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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 661 Documents
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Development of Higher Education Key Performance Indicator Monitoring System using Rapid Application Development Method Adi Widianto; Laurentinus Laurentinus
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3680

Abstract

Key Performance Indicators (KPIs) have a very essential role in higher education institutions in order to maintain the quality standards and to meet the requirements of the accreditation. But manual input and tracking typically results in data silos, data loss and delayed reporting. Furthermore, the system must be integrated with the subsystems that have already been built, which makes the development process longer and more complex. The purpose of this project is to design a university web-based KPI monitoring system by using Rapid Application Development (RAD) method to increase efficiency and reduce data loss. This choice is done because it allows a fast implementation in a real environment with an already existing subsystem. It started development in June 2025 and continued through August. The user input was looped as per criteria. The KPI tracking system has been implemented in one semester already. RAD has already proven to be the right methodology, as it achieved the goal of fast implementation and satisfied functional requirements.
Sistem Monitoring Listrik Dan Kesehatan Perangkat Videotron Jalan Tol Berbasis IoT: Studi Kasus: Jalan Tol Semarang-Solo PT Trans Marga Jateng Alvan Naufa Luthfi Firmansyah; Setiyo Adi Nugroho; Rudjiono Rudjiono
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3686

Abstract

Videotron pada jalan tol berfungsi sebagai media informasi visual untuk menyampaikan kondisi lalu lintas, himbauan keselamatan, serta peringatan dini kepada pengguna jalan. Namun, keandalan videotron sangat dipengaruhi oleh kestabilan pasokan listrik dan kondisi kesehatan perangkat. Gangguan kelistrikan seperti tegangan tidak stabil, pemadaman listrik, overheating, dan kelembaban tinggi dapat menyebabkan kerusakan perangkat serta terganggunya operasional videotron. Penelitian ini bertujuan merancang dan membangun sistem monitoring listrik dan kesehatan perangkat videotron berbasis Internet of Things (IoT) pada ruas Jalan Tol Semarang–Solo PT Trans Marga Jateng. Sistem menggunakan NodeMCU ESP8266 sebagai mikrokontroler utama yang terintegrasi dengan sensor PZEM-004T untuk monitoring parameter listrik dan sensor DHT22 untuk monitoring suhu serta kelembaban. Data dikirim secara real-time melalui jaringan internet menuju aplikasi Blynk & Telegram sebagai media monitoring dan notifikasi dini. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan model prototype. Hasil penelitian menunjukkan bahwa sistem mampu melakukan monitoring tegangan, arus, daya, energi listrik, suhu, dan kelembaban secara real-time serta memberikan notifikasi dini ketika terjadi anomali pada parameter tertentu. Sistem ini diharapkan dapat meningkatkan keandalan operasional videotron, mempercepat penanganan gangguan, dan mengurangi biaya pemeliharaan perangkat.  
Thermal Behavior Clustering of High-Voltage Electrical Equipment Using K-Means and Fuzzy C-Means Giovanni Dimas Prenata; Ahmad Ridho’i
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3700

Abstract

Thermal monitoring of high-voltage electrical equipment is an important aspect of maintaining the reliability and operational safety of electrical power systems. Conventional classification approaches generally require labeled data and are limited in representing transitional thermal conditions. Therefore, this study proposes an unsupervised learning approach using K-Means and Fuzzy C-Means (FCM) clustering methods to analyze thermal behavior patterns in high-voltage electrical equipment based on thermal image features. The proposed model utilizes two main features extracted from thermal images, namely the percentage of white regions (% white) and non-white regions (% non-white), where white regions represent high-temperature areas. A total of 12 thermal images were used in the clustering process. Experimental results showed that the K-Means algorithm converged after only 2 iterations, whereas FCM required 53 iterations to achieve convergence . Both methods successfully identified dominant thermal patterns corresponding to Normal, Warning, and Hazardous conditions. The most extreme thermal condition was observed in data sample 6, which had a white-region percentage of 83.2647% and was consistently classified as Hazardous by both K-Means and FCM . In addition, FCM demonstrated superior capability in representing transitional thermal conditions through membership values. Data sample 3, with a white-region percentage of 56.5476%, was classified as Hazardous by K-Means but categorized as Warning by FCM with a dominant membership value of 0.702543 . These results indicate that FCM provides more flexible thermal behavior representation compared with hard clustering approaches. Overall, the proposed clustering-based approach demonstrates significant potential for real-time thermal condition assessment and predictive maintenance applications in high-voltage electrical equipment.
Rancang Bangun Sistem Presensi Berbasis Internet of Things Pada PT. Roda Maju Bahagia Silvia Carmelita Febrianti; Edy Siswanto; Bagus Sudirman
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3724

Abstract

This research is intended to develop an Internet of Things (IoT)-based attendance system that enhances the efficiency of attendance data management at PT. Roda Maju Bahagia, where the previous process was still carried out manually. Human error during manual attendance management became one of the main issues, accompanied by inefficient data recording, obstacles in data retrieval and archiving, and limited accuracy in reporting. This research applied a qualitative method using a Research and Development (R&D) approach based on a prototype model. The attendance device/machine was built using a microcontroller circuit. Fingerprint reading results were then sent to a database, and notifications were sent to employees' Telegram accounts. All of this was done via a Wi-Fi or internet connection. The system featured automatic daily and monthly attendance reporting on a local website managed by HR administrators, utilizing attendance data obtained from the fingerprint device. Reports can be downloaded in Excel or PDF format, in tabular format, according to management and company needs. The results indicated that the system was able to record, process, and display attendance reports effectively. This system implementation has improved the efficiency, accuracy, and transparency of attendance records used for payroll calculations, thereby enhancing human resource management performance.
Penerapan Kecerdasan Buatan (AI) dalam Sistem Rekomendasi Produk Pada E-commerce Muhammad Zaki Mubarok; Eko Aziz Apriadi; Ribut Julianto; Muawan Bisri
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3732

Abstract

The rapid advancement of the digital era has fundamentally transformed the electronic commerce landscape, where the abundance of product options frequently causes information overload that hinders consumer decision-making. This study aims to examine the effectiveness of artificial intelligence implementation in product recommendation systems on e-commerce platforms while comparing the performance of various algorithms employed. The research adopted a comparative experimental quantitative approach using 10,000 transaction records, evaluating three primary algorithms, namely Collaborative Filtering, Content-Based Filtering, and Hybrid Filtering, through Precision, Recall, F1-Score, and RMSE metrics. Findings revealed that AI-based systems achieved an average recommendation relevance rate of 84.6%, substantially surpassing conventional systems at only 51.3%. Among the three algorithms tested, Hybrid Filtering demonstrated the highest performance with an F1-Score of 87.9% and the lowest RMSE of 0.231. The hybrid approach also proved most resilient under cold-start and data sparsity conditions compared to other algorithms. This study concludes that integrating artificial intelligence, particularly through a hybrid algorithm, represents the most optimal strategy for improving product recommendation personalization quality and driving sales conversion on large-scale e-commerce platforms.
OPTIMALISASI ALGORITMA SUPPORT VECTOR MACHINE UNTUK MEMPREDIKSI TES SAMAPTA PERSONEL KODIM 0713 BREBES Muhammad Agam Tamlica; Nur Ariesanto Ramdhan; Otong Saeful Bachri
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3754

Abstract

The Samapta Test is a component of the physical fitness assessment that is mandatory for all military personnel, including personnel of the 0713 Brebes Military District Command (Kodim), as an indicator of physical readiness to carry out duties. The high failure rate of this test encourages the need for a prediction system capable of identifying personnel at risk of failure early. This study aims to build and optimize a prediction model for passing the Samapta Test using the Support Vector Machine (SVM) algorithm. Optimization is carried out through hyperparameter tuning techniques using the Grid Search Cross-Validation method to obtain the optimal combination of kernel parameters, C values, and gamma values. The data used comes from a summary of the Samapta Test results of Kodim 0713 Brebes personnel, including attributes such as age, running, push-up, sit-up, pull-up, and swimming scores. The research stages include data collection, pre-processing, feature selection, SVM model development, parameter optimization, and model performance evaluation using accuracy, precision, recall, and F1-score metrics. The results of the study show that the optimized SVM model is able to significantly increase prediction accuracy compared to the SVM model without optimization, so that it can be used as a decision-making tool for units in designing more targeted and effective personnel physical development programs.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN AYAM PETELUR MENGGUNAKAN METODE SAW (STUDI KASUS BUMDES KARANGASEM-CIREBON): Studi Kasus Bumdes Karangasem-Cirebon Trisena Pramuja; Otong Saeful Bachri; Agyztia Premana
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3755

Abstract

Pemilihan jenis ayam petelur yang tepat sangat penting untuk meningkatkan produktivitas peternakan BUMDes Desa Karangasem. Proses penilaian yang masih manual cenderung subjektif sehingga diperlukan Sistem Pendukung Keputusan menggunakan metode Simple Additive Weighting (SAW). Penelitian ini menggunakan kriteria produktivitas telur, kesehatan ayam, konsumsi pakan, daya tahan tubuh, adaptasi lingkungan, kualitas telur, dan tingkat kematian ayam dengan alternatif Ras Brown, KUB, Leghorn, Lohmann Brown, Hy-Line, dan Elba. Sistem berbasis website dibangun menggunakan PHP dan MySQL. Hasil penelitian menunjukkan bahwa metode SAW mampu memberikan penilaian dan perangkingan secara objektif, dengan ayam Elba memperoleh nilai tertinggi sebesar 0.9671 sehingga direkomendasikan sebagai jenis ayam petelur terbaik.  
PREDIKSI PENJUALAN SEPEDA MOTOR TERLARIS DI ASTRA HONDA BREBES MENGGUNAKANALGORITMA NAIVE BAYES Luthfi Ardyansyah; Nur Ariesanto Ramdhan; Puji wahyuningsih
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3756

