cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Nuris Dwi Setiawan
Contact Email
elkom@stekom.ac.id
Phone
+6285641386859
Journal Mail Official
elkom@stekom.ac.id
Editorial Address
Jalan Majapahit No 605 Semarang
Location
Kota semarang,
Jawa tengah
INDONESIA
Elkom: Jurnal Elektronika dan Komputer
Published by Universitas Sains Dan Teknologi Komputer
ISSN : 19070012     EISSN : 27145417     DOI : https://doi.org/10.51903/elkom.v14i1
Core Subject : Education,
Education
Elkom : Jurnal Elektronika dan Komputer merupakan Jurnal yang diterbitkan oleh SEKOLAH TINGGI ELEKTRONIKA DAN KOMPUTER (STEKOM). Jurnal ini terbit 2 kali dalam setahun yaitu pada bulan Juli dan Desember. Misi dari Jurnal ELKOM adalah untuk menyebarluaskan, mengembangkan dan menfasilitasi hasil penelitian mengenai Ilmu bidang informatika, sebagai media bagi para dosen, guru, peneliti dan para praktisi dalam bidang teknologi informasi dari seluruh Indonesia, dalam melakukan pertukaran informasi tentang hasil-hasil penelitian terbaru yang telah dilakukan.
Arjuna Subject : -
Articles 631 Documents
 60   61   62   63   64 
Perancangan Knowledge Management System Sebagai Media Berbagi Pengetahuan Mahasiswa Dengan Metode Knowledge Management System Lifecycle Sri Anardani; Muhammad Salimy Ahsan; Crismantoro Budisaputro; Muh Nur Luthfi Azis
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3277

Abstract

Knowledge must be managed effectively to facilitate transfer between individuals, groups, and organizations. The Informatics Engineering study program currently lacks a system for knowledge management. Currently, the study program facilitates offline discussion forums for the sharing of knowledge gained by lecturers and students. These offline discussion forums require significant costs, time, and space, often resulting in delays in knowledge sharing. This research focused on the analysis and design of a Knowledge Management System to meet the needs of Informatics Engineering students at Universitas PGRI Madiun. The system development method used was the Knowledge Management System Lifecycle (KMSL). In this study, the TIF KMS system using the KMSL method has been successfully built. The results of testing using the Blackbox Testing method showed that 5 scenarios and 18 cases were successfully executed as expected with a 100% success rate. Based on the system test results, the TIF KMS is ready to proceed to the implementation stage. Future implementation can be done by developing additional features such as a digital library
Analisis Hasil Pengukuran Flowmeter Oksigen Bayi Produk Dalam Negeri Dan Produk Luar Negeri Dengan Metode Uncertainty Dan Uji Mann-Whitney Rustiana Rustiana; Eka Nuryanto Budisusila
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3279

Abstract

Oxygen is vital therapy where delivery accuracy is crucial, especially for infant patients, to ensure treatment effectiveness and prevent the risks of hypoxia or toxicity. With the implementation of the mandatory Domestic Product Utilization Policy (TKDN+BMP ≥ 40%), evaluating the quality of local products has become an urgent necessity. This study aims to test and analyze the quality and accuracy of domestically produced infant oxygen flowmeters compared to an imported product. The method used was experimental testing, measuring three brands of domestic products and one brand of foreign product at flow rate settings of 0.5, 1, 1.5, and 2 liters per minute (LPM). Each setting point was measured 10 times using a standardized calibrator to ensure data reliability. The measurement results were analyzed to identify the deviation level of each product. The findings of this study are expected to provide an objective conclusion on the quality equivalence of domestic products with imported ones and to identify which product has the lowest deviation rate. This can serve as scientific consideration for hospitals in selecting high-quality infant oxygen flowmeters, thereby supporting the domestic product policy.
Penerapan Metode Design Thinking Dalam Perancangan UI/UX Sistem Pencatatan dan Pemantauan Kekeruhan Air Berbasis Website Efansa, Chika; Chika Efansa; Pradita Eko Prasetyo Utomo; Muhammad Razi A
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3286

Abstract

PAMTIRTA Tempino is an institution that provides clean water services in the Tempino area. The process of recording water use and monitoring water turbidity is still done manually, making it prone to recording errors and making it difficult to monitor the water quality distributed to the community. This study aims to design a website-based water turbidity recording and monitoring system by focusing on User Interface (UI) and User Experience (UX) aspects using the Design Thinking method. The research follows five stages of Design Thinking: empathize, define, ideate, prototype, and test. Data collection involves observation and in-depth interviews with PAMTIRTA officers. The results include a design with key features such as digital water meter recording, turbidity monitoring dashboards, and complaint services. The prototype was tested using Maze and the System Usability Scale (SUS), achieving a score of 80.1 and falling into the "Good" category (grade B). These results demonstrate that the UI/UX design effectively provides an easy-to-understand, operationally suitable, and efficient solution for PAMTIRTA Tempino's water recording and turbidity monitoring needs. This design offers a ready-to-implement solution to improve the efficiency, accuracy, and quality of clean water services in the Tempino area.  
Rancangan Bangun Pembuatan Charger Hp Tenaga Batre Dan Gerak Dinamo Citra Cahya Rizqina; Nurhamidah Nurhamidah; Rizki Agung Maulidin; Jamiatul Khairunnisa Putri
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3291

Abstract

Keterbatasan akses sumber listrik di wilayah terpencil atau situasi darurat sering kali menghambat ketersediaan daya bagi perangkat telekomunikasi. Penelitian ini bertujuan untuk merancang bangun alat pengisi daya (charger) hibrida yang mengintegrasikan penyimpanan energi kimia baterai dan konversi energi mekanik dinamo sebagai solusi alternatif. Metode penelitian menggunakan Research and Development (R&D) dengan pendekatan deskriptif kuantitatif untuk menguji stabilitas tegangan dan efektivitas pengisian daya. Prototipe dirancang menggunakan baterai 18650, dinamo 12V, dan modul regulator tegangan untuk menstabilkan luaran. Hasil pengujian menunjukkan bahwa integrasi regulator berhasil menstabilkan fluktuasi tegangan dinamo (rentang 5–12V) menjadi tegangan konstan 5V yang aman bagi ponsel. Pengujian efektivitas selama 15 menit menunjukkan kenaikan kapasitas baterai ponsel sebesar 5–10% pada mode baterai dan 2–4% pada mode dinamo. Disimpulkan bahwa meskipun mode dinamo memiliki efisiensi yang lebih rendah akibat variabilitas putaran manual, alat ini layak diimplementasikan sebagai solusi catu daya darurat (emergency kit) yang portabel, ekonomis, dan memiliki redundansi energi yang andal.
Rancang Bangun Prototype Sistem Monitoring dan Kontrol Suhu dan Kelembaban pada Multi-Kubikel Berbasis IoT Oktavia, Putri Eka; Auliq, Muhammad A'an; Fitriana
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3292

Abstract

Suhu dan kelembaban merupakan parameter lingkungan yang harus dijaga pada ruang kubikel untuk memastikan peralatan distribusi listrik tetap bekerja secara optimal. Pada multi-kubikel, perbedaan fungsi dan beban menyebabkan karakteristik suhu dan kelembaban pada tiap ruang kubikel tidak sama, sehingga pemantauan secara manual menjadi kurang efektif dan efisien. Penelitian ini bertujuan untuk merancang dan membangun prototype sistem monitoring dan kontrol suhu-kelembaban pada multi-kubikel berbasis Internet of Things (IoT) yang terdiri dari tiga buah kubikel. Sistem ini menggunakan ESP8266 sebagai mikrokontroler utama dan sensor DHT20 sebagai sensor suhu dan kelembaban yang masing-masing dipasang pada kubikel dengan kondisi lingkungan berbeda. Sistem dilengkapi dengan aktuator kipas dan lampu, serta notifikasi real-time melalui LCD dan Telegram. Meskipun kontrol dan monitoring dilakukan secara terpisah pada tiap kubikel, notifikasi kondisi seluruh kubikel terintegrasi pada satu kanal Telegram yang sama. Pengujian kinerja sistem dengan memberikan variasi suhu dan kelembaban yang berbeda untuk tiap kubikel. Kubikel 1 diberi kondisi normal (suhu 35°C-40°C dan kelembaban 50%-70%), kubikel 2 diberi kondisi overheat (suhu di atas 40°C), sedangkan kubikel 3 diberi kondisi overhumidity (kelembaban > 70%). Hasil pengujian menunjukkan sistem mampu melakukan kontrol suhu dan kelembaban dalam ruang multi-kubikel serta mengirimkan notifikasi melalui Telegram dengan tingkat keberhasilan 100% dan rata-rata delay 5,6 detik.
Kerangka Hibrida Apriori–MST untuk Mengungkap Struktur Dasar Pola Pembelian Konsumen Marta Dinata, Riadi; Kurniawan Atmadja; Marhaeni Mahaeni; Lely Mustika
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3300

Abstract

Traditional association rule analysis is effective at uncovering co-purchase patterns but fails to provide a global structural view of the market, which often results in fragmented and isolated insights. This study proposes a hybrid framework that integrates the Apriori algorithm with a Minimum Spanning Tree (MST) in order to validate and contextualize association rules within a single structural backbone. Transaction data from a retail store are transformed into a weighted, undirected product graph using an inverse-support function, and an MST is then extracted to represent the market backbone, while frequent itemsets and strong rules are obtained using Apriori. Experimental results on 236 multi-item transactions show that the MST backbone comprises 10 products and 9 fundamental links, with 66.67% of these links being confirmed by strong association rules, indicating a substantial coherence between statistical and structural evidence. The proposed model identifies 41 Apriori patterns that can be embedded in the MST and ranks them using a new metric, Structural Distance, which enables the categorization of Core Patterns, Bridge Patterns, and Complex Patterns according to their structural tightness. This hybrid perspective distinguishes dense, strategically meaningful bundles from anomalous but frequent combinations that are structurally peripheral, thereby offering a more holistic and actionable alternative to conventional Market Basket Analysis. The validated framework can support various applications, including store layout optimization, cross-selling strategies, and the design of path-based recommender systems, and it opens avenues for future extensions based on dynamic graphs and Graph Neural Networks.
Analisis Performansi Pendekatan Machine Learning Pada Deteksi Penyakit Daun Tanaman Kopi Purnomo, Rosyana Fitria; Yodhi Yuniarthe; Hilda Dwi Yunita; Fatimah Fahurian; Ahmad Ikhwan
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3302

Abstract

Detection and identification of plant diseases is critical to the success and efficiency of agricultural production. Plant disease outbreaks are becoming more frequent throughout the world, and the presence of these diseases in cultivated plants has a significant impact on productivity. Therefore, researchers are focusing on developing effective and reliable plant disease detection methods. Thus, farmers can take advantage of early detection of this disease to minimize future losses. This article discusses machine learning approaches as well as decision trees, K-nearest neighbors, naive Bayes, support vector machines (SVM), and random forests for detecting coffee leaf diseases using leaf images. The above-mentioned classifications were researched and compared to determine the most suitable plant disease prediction model with the highest accuracy. Compared with other classification algorithms, the SVM algorithm achieves the highest accuracy of 99.75%. All the models trained above will be used by farmers to quickly identify and classify new diseases in images as a prevention strategy. As a preventive measure, farmers can detect and classify new diseases in images early.
Klasifikasi Huruf Hijaiyah Berbasis Citra Digital Menggunakan Metode Convolutional Neural Network (CNN) Firyal Nabila Ulya H.M; Bambang Irawan; Abdul Khamid
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3308

Abstract

Hijaiyah letters have varying shapes, and some of them are very similar, often causing errors in the manual character recognition process. This study aims to classify Hijaiyah letters based on digital images using the Convolutional Neural Network (CNN) method. This method was used in this study with a dataset consisting of 28 letter classes and a total of 4,480 images obtained from various public sources and private data. All images underwent a preprocessing stage that included labeling, resizing, normalization, and augmentation, then were divided into three parts, namely training data, validation data, and test data with a ratio of 70:20:10. The training process was carried out using the Python programming language with the help of the TensorFlow and Keras libraries on the Google Colab platform. The test results showed that the CNN model achieved an accuracy of 97.10%, with an average precision, recall, and F1-score of 0.97, respectively. Classification errors only occurred in letters that had similar shapes, such as Syin and Sin. Based on these results, the CNN method proved to be effective, efficient, and accurate in recognizing Hijaiyah letter image patterns, so it can be used as a basis for developing classification models with higher accuracy in the future.  
Klasifikasi Jenis Sampah Organik Dan Anorganik Menggunakan Convutional Neural Network Berbasis Citra Digital Nova Eliza; Bambang Irawan; Abdul Khamid
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3309

Abstract

Waste has become a serious environmental problem in Indonesia, which continues to increase along with population growth. The issue of waste management poses serious challenges for the environment, especially in the process of separating organic and inorganic waste. In the field of computer vision, recognising the type and shape of waste through camera images remains a challenge due to variations in shape, colour, and complex lighting conditions. Therefore, this problem utilises Deep Learning technology, which is expected to be widely applied in Indonesia, especially in large cities with high waste volumes. This study aims to distinguish between organic and inorganic waste using the Convolutional Neural Network (CNN) method based on digital images. The developed CNN model was trained to recognise the visual patterns of each type of waste and tested to measure its accuracy. The test results show that the CNN-based classification system is capable of achieving an accuracy rate of 95%, thus proving the effectiveness of this method in supporting artificial intelligence-based automatic waste sorting systems.
Enkripsi Homomorfik Parsial untuk Mendukung Pencarian Data Terenkripsi pada Basis Data Relasional Niko, Niko Surya Atmaja; Surya Atmaja, Niko; Muhammad Khoiruddin Harahap; Sahyunan Harahap
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3312

Abstract

Relational databases store information in interconnected tables and are widely used for data management and retrieval. However, in certain environments, the original values stored in a relational database cannot be exposed during data retrieval. This limitation creates a challenge because common encryption methods only transform data for storage and do not support mathematical operations needed for value matching. Partially Homomorphic Encryption is a cryptographic approach that allows specific mathematical operations to be performed directly on transformed data without restoring it to its original form. This study proposes the use of Partially Homomorphic Encryption to enable value-based data retrieval while keeping all stored values in their transformed form throughout the entire process. The method relies on homomorphic properties that allow mathematical comparison to be conducted on encrypted data, making the retrieval process possible without revealing the original values. The results show that this approach can perform data retrieval operations in a relational database while preserving the transformed structure of the stored data. The proposed method offers an alternative for environments that require data retrieval without exposing original values and demonstrates the potential of homomorphic techniques in supporting secure and functional data processing in relational database contexts.

Page 62 of 64 | Total Record : 631

 60   61   62   63   64 

Filter by Year

2007 2025


Reset
Filter By Issues
All Issue Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer Vol. 18 No. 1 (2025): Juli : Jurnal Elektronika dan Komputer Vol. 17 No. 2 (2024): Desember : Jurnal Elektronika dan Komputer Vol. 17 No. 1 (2024): Juli : Jurnal Elektronika dan Komputer Vol 17 No 1 (2024): Juli : Jurnal Elektronika dan Komputer Vol. 16 No. 2 (2023): Desember : Jurnal Elektronika dan Komputer Vol 16 No 2 (2023): Desember : Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer Vol 16 No 1 (2023): Juli : Jurnal Elektronika dan Komputer Vol 15 No 2 (2022): Desember : Jurnal Elektronika dan Komputer Vol. 15 No. 2 (2022): Desember : Jurnal Elektronika dan Komputer Vol 15 No 1 (2022): Juli : Jurnal Elektronika dan Komputer Vol. 15 No. 1 (2022): Juli : Jurnal Elektronika dan Komputer Vol 14 No 2 (2021): Desember: Jurnal Elektronika dan Komputer Vol 14 No 1 (2021): Juli: Jurnal Elektronika dan Komputer Vol 13 No 2 (2020): Desember: Jurnal Elektronika dan Komputer Vol 13 No 1 (2020): Juli: Jurnal Elektronika dan Komputer Vol 12 No 2 (2019): Desember: Jurnal Elektronika dan Komputer Vol 12, No 1 (2019) Vol 12 No 1 (2019): Juli: Jurnal Elektronika dan Komputer Vol 11 No 2 (2018): Desember: Jurnal Elektronika dan Komputer Vol 11, No 1 (2018) Vol 11 No 1 (2018): Juli: Jurnal Elektronika dan Komputer Vol 10, No 1 (2017) Vol 9, No 1 (2016) Vol 9, No 1 (2016) Vol 8, No 1 (2015) Vol 8, No 1 (2015) Vol 7, No 2 (2014) Vol 7, No 2 (2014) Vol 6, No 2 (2013) Vol 6, No 2 (2013) Vol 5, No 2 (2012) Vol 4, No 1 (2007) More Issue