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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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Sistem Pemantauan Konsumsi Energi Listrik Rumah Tangga Untuk Validasi Tagihan Listrik Pelanggan Egi Hergiyan; Muhammad Dzaky; Nadira Desti P.P
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.v19i1.3805

Abstract

Current conventional electrical energy recording systems have limitations in accurately monitoring power consumption fluctuations in real-time. On the other hand, Internet of Things (IoT)-based monitoring solutions are often vulnerable to the risk of data loss during internet connection disruptions on the user's end. This study aims to design a single-phase electrical power consumption monitoring system as a comparison instrument for State Electricity Company (PLN) bills that is robust against network disturbances. The proposed solution is a system based on the ESP32 microcontroller and PZEM-004T sensor, implementing a dual (hybrid) logging method. This system utilizes an SD Card as an independent local storage medium and Google Spreadsheets as a cloud database, which is subsequently visualized through a Grafana dashboard. Processing is managed in parallel using FreeRTOS to prevent program interruptions. Calibration results demonstrate an exceptionally high level of system precision, with a coefficient of determination ($R^2$) of 0.9997 for voltage and 0.9999 for current against standard measuring instruments. Transmission reliability testing over 30 days recorded a 0% data loss rate from a total of 43,200 samples. Furthermore, direct validation against PLN postpaid bills shows a high degree of alignment, where the system's accumulated monthly consumption of 144.541 kWh differed by only 0.541 kWh from the official PLN meter reading (144 kWh). This system is proven effective in preventing data loss while simultaneously functioning as a credible and transparent actual bill comparison instrument for customers.
Audit Sistem Pencahayaan pada Gedung Sekolah B Politeknik Negeri Semarang Pangestuningtyas Diah Larasati; Adeguna Ridlo Pramurti; Adi Wasono; Lilik Eko Nuryanto; Septiantar Tebe Nursaputro; Muhammad Bhayu Bramantyo
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.v19i1.3817

Abstract

School Building B of Politeknik Negeri Semarang (POLINES) is an intensively used academic facility that requires a comprehensive evaluation of its lighting energy consumption. A lighting system energy audit was conducted using a quantitative descriptive method through direct measurements with a lux meter and laser meter. The results indicate that only 6 out of 41 rooms met the minimum illuminance standard of SNI 6197:2020, while 5 rooms exceeded the maximum LPD limit of 7.53 W/m², primarily due to the use of inappropriate lamp types and sizes relative to room dimensions, as well as performance degradation from aging lamps. Replacing conventional lamps with LED technology and adjusting the number of luminaires based on illuminance requirement calculations are recommended as corrective measures, which are proven to reduce LPD values below the maximum standard limit while improving visual comfort for building occupants.
Rancang Bangun Sistem IoT MCB Kantor Dengan Auto Cut-off Untuk Efisiensi Energi Agus Windarto; Unang Achlison; Iman Saufik Suasana
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.v19i1.3825

Abstract

Penggunaan energi listrik di lingkungan perkantoran yang belum terkelola secara optimal sering menimbulkan pemborosan, khususnya pada lampu dan pendingin ruangan yang tetap aktif di luar jam operasional. Penelitian ini bertujuan merancang dan membangun sistem berbasis Internet of Things menggunakan ESP32 untuk pengendalian listrik kantor dengan mekanisme auto cut-off berbasis waktu melalui jalur setelah Miniature Circuit Breaker. Sistem mengendalikan beban lampu dan pendingin ruangan secara terpusat menggunakan relay sebagai aktuator, dilengkapi sinkronisasi waktu melalui Network Time Protocol, Real Time Clock DS3231 sebagai sumber waktu cadangan saat offline, sensor DHT11, tampilan OLED, tombol input, serta dashboard web berbasis Laravel untuk pemantauan dan kontrol dua arah. Metode penelitian menggunakan pendekatan rancang bangun dengan tahapan analisis kebutuhan, perancangan perangkat keras dan perangkat lunak, implementasi, integrasi, serta pengujian menggunakan black box testing, integration testing, dan endurance testing. Hasil pengujian menunjukkan bahwa sistem mampu mengaktifkan dan menonaktifkan relay sesuai jadwal operasional, membedakan hari kerja dan hari libur nasional, tetap berjalan pada kondisi tanpa internet, serta menyediakan override mode untuk kendali manual. Sistem yang dikembangkan dapat mendukung efisiensi penggunaan energi listrik dan penerapan konsep smart office berbasis Internet of Things.
Perancangan Karakter Virtual 2D Berbasis Artificial Intelligence sebagai Media Promosi untuk Mendukung Keterbukaan Informasi Publik di Universitas Jambi Kevin Kifeda; Daniel Arsa; Mochammad Arief Hermawan Sutoyo
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.v19i1.3845

Abstract

Penyampaian informasi publik di Universitas Jambi saat ini masih bersifat satu arah melalui media sosial tanpa mekanisme respons otomatis, sehingga belum mampu memenuhi kebutuhan interaksi pengguna secara optimal. Penelitian ini bertujuan merancang dan mengembangkan karakter virtual 2D berbasis Artificial Intelligence (AI) bernama JUVIO (Jambi University Virtual Information Officer) sebagai media promosi interaktif guna mendukung keterbukaan informasi publik di Universitas Jambi. Pengembangan sistem dilaksanakan menggunakan metodologi Waterfall melalui tahapan requirement analysis, design, implementation, testing, dan maintenance. Sistem dibangun menggunakan framework Laravel dengan karakter virtual dirender melalui Live2D Cubism SDK dan PixiJS, serta mekanisme kecerdasan buatan berbasis Retrieval-Augmented Generation (RAG) menggunakan model LLM Gemini 2.0 Flash Lite melalui LiteLLM, dilengkapi fitur text-to-speech menggunakan edge-tts dan WebSpeech API. Pengujian fungsionalitas menggunakan metode Black Box Testing dengan teknik Equivalence Partitioning melibatkan 4 penguji dengan total 88 skenario, menghasilkan persentase keberhasilan 100% dan persentase kegagalan 0%. Hasil ini membuktikan bahwa sistem JUVIO layak sebagai media promosi interaktif berbasis karakter virtual 2D dan AI dalam mendukung keterbukaan informasi publik di Universitas Jambi.
Sistem Pendukung Keputusan Rekomendasi Laptop Berdasarkan Kebutuhan Mahasiswa Berbasis Android Kreshna Ady Saputra; Yulia Darmi; Pigar Apronoverel; Bintang Fardiansyah; Rendy Kusadi Novas Putra; M. Davindra Putra Mahesa
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.v19i1.3900

Abstract

The increasing variety of laptop products with diverse specifications and prices has made the selection process more challenging for students. Different academic activities such as coding, gaming, graphic design and editing, 3D engineering modeling, and multitasking require distinct hardware specifications, making it difficult to determine the most suitable laptop manually. This study aims to develop an Android-based Decision Support System (DSS) for laptop recommendations using the Simple Additive Weighting (SAW) method. The system evaluated 25 laptop alternatives based on nine evaluation criteria, namely price, RAM, CPU, GPU, SSD, battery, device weight, screen size, and body material. The SAW method was implemented through decision matrix construction, normalization, weighted preference calculation, and alternative ranking. The results showed that different user profiles produced different recommendation outcomes. The ASUS Zenbook 14 OLED UM3402YA achieved the highest preference value in the coding and multitasking categories, while the Nitro V obtained the highest score in the gaming, graphic design and editing, and 3D engineering modeling categories. The developed Android application provides users with a practical and flexible tool for obtaining laptop recommendations according to their specific needs. The findings indicate that the SAW method is effective in generating objective and personalized laptop recommendations through a multi-criteria decision-making approach.
Optimasi Algoritma XGBoost Berbasis SMOTE untuk Mengidentifikasi Faktor Logistik Pemicu Pembatalan Pesanan E-commerce Arif Fitra Setyawan; Thomas Tri Wibowo; Intan Laily Muflikhah; Muhammad Bhayu Bramantyo
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.v19i1.3913

Abstract

Unilateral order cancellation by consumers is a major operational challenge in the Indonesian e-commerce industry, directly impacting supply chain inefficiency and inflating logistics costs. Computational modeling to predict this risk often faces hurdles such as class imbalance and vulnerability to data leakage. This study proposes an optimization of the Extreme Gradient Boosting (XGBoost) algorithm integrated with the Synthetic Minority Over-sampling Technique (SMOTE) using a multi-scenario feature analysis approach. The dataset used comprises real transaction records from a major e-commerce platform. Experiments were designed in two scenarios: Scenario 1 included all transactional features, while Scenario 2 excluded the dominant financial feature (Total Pembayaran) to test the model's pure dependency on pre-finalization variables. The test results showed that Scenario 1 yielded a pseudo-accuracy of 99.50% due to data leakage. After reconstruction in Scenario 2, the SMOTE-based XGBoost model produced a stable real performance with an Accuracy Score of 83.96% and an Area Under ROC (AUC) of 86,98%. Through Feature Importance analysis, this study successfully revealed that pure logistics factors, specifically "Ongkos Kirim Dibayar oleh Pembeli" (Shipping Fee Paid by Buyer) with an absolute importance weight of 77.10%, serve as the primary predictor and driver behind consumer order cancellations. These findings provide tactical contributions for e-commerce decision-makers in formulating shipping cost strategies and mitigating early operational risks.
ANALISIS PENERAPAN METODE WEIGHTED PRODUCT WP UNTUK PENILAIAN KELAYAKAN KREDIT KENDARAAN BERMOTOR Damal Lihan; Budi Santoso; Andri Krisna Wijaya
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.v19i1.3923

Abstract

In the credit approval process, prospective customers are first surveyed, after which the Credit Analyst determines whether they are eligible to receive credit. A Credit Analyst is required to work quickly and accurately when analyzing the large number of incoming credit applications. As a result, the possibility of human error cannot be ignored, such as calculation errors, data misinterpretation, and other mistakes. Therefore, to support the decision-making process in determining customer creditworthiness, a computer-based system is needed to facilitate data analysis, evaluate credit applicant criteria, and process data into meaningful information for making decisions regarding semi-structured problems. A Decision Support System (DSS) is an appropriate solution to assist in the selection of motor vehicle credit applicants. The system is designed using the Weighted Product (WP) method, which is one of the methods in Fuzzy Multiple Attribute Decision Making (FMADM). The WP method was chosen because the criteria weighting calculations are relatively simple and not overly complex. The proposed system is expected to assist in the selection of credit applicants, thereby accelerating the credit evaluation process and reducing errors in determining customer creditworthiness. With the implementation of this system, Credit Analysts can more easily identify customers who are eligible to receive motor vehicle credit. In addition, the calculation process for determining the most suitable customers becomes easier and faster. The system also helps management reduce difficulties in selecting the best customers by considering and representing each evaluated criterion, resulting in accurate and reliable decisions.
DETEKSI SAMPAH ORGANIK DAN ANORGANIK DI PERMUKAAN SUNGAI DELI MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Angelita Anggi Sean Manuella Limbong; Arnita Arnita
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.v19i1.3941

Abstract

River pollution caused by waste remains a serious environmental issue, particularly in urban areas such as the Deli River. The process of monitoring and identifying waste types is still largely performed manually, making it inefficient and ineffective. Therefore, this study aims to develop an image-based classification system for organic and inorganic waste using the Convolutional Neural Network (CNN) method with the MobileNetV2 architecture. The dataset used in this research consists of surface images of the Deli River captured using a drone camera. The images were processed through preprocessing and data augmentation stages, followed by data splitting, model training, and testing. The CNN model was designed to classify two waste categories, namely organic and inorganic waste. Model performance was evaluated using a confusion matrix with accuracy, precision, recall, and F1-score as evaluation metrics. The results indicate that the proposed CNN model is able to classify organic and inorganic waste effectively. The system achieved an accuracy of 94%, a precision of 92%, a recall of 98%, and an F1-score of 95%. These results demonstrate that the model has excellent performance and reliability in identifying waste characteristics based on shape, color, and texture features from river surface images. Therefore, the developed system has the potential to be implemented as an automatic and sustainable tool for monitoring the cleanliness of the Deli River.
Real-Time Human Detection and Face Recognition System Using CCTV Stream and Localhost-Based Monitoring Dashboard M. A. Racka Eratama; Ade Silvia Handayani; Aryanti Aryanti; Asriyadi Asriyadi
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.v19i1.3954

Abstract

This study presents a real-time human detection and face recognition system that utilizes CCTV video streams and a localhost-based monitoring dashboard. Using a Research and Development (R&D) approach, a computer vision application was designed and implemented on a laptop platform. Human detection was performed using YOLO11n, facial regions were localized with YuNet, and face recognition was carried out using SFace to distinguish registered individuals from unknown persons. The detection results were displayed through a web-based dashboard that provided live video streaming, AI status information, face registration, and detection history records. Performance evaluation was conducted under various conditions, including human and non-human scenarios, registered and unknown faces, dark-room environments, and night-vision mode. The dashboard maintained a preview rate of approximately 20–30 FPS. Experimental results showed that human detection achieved an accuracy of 80%, while face recognition achieved 72% accuracy under the tested conditions. Alert Level 1 was triggered when a person was detected, whereas Alert Level 2 was activated for unknown-face events. The findings demonstrate the potential of integrating lightweight computer vision models into a local surveillance system without relying on cloud infrastructure. Nevertheless, system performance remained dependent on factors such as lighting conditions, camera distance, face orientation, image quality, and available computing resources.
Sistem Informasi Inventory Barang Berbasis Website Pada PT. Oasis Water International Bogor Siti Faizah; Eni Pudjiarti
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.v19i1.3987

Abstract

PT. Oasis Water International is a company engaged in bottled drinking water (AMDK). This research aims to design and build an information system that can efficiently manage inventory at PT. Oasis Water International, which operates in the bottled water production sector. Currently, inventory management in the company is still conducted manually, using unintegrated recording methods, resulting in inefficiencies, recording errors, and delays in data processing. The method used in this research is the First-In First-Out (FIFO) method to ensure that the first items in are the first items out, thereby minimizing the risk of losses due to expired products. This research also employs the Rapid Application Development (RAD) approach in software development to accelerate the design and implementation process of the system. The results of this research are expected to improve operational efficiency, reduce storage costs, and enhance customer satisfaction by providing accurate and real-time information regarding inventory. With the implementation of this web-based information system, PT. Oasis Water International is expected to address existing issues and improve performance and competitiveness in the bottled drinking water industry.

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