Abstract

Penelitian ini bertujuan untuk menerapkan metode Support Vector Machine (SVM) dalam memprediksi tingkat penjualan sepeda motor di Astra Honda Brebes menggunakan data historis penjualan periode 2020–2025. Dataset penelitian terdiri dari 200 data penjualan yang memiliki atribut model motor, tahun kendaraan, harga, jenis transmisi, jenis kendaraan, kapasitas mesin, dan status penjualan. Proses penelitian meliputi preprocessing data, pembagian data training dan testing, proses klasifikasi menggunakan kernel RBF, serta evaluasi model menggunakan confusion matrix, accuracy, precision, recall, F1-score, AUC, dan cross validation. Hasil penelitian menunjukkan bahwa metode SVM mampu melakukan klasifikasi tingkat penjualan kendaraan dengan performa yang baik. Nilai accuracy yang diperoleh sebesar 89.50%, precision 87.20%, recall 85.40%, F1-score 86.29%, AUC sebesar 0.91, serta cross validation accuracy sebesar 91.20%. Hasil tersebut menunjukkan bahwa metode SVM memiliki kemampuan yang baik dalam membedakan kategori kendaraan laris dan kurang laris. Penelitian ini diharapkan dapat membantu pihak dealer dalam menentukan strategi pemasaran, pengelolaan stok kendaraan, dan pengambilan keputusan secara lebih efektif, objektif, dan berbasis data.
Implementasi sistem IoT untuk monitoring dan deteksi dini kerusakan bearing motor induksi Yuli Leksana; Setiyo Adi Nugroho; Rudjiono Rudjiono
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3762

Abstract

Induction motors are essential components in industrial systems, where bearing failures can cause increased vibration, overheating, reduced performance, and unexpected production downtime. Conventional monitoring methods are generally manual and periodic, limiting the ability to detect early signs of failure in real time. This study aims to develop an Internet of Things (IoT)-based monitoring and early fault detection system for induction motor bearings using a DS18B20 temperature sensor, ADXL345 vibration sensor, ESP32 microcontroller, Blynk cloud platform, and a risk score decision method. The research employed a research and development (R&D) approach with a prototyping model to design and evaluate the proposed system. Experimental results showed that the DS18B20 sensor was able to detect temperature changes properly, while the ADXL345 sensor successfully measured vibration changes with readings relatively close to reference instruments. The Blynk platform successfully displayed temperature and vibration monitoring data in real time, although minor delays were observed due to network conditions. System testing under four simulated operating conditions confirmed that the risk score method successfully classified motor conditions into normal, warning, danger, and shutdown categories according to predefined thresholds. The developed system demonstrates the potential to support continuous monitoring and early fault detection of induction motor bearings, contributing to more effective preventive maintenance in industrial applications.
Analisis Kualitas Layanan Sistem Informasi Transportasi LRT Kota Palembang Menggunakan ITIL 4 Studi Literatur Ahmad Subarkah; M. Dicky; Salman Alfahiri; Eriene Dheanda Absharina
Elkom: Jurnal Elektronika dan Komputer Vol. 19 No. 1 (2026): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v19i1.3804

Abstract

The development of information technology drives the improvement of service quality in various sectors, including public transportation. Technology-based transportation services such as the Palembang LRT utilize information systems in their operations, such as electronic ticketing systems and the delivery of travel information to users, making the quality of information technology services an important factor in determining user satisfaction as well as the overall success of the service. analyzing the service quality of the information system at Palembang LRT using the ITIL 4 framework. The method used is a literature review by examining various previous studies that are relevant within the last five years. shows that the implementation of ITIL 4 is able to improve the quality of information technology services, especially through the practices of incident management, problem management, and service request management. The analysis also shows that the aspects of reliability, responsiveness, availability, and user satisfaction are the main indicators in assessing IT service quality. Nevertheless, there are still potential issues such as disruptions in the ticket system and delays in information delivery that can affect the user experience. Therefore, it is recommended to implement ITIL 4 gradually, enhance system monitoring, and optimize the service desk to improve IT service quality. Thus, it is expected that LRT Palembang services can provide a better experience for users and increase public trust in technology-based public transportation.

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