Article Per Year (5 Year)
p-Index From 2021 - 2026
1.456
P-Index
This Author published in this journals
All Journal Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi Jurnal Elkolind : Jurnal Elektronika dan Otomasi Industri ELECTRA : Electrical Engineering Articles Jurnal Teknologi International Journal of Electronics and Communications Systems Journal Of Human And Education (JAHE) EPSILON: Journal of Electrical Engineering and Information Technology Jurnal Inkofar
Maria Bestarina Laili
Universitas Singaperbangsa Karawang
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Other

Published : 9 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 9 Documents
Search

 1 
RANCANG BANGUN BATTERY PACK LITHIUM 144V/220AH UNTUK MOBIL LISTRIK Sunardi, Egi; Maria Bestarina Laili; Jelita Permatasari; Hanopa Abdul Hidayah; Diky Zakaria
EPSILON: Journal of Electrical Engineering and Information Technology Vol 23 No 1 (2025): EPSILON - Journal of Electrical Engineering and Information Technology
Publisher : Department of Electrical Engineering, UNJANI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55893/epsilon.v23i1.127

Abstract

The development of electric vehicle (EV) technology is advancing rapidly in various aspects, driven by the need for environmentally friendly and efficient transportation solutions. Electric vehicles are powered by electric motors, which require an energy source in the form of a battery arranged into a battery pack. A battery pack consists of battery cells arranged in series and parallel to meet the energy specifications required by the electric vehicle. Currently, lithium batteries are considered the best choice for electric vehicles due to their advantages in energy density and cost per cycle compared to other types of batteries. In the design of this battery pack, the vehicle's specifications require a voltage of 144V to power the electric motor, with a target usage time of 5 hours, leading to a designed capacity of 220Ah. The battery used is a Lithium Ferro Phosphate (LFP) type with specifications of 3.2V and 22Ah. Based on mathematical calculations, the battery pack design utilizes 10 batteries in parallel and 48 in series to achieve the required specifications. The design also takes into account the maximum storage space inside the vehicle, with the battery pack divided into two banks placed in the front and rear of the vehicle to maintain a balanced center of gravity. After assembly, voltage measurements showed that the maximum voltage achieved was 153.6V. Testing was conducted after the batteries were installed in the vehicle, which showed that the vehicle could be operated for 19 hours with an average current of 11.5A. From the test results, the battery capacity was calculated to be approximately 218.5Ah. The test results indicate that the battery performance does not fully match the theoretical calculations, due to factors such as battery characteristics and energy losses in the vehicle system.
Implementasi Sistem Pendeteksi Buku dengan YOLOv8 Maria Bestarina Laili; Raihan Alfariji; James Tri Septiono; Muhammad Farid Idlal; Egi Sunardi
EPSILON: Journal of Electrical Engineering and Information Technology Vol 23 No 1 (2025): EPSILON - Journal of Electrical Engineering and Information Technology
Publisher : Department of Electrical Engineering, UNJANI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55893/epsilon.v23i1.130

Abstract

Pendeteksian objek secara otomatis merupakan salah satu teknologi yang berkembang pesat dalam bidang visi komputer, khususnya dalam konteks pengelolaan data visual berbasis citra digital. Buku sebagai objek fisik yang umum dijumpai di perpustakaan, toko, dan lingkungan pendidikan memiliki potensi untuk diidentifikasi secara otomatis guna mendukung proses inventarisasi dan digitalisasi. Tujuan jurnal ini ialah untuk mengimplementasikan dan mengevaluasi kinerja algoritma deteksi objek YOLOv8 dalam mengenali dan melokalisasi objek buku pada gambar statis. Model YOLOv8 dipilih karena memiliki arsitektur yang efisien dan telah terbukti unggul dalam kecepatan serta akurasi deteksi. Dataset yang digunakan terdiri dari citra-citra beranotasi yang menggambarkan berbagai kondisi penempatan dan orientasi buku. Setelah melalui proses pelatihan dan pengujian, model dievaluasi menggunakan metrik precision, recall, F1-score, dan mean Average Precision (mAP). Model deteksi ini memiliki nilai box loss sebesar 0.4325 dan class loss sebesar 0.3096. Semakin kecil nilai loss, semakin akurat prediksi yang dihasilkan oleh model. Model juga mencapai mAP 50 sebesar 0.80 dalam metrik, dan mAP50-0.97 sebesar 0.811 dalam metrik. Hasil penelitian ini berhasil mengimplementasikan model YOLOv8 untuk mendeteksi buku dengan tingkat presisi sebesar 88% dan recall sebesar 94% dengan tingkat akurasi sebesar 90% dan 92%.
Performance Evaluation of Electronic Control System in Series-Parallel Hybrid Vehicle: A Simulation Study Permatasari, Jelita; Santoso, Dian Budhi; Sunardi, Egi; Laili, Maria Bestarina
International Journal of Electronics and Communications Systems Vol. 5 No. 1 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v5i1.27629

Abstract

The increasing contribution of the transportation sector to global emissions has driven the development of hybrid electric vehicles (HEVs) as a practical solution to reduce environmental impact. The effectiveness of HEVs is highly dependent on electronic control systems that regulate power distribution between the internal combustion engine (ICE), electric motor, generator, and battery in real time under various operating conditions. This study aims to evaluate the performance of the electronic control system implemented using Stateflow in a simulated series-parallel hybrid electric vehicle. The research methodology involves simulating the vehicle model in MATLAB/Simulink, which integrates Stateflow to design and manage the logic and operational mode transitions. A continuous closed-loop feedback structure is used to facilitate real-time control decisions, guided by input variables such as throttle position, vehicle speed, and battery State of Charge (SoC). Various driving scenarios are simulated, including acceleration, steady cruising, deceleration, and energy recovery during braking. Simulation results show that the designed electronic control system can maintain operational stability with engine efficiency reaching 92%, battery power utilization up to 65%, and electronic transitions between modes (EV, HEV, regenerative) in less than 0.2 seconds, demonstrating a 40% improvement in response compared to conventional electronic control models. These findings confirm the potential of Stateflow-based electronic control approaches in creating more responsive and efficient hybrid vehicle propulsion systems, while supporting the development of low-emission transportation technology
Evaluasi Kinerja YOLOv11 pada Deteksi Penyakit Tanaman Cabai: Studi Komparatif dengan YOLOv8, YOLOv5, dan SSD Permatasari, Jelita; Armin, Edmund Ucok; Sunardi, Egi; Laili, Maria Bestarina; Putri, Salsanabila Mariestiara
Jurnal Teknologi Vol 25, No 3 (2025): Desember 2025
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/teknologi.v25i3.8400

Abstract

Early and accurate detection of chili plant diseases is essential to support precision agriculture and minimize crop losses. Conventional visual inspection performed by farmers is often subjective and inconsistent, particularly under varying lighting conditions and complex field environments. Recent developments in deep learning, especially object detection models, enable the automation of disease identification with higher reliability. This study evaluates the performance of the YOLOv11 architecture for detecting three classes related to chili plant conditions—anthracnose, fruit fly, and healthy fruit—using a primary dataset of 1,062 field images collected in Karawang, Indonesia. The model was trained using a standardized configuration and compared with three widely used object detection models: YOLOv8, YOLOv5, and SSD. The training process was conducted for 100 epochs, with evaluation metrics including precision, recall, mAP50, mAP50–95, and inference time. Experimental results show that YOLOv11 achieved the highest detection performance, with an mAP50 of 86.94%, outperforming YOLOv8 by 3.8%, YOLOv5 by 6.8%, and SSD by 12.7%. The model also demonstrated the fastest inference speed at 10.9 ms, making it suitable for real-time field applications. Training analysis indicated stable convergence at the 61st epoch, supported by balanced precision (0.82391) and recall (0.77967) values as well as consistent reductions in both training and validation losses. These findings demonstrate that YOLOv11 provides more accurate and efficient detection of chili plant diseases compared with previous YOLO variants and SSD, and it offers strong potential for implementation in practical agricultural environments.
Penerapan Metode QoS pada Sistem Monitoring Telur Berbasis IoT Zulia Nurzamilah; Reni Rahmadewi; Maria Bestarina Laili
Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi Vol 11, No 2 (2025): Oktober
Publisher : universitas teuku umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jmkn.v11i2.12169

Abstract

Kemajuan teknologi Internet of Things (IoT) telah mendorong penerapan otomatisasi dalam berbagai bidang, salah satunya adalah sistem pemantauan proses penetasan telur. Penelitian ini bertujuan untuk mengevaluasi kualitas layanan jaringan pada sistem monitoring berbasis IoT dengan menggunakan pendekatan Quality of Service (QoS) melalui perangkat lunak Wireshark. Evaluasi dilakukan dengan mengukur empat parameter utama, yaitu throughput, delay, jitter, dan packet loss. Berdasarkan hasil pengujian, nilai rata-rata throughput yang diperoleh sebesar 7,88 Kbps, dengan rentang nilai antara 2,89 Kbps hingga 21,41 Kbps. Parameter delay menunjukkan nilai rata-rata sebesar 67,71 ms, di mana nilai terendah mencapai 2,72 ms dan tertinggi 160 ms, masih dalam kategori sangat baik menurut standar TIPHON. Untuk jitter, nilai rata-rata tercatat sebesar 1,63 ms, dengan variasi dari 0,2 ms hingga 3,0 ms, yang menandakan kestabilan jaringan dalam hal waktu tunda. Adapun packet loss tercatat sebesar 0% pada seluruh pengujian, menunjukkan tidak adanya kehilangan paket data selama transmisi berlangsung. Temuan ini menunjukkan bahwa sistem monitoring IoT yang diuji memiliki kualitas jaringan yang cukup andal dan stabil, serta layak digunakan untuk pemantauan suhu dan kelembaban secara real-time dalam aplikasi inkubasi telur.
Prediksi harga rumah Jabodetabek menggunakan machine learning dengan fitur geospasial dan perspektif pengembang properti Muhammad Alif Ramadhan Ramadhan; Maria Bestarina Laili Laili; Shafa Aura Ayu Ramadhan
Jurnal Elektronika dan Otomasi Industri Vol. 13 No. 2 (2026): Jurnal Elkolind Vol. 13, No. 2, 2026 (Juli 2026)
Publisher : Program Studi Teknik Elektronika Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/elkolind.v13i2.10139

Abstract

Penetapan harga rumah di kawasan Jabodetabek masih bergantung pada penilaian manual yang subjektif sehingga menimbulkan ketimpangan informasi antara penjual dan pembeli. Penelitian ini membandingkan empat algoritma pembelajaran mesin, yaitu regresi linear, hutan acak, peningkatan gradien berbasis histogram, dan ansambel bertumpuk, untuk memprediksi harga rumah berdasarkan 3.508 data listing dari sembilan kota dan kabupaten. Kontribusi utama penelitian adalah perancangan fitur dari perspektif pengembang properti, meliputi rasio koefisien dasar bangunan, kepastian legal sertifikat, tingkat daya listrik, skor fasilitas premium, dan indikator kawasan bermerek, yang dipadukan dengan fitur geospasial berupa jarak ke pusat ekonomi. Dua skenario fitur diuji untuk mengukur kontribusi fitur tersebut. Model peningkatan gradien menghasilkan kinerja terbaik dengan koefisien determinasi sebesar 0,929 dan galat persentase absolut rata-rata sebesar 18,84 persen. Penambahan fitur geospasial dan perspektif pengembang terbukti meningkatkan akurasi prediksi secara konsisten dan signifikan.
DESIGN OF A DIGITALIZED INDEPENDENT WASTE BANK INFORMATION SYSTEM USING GOOGLE APPS SCRIPT WITH AN INTEGRATED INPUT GATEWAY AND LIVE CALCULATOR Fery Andika Kurniawan; Maria Bestarina Laili; Ima Rochimawati; Nita Winda Sari
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Conventional waste bank management often faces challenges regarding transaction data recording accuracy, the risk of incorrect resident ID entry, and delays in updating savings balance information. This research aims to design and implement a digitized, web-based independent waste bank information system using Google Apps Script (GAS), Google Sheets as the database, and Bootstrap for the user interface. The design methodology focuses on minimizing human error by implementing a "Resident ID Master Input" feature (Single Input Gate) that integrates and locks transaction data, alongside a "Live Calculator" for real-time Rupiah value simulations based on pricing data from the *Harga_Komoditas* (Commodity Prices) sheet. Testing results demonstrate that the system successfully eliminates ID input errors across transaction modules (Waste Deposit and Cash Withdrawal), presents transaction history in reverse-chronological order (newest first) with precise timestamps, and displays resident financial data instantly without synchronization delays.
CHIKARA: Sistem Pemantauan dan Kendali Kandang Ayam Berbasis Internet of Things dengan Mobile Application Catur Sastro Utomo; Raisa Aqila Alfadzila; Lela Nurpulaela; Maria Bestarina Laili
ELECTRA : Electrical Engineering Articles Vol. 7 No. 1 (2026)
Publisher : UNIVERSITAS PGRI MADIUN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25273/electra.v7i1.25808

Abstract

Pengelolaan lingkungan kandang ayam menuntut pemantauan dan pengendalian berkelanjutan terhadap suhu, kelembapan, pencahayaan, kualitas udara, dan keamanan kandang. Penelitian ini mengembangkan CHIKARA (Chicken Smart Poultry Technology), sistem monitoring dan kendali kandang ayam berbasis Internet of Things yang terintegrasi dengan mobile application. Metode Research and Development dengan model ADDIE (Analysis, Design, Development, Implementation, Evaluation) digunakan dalam pengembangan sistem. Perangkat keras memanfaatkan mikrokontroler ESP32-S3 bersama sensor DHT22, LDR, MQ-135, dan flame sensor, dengan Firebase Realtime Database sebagai media sinkronisasi data. Pengujian meliputi fungsi sensor, respons aktuator, integrasi sistem, komunikasi data, dan fitur aplikasi melalui metode black-box testing. Hasil menunjukkan DHT22 membaca suhu 28,4–33,0°C dan kelembapan 64–72%, LDR bernilai 824–2.531, serta MQ-135 bernilai 432–861, dengan aktuator (lampu, kipas, buzzer) merespons sesuai ambang batas yang ditetapkan. Flame sensor berhasil mendeteksi api dan mengaktifkan buzzer, sedangkan seluruh fitur aplikasi berjalan sesuai rancangan. CHIKARA mampu memadukan monitoring, kendali otomatis dan manual, serta peringatan dalam satu platform IoT terintegrasi.
Rancang Bangun Antena Mikrostrip Compact Teroptimasi pada Frekuensi 920-923 MHz untuk Node LoRa Berdaya Rendah di Lingkungan Maritim Salsanabila Mariestiara Putri; Jelita Permata Sari; Safrian Andromeda; Maria Bestarina Laili; Egi Sunardi; Amir Akbar Wicaksono
Journal Of Human And Education (JAHE) Vol. 6 No. 5 (2026): Journal of Human And Education (JAHE)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jh.v6i5.3134

Abstract

Traditional fishing activities in Karawang waters pose a high safety risk due to the lack of cellular signal coverage. Long Range (LoRa) technology operating at the 920-923 MHz frequency band provides an ideal solution for emergency (SOS) communication and tracking; however, the default whip antenna on LoRa nodes is vulnerable to physical shocks and signal attenuation in maritime environments (multipath fading). This study aims to design, fabricate, and evaluate a compact microstrip antenna using an Epoxy FR-4 substrate with an inset feed technique to improve the transmission reliability of low-power LoRa nodes. The research methods include 3D computational simulation, laboratory measurement using a Vector Network Analyzer (VNA), and direct Line of Sight (LoS) field testing on a fishing boat in Karawang waters up to a distance of 15 km. Simulation and VNA measurement results prove that the antenna resonates precisely within the target band, achieving a Return Loss of ≤ -10 dB and a VSWR of ≤ 2. Based on the field tests, the proposed microstrip antenna significantly outperformed the default antenna by maintaining a more stable Received Signal Strength Indicator (RSSI) level. At a critical distance of 10 km from the coastline, the proposed antenna successfully suppressed Packet Loss to only 4% for tracking coordinate data and 0% for emergency SOS signals. In conclusion, the designed microstrip antenna is proven reliable in overcoming maritime propagation attenuation, extending operational range, and supporting faster Search and Rescue (SAR) responses for the enhancement of fishermen's safety.
Co-Authors Amir Akbar Wicaksono Armin, Edmund Ucok Catur Sastro Utomo Diky Zakaria Egi Sunardi Egi Sunardi Fery Andika Kurniawan Hanopa Abdul Hidayah Ima Rochimawati James Tri Septiono Jelita Permata Sari Jelita Permatasari Lela Nurpulaela Muhammad Alif Ramadhan Ramadhan Muhammad Farid Idlal Nita Winda Sari Permatasari, Jelita Putri, Salsanabila Mariestiara Raihan Alfariji Raisa Aqila Alfadzila Reni Rahmadewi Safrian Andromeda Salsanabila Mariestiara Putri Santoso, Dian Budhi Shafa Aura Ayu Ramadhan Sunardi, Egi Zulia Nurzamilah