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All Journal Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics JKTP: Jