more efficient and sustainable agriculture. Future work will focus on refining the system for broader applications and integrating advanced technologies such as IoT and machine learning for further optimization.
Copyright (c) 2025 Budi Wibowo, Affan Nawly Tanjung, Nur Afandi, Tio Dwi Ananpasha, Taufik Hidayat https://creativecommons.org/licenses/by-sa/4.0/
Analisa Metode Pengalokasian Time Slot pada Jaringan Time Division Duplex
Perkembangan komunikasi bergerak sudah sangat maju teknologi. Tujuan perkembangan jaringan komunikasi bergerak adalah menyediakan standar yang dapat memenuhi aplikasi-aplikasi nirkabel yang luas variasinya, tidak hanya mampu menyediakan jenis layanan dasar seperti suara (voice) dan pesan (messaging) saja melainkan telah diperluas hingga mampu menyediakan jenis layanan multimedia dan high multimedia. Salah satu karakter layanan multimedia dan high multimedia adalah sifat keasimetrisan dari sisi trafiknya, sehingga kebutuhan data rate pada arah downlink berbeda dengan kebutuhan data rate pada arah uplink. Hal ini dapat menyebabkan ketidakefisienan penggunaan bandwitdh apabila diimplementasikan dengan menggunakan sistem FDD, untuk hal tersebut maka UMTS juga mengeluarkan standard TDD dimana pada sistem ini alokasi time slot antara uplink dan downlink dapat diatur sehingga sistem dapat mencapai kondisi optimal. Pengalokasian time slot antara uplink dan downlink yang optimal disimulasikan dengan metode alokasi time slot seragam (uniform allocation) dan metode alokasi time slot tak-seragam (non-uniform allocation). Masing-masing formulasi kedua metode alokasi time slot tersebut diselesaikan dengan metode optimasi simpleks. Dari hasil simulasi tersebut terlihat bahwa metode uniform allocation sesuai untuk jenis trafik simetris dan komposisi trafik antar sel yang seragam, sedangkan metode non-uniform allocation sesuai untuk jenis trafik asimetris dengan tingkat keasimetrisan yang tinggi. Pada kondisi rasio interferensi yang tinggi maka metode non-uniform memiliki tingkat ketahanan kapasitas yang lebih baik dibandingkan metode uniform.
Copyright (c) 2025 Rini Astuti https://creativecommons.org/licenses/by-sa/4.0/
Pengembangan Sistem Pengontrolan Berat menggunakan PID berbasis Arduino & Paralax Data Acqusition
Telah dilakukan pengembangan sistem pengontrolan berat menggunakan PID berbasis Arduino dan Paralax Data Acqusition. Pengontrolan berat pada benda cair ini berguna dalam proses di industri. Loadcell (Strain gauge) akan membaca besar nilai dari berat benda cair tersebut. Loadcell dirancang dengan menggunakan Arduino UNO R3 yang didalamnya terdapat mikrokontroler ATMEGA 328P menggunakan komunikasi data Integrated Inter Circuit (I2C) sebagai penghubung terhadap LCD sebagai display dan menggunakan gear pump sebagai alat penambah ataupun pengurang dalam pengontrolan berat pada benda cair ini. Untuk menampilkan hasil pengukuran dari loadcell digunakan software Paralax Data Acqusition yang akan menampilkan grafik serta tabel data pengukuran. Data hasil pengukuran menunjukan bahwa pompa akan bekerja mengikuti set point yang telah ditentukan dan menyesuaikan berdasarkan kondisi pembacaan berat. Berdasarkan hasil pengujian ini maka sistem dapat digunakan menjadi sistem pengontrolan berat pada benda cair.
Copyright (c) 2024 Siti Rokhmanila, Rini Astuti https://creativecommons.org/licenses/by-sa/4.0/
Radar Wing Defender (RWD): Sistem untuk membantu para petani dalam mendeteksi dan pengusir hama burung
Around 90% of Indonesia's population uses rice as food. However, the production process has not been able to fully fulfil the needs of the community, due to several obstacles that affect productivity. Bird pests are one of the main causes of rice disruption. Group birds are known as one of the few pests that tend to cause population problems. The purpose of this research is to get the design of an IoT-based rice bird repellent. This IoT-based bird repellent consists of two main parts: hardware, or hard system, and software, or soft system. An ESP32 microcontroller and ultrasonic sensors are used in this prototype. This Bird Pest Prototype can be hammered automatically. As a result, the existence of this prototype makes it easier for caregivers to treat patient wounds in case of pest injuries; however, this can be done more effectively and efficiently because caregivers do not need to visit the fields to treat patient wounds due to various pest injuries. Based on this prototype, if the ultrasonic sensor detects a bird with a range of 0 to 4 metres, the buzzer will sound, and the servo motor will move the lever to bring the radar-detected bird closer.
Copyright (c) 2025 Fawwaz Mulya Rabbani Fawwaz, Rafi Fadhlurrahman, Nadira Eka Putri, Raihan Akmalano, Galih Alif Artanto, Rahmat Hidayat https://creativecommons.org/licenses/by-sa/4.0/
Sistem Pemantauan Suhu Otomatis untuk Ruang Penyimpanan Obat dengan Mikrokontroler
Obat-obatan adalah salah satu produk yang sangat penting dalam kehidupan manusia. Oleh karena itu, penyimpanan obat harus dilakukan dengan baik agar kualitasnya tetap terjaga. Salah satu faktor yang penting untuk diperhatikan dalam penyimpanan obat adalah suhu. Suhu yang terlalu tinggi atau rendah dapat menyebabkan obat rusak. Untuk menjaga suhu ruang penyimpanan obat agar tetap stabil, diperlukan sistem pemantauan suhu yang dapat bekerja secara otomatis. Sistem pemantauan suhu ini dapat menggunakan mikrokontroler sebagai pengendalinya. Dalam penelitian ini, telah dirancang sistem pemantauan suhu otomatis untuk ruang penyimpanan obat dengan menggunakan mikrokontroler ESP8266. Sistem ini menggunakan sensor DHT22 untuk mendeteksi suhu ruang penyimpanan obat. Jika suhu ruang penyimpanan obat mencapai 25 derajat celcius, maka kipas DC akan menyala secara otomatis. Sebaliknya, jika suhu ruang penyimpanan obat dibawah 25 derajat celcius, maka kipas DC akan mati secara otomatis. Hasil pengujian sistem pemantauan suhu menunjukkan bahwa sistem ini dapat bekerja dengan baik serta suhu ruang penyimpanan obat dapat dijaga agar tetap stabil.
Copyright (c) 2025 Rifky Abilio Faizal, Andrean Hosea Simanjuntak, Bagas Sulistyo, Luthfi Luqman Fattah, Rafly Fawaz Fauzi, Rahmat Hidayat https://creativecommons.org/licenses/by-sa/4.0/
A Review Method for Analysis of the Causes of Data Breach in the Pasca Pandemic
The vulnerability of personal data breaches makes countries aware of the importance of regulations governing the protection of personal data Therefore, the importance of this research is to conduct a systematic review of the causes of data breaches based on the mechanism of activities carried out to answer problems and provide solutions to problems related to information security. The Systematic Literature Review (SLR) method was used to identify 283 papers in IEEE Xplore database, direct and signature digital science library based on automated search and predefined strings. Then 18 papers were selected for study based on inclusion and exclusion criteria. From the literature study, it can be concluded that the trends analyzed, data breaches are caused by user behavior that has not been educated about the dangers of data theft and awareness of information security.
Copyright (c) 2025 Andrie Yuswanto, Budi wibowo, Luqman Hafiz https://creativecommons.org/licenses/by-sa/4.0/
Implementasi Sistem Informasi Wisata Berbasis Media Sosial untuk Meningkatkan Promosi Destinasi Pariwisata di Muara Enim
This research discusses the implementation of a social media-based tourism information system to improve the promotion of tourism destinations in Muara Enim, South Sumatra. With a focus on TikTok and Instagram, this research addresses the lack of understanding of Muara Enim's tourism potential among people outside the region through qualitative methods and data analysis. The results show that the utilization of social media, such as TikTok and Instagram, effectively increases the visibility of Muara Enim's tourism destinations, attracts tourists, and expands people's understanding of the tourism potential in the area. In the context of contribution, this research highlights the role of social media as an effective tool for local tourism development. As a suggestion for future research, further studies regarding the interaction and direct response of tourists to social media content, as well as evaluating the economic impact of increased tourism in Muara Enim. This can help a deeper understanding of the potential and challenges in developing the tourism sector through social media in Muara Enim.
Copyright (c) 2024 Diestha Wulandari, Indah Febrianti Makini, Ananda Putri Aulia, M Arief Rahman https://creativecommons.org/licenses/by-sa/4.0/
Manajemen Proyek Sistem Informasi Kesehatan Mental Mahasiswa berbasis Akun Tiktok @healing.campus
Project Management for Mental Health Information System among Students Based on TikTok Accounts (Healing.Campus) is an initiative aimed at providing an alternative solution to assist students in dealing with mental health issues. Mental health is a crucial aspect of general well-being, yet issues related to mental health among students remain constrained and limited. This research employs a qualitative research method and data analysis techniques as a theoretical study. Qualitative research methods are used due to literature indicating constraints and limitations in using TikTok as a platform for developing students' mental health. Data analysis techniques, as part of the theoretical study, are utilized to determine whether the hypotheses formulated in the literature review are accurate. The research findings demonstrate that the TikTok-based information system, Healing.Campus, for mental health has achieved satisfactory outcomes, reflecting a significant positive impact on its audience. The Healing.Campus TikTok account has been able to contribute positively to students' mental health. Motivational video content has successfully created a supportive and empathetic atmosphere, provided practical solutions, and reduced stigma associated with mental health issues. It has successfully attained positive and significant outcomes in aiding students in addressing mental health concerns. This TikTok account proves its effectiveness in creating a supportive and empathetic atmosphere, offering practical solutions, and reducing the stigma associated with mental health problems. The existence of this mental health information system is expected to provide motivation and encouragement to students facing difficulties.
Copyright (c) 2024 Rio Anugrah, Najla Puteri Salsabila, Nurul Agami, Faresh Utomo, Vitha Anggraini, Aryo Wiranata, M Arief Rahman https://creativecommons.org/licenses/by-sa/4.0/
AWAS: Auto Weigh Air Sorter Untuk Memilah Barang Berdasarkan Berat Di Bandara
Auto Weigh Air Sorter (AWAS) is a technological innovation designed to sort items based on weight at airports. This system uses Arduino as a controller and a load cell as a weight sensor. Items are sorted using a servo motor based on the data obtained from the sensor. The aim of AWAS is to improve efficiency and accuracy in baggage handling, thereby speeding up the process of pricing and baggage handling. Thus, AWAS have the potential to make a significant contribution to the aviation industry by improving service quality to passengers and reducing baggage waiting time. This research focuses on the design, implementation, and evaluation of the AWAS system, as well as its potential application in the airport context.
Copyright (c) 2024 Rahmat Hidayat, Wafiq Nurhanafi, Fauzan Adityo https://creativecommons.org/licenses/by-sa/4.0/
Sistem Monitoring Kualitas Air Berbasis IoT dengan ESP32 untuk Pengendalian Kualitas Lingkungan
Pendeteksian dan pemantauan air bersih sangat diperlukan untuk kehidupan sehari-hari makhluk hidup terutama air yang dikonsumsi. Pada artikel ini dibahas mengenai pembuatan alat pendeteksi kualitas air berdasarkan tingkat EC sebuah air. Di mana menurut WHO, tingkat EC yang baik untuk sebuah air dapat dikonsumsi adalah dibawah 400 µS/cm atau 0.4 mS/cm. Dalam hal ini digunakan komponen utama ESP32, sensor kekeruhan air TDS, sensor suhu DS18B20, dan LCD OLED 0.96 inci. Hasil pendeteksian dapat dimonitor melalui LCD yang sudah terintegrasi dan bisa juga secara nirkabel melalui website cloud Thingspeak, sehingga monitoring jarak jauh dapat dilakukan. Pengujian dilakukan pada suhu ruangan 32°C dan memakai air isi ulang. Dilakukan sebanyak 100 kali pembacaan dengan sensor suhu dan sensor TDS diletakkan secara bersamaan ke dalam cangkir berisi air isi ulang. Dengan melihat hasil pendeteksian pada bagan garis dalam website cloud Thingspeak, di mana data akan muncul sekali setiap 15 detik. Setelah 100 kali pembacaan didapat rata-rata suhu air isi ulang yang diuji adalah 28.63°C dan rata-rata EC sebesar 0.3006 mS/cm. Sehingga bisa disimpulkan bahwa alat berhasil mendeteksi kualitas air dan memberikan hasil bahwa air isi ulang tersebut layak untuk dikonsumsi.
Copyright (c) 2026 Sultan Mingkamanad, Dimas Kisworo, Della Puspitasari, Naufal Akmal Nugraha, Utari Lindawati, Rahmat Hidayat https://creativecommons.org/licenses/by-sa/4.0/
Smart Air Quality Guardian: Pengawasan Polusi Udara Berbasis ESP32 dengan Sensor Gas MQ-2 dan MQ-135
The campus area of Singaperbangsa Karawang University has increased air pollution levels due to the growth of urban activities. Daily activities such as traffic, construction, and industrial activities are indicators of increased emissions of air pollutants such as PM2.5, carbon monoxide (CO), and volatile organic compounds. The lack of real-time air pollution data can hamper efforts to identify sources of pollution and take appropriate action to reduce air pollution on campus. To overcome this, solutions are needed to reduce sustainable pollutant emissions. The application of the concept of sustainable solutions is poured into research through the design of an air pollution monitoring system called Smart Air Guardian. This supervision is carried out based on a microcontroller using the MQ-2 and MQ-135 gas sensor which will monitor the air in real-time. Gas sensors MQ-2 and MQ-135 use a multilayer sensor structure that has high sensitivity to CO and CO­2 content. This system is equipped with Bluetooth dual-mode capabilities and is integrated with IoT (Internet of Things) features so that it can process and display sensor data output through an LCD that easily detects air quality. The application of this system is used as an effort to monitor the air quality of the Singaperbangsa Karawang University campus to increase awareness about the importance of maintaining air quality.
Copyright (c) 2024 Rifki Fajar Nugraha, Fitria Nurul Husna, Sandi Sandi, Amanda Fairuz Syahla, Yogi Aldi Saputra, Rahmat Hidayat https://creativecommons.org/licenses/by-sa/4.0/
AeroSense Monitor Integrasi Sensor DHT11 dan MQ135 untuk Pemantauan Kualitas Udara Berbasis Arduino Uno
Clean air is a basic necessity, but air pollution in Indonesia's major cities has increased significantly. The lack of air quality monitoring facilities in certain areas leads to a lack of public awareness of air pollution levels, which can adversely affect health. As a solution, the development of AeroSenseMonitor, an Arduino Uno-based air quality monitoring tool with DHT11 and MQ135 sensors, is proposed. This tool is expected to provide accurate information on air quality, enabling people to take preventive measures and protect their health. By raising awareness of the importance of clean air, it is hoped that the AeroSenseMonitor can be the first step in addressing the negative impacts of air pollution in Indonesia.
Copyright (c) 2024 Muhammad Erik, Furkhon Nurdiyanto, Rahmat Hidayat https://creativecommons.org/licenses/by-sa/4.0/
Analisis Output Daya pada Sistem Pembersih Debu berbasis ESP32 terhadap Panel Surya
Pemanfaatan energi baru terbarukan semakin meningkat seiring dengan berkembangnya pemahaman masyarakat mengenai dampak lingkungan. Namun daerah karawang memiliki masalah krusial yaitu tingginya tingkat polusi udara dan debu yang sering kali melanda daerah ini. Polusi udara ini dapat menyebabkan penumpukan debu pada permukaan panel surya, yang selanjutnya mengurangi efisiensi konversi energi matahari menjadi listrik. Dampak polusi udara menghasilkan partikel-partikel kecil yang dapat menempel pada panel surya, memblokir cahaya matahari yang seharusnya diserap oleh sel surya. Akibatnya, produksi listrik dari panel surya menurun, mengurangi potensi energi terbarukan yang dihasilkan. Sistem SWAM (Smart Water Mist) dirancang untuk mencegah penumpukan debu pada panel surya yang disebabkan oleh polusi udara di daerah karawang. Dari hasil analisis yang dilakukan diperoleh daya rata rata sebelum dibersihkan memperoleh hasil 1,4898 Watt. Sedangkan rata rata sesudah dibersihkan menggunakan sistem SWAM mendapatkan hasil 3,2218 Watt. Berdasarkan analisa kurva perbandingan daya memiliki kesimpulan bahwa penggunaan sistem SWAM memiliki persentase perbandingan senilai 1,16 %. hasil penelitian ini diharapkan dapat menjadi masukan untuk menggunakan sistem SWAM pada proyek proyek PLTS.
Copyright (c) 2024 Mauludy Meilany, Dika Satria, Rianda Pusparina A, Arkan Dhia Saputro, Budiman Fasial Tanjung, Rahmat Hidayat https://creativecommons.org/licenses/by-sa/4.0/
Desain Prototype Robot Vacuum Cleaner Otomatis Berbasis Arduino Uno
The Arduino Uno-based Robot Vacuum Cleaner has been created as an innovative solution to deal with the problem of difficulty in cleaning the floor. Instead of traditional methods such as sweeping or using a large vacuum cleaner that require time and effort, this robot can be operated efficiently through Arduino Uno automatic control. By utilizing Arduino Uno, the robot is able to perform various functions automatically, including moving forward, backward, turning right, and turning left, while sucking up dirt independently. Through the test results, it was found that this robot vacuum cleaner can vacuum dust and garbage thoroughly. In addition, it can operate without error for 3 hours on a full battery, demonstrating reliable and efficient performance.
Copyright (c) 2024 Dhoni Hidayatullah, Diva Adesta Putra Afrizen, Maria Ulfa, Muhammad Fairuz Ivandyaputra, Sheva Maulana Ardy Syah Putra, Rahmat Hidayat https://creativecommons.org/licenses/by-sa/4.0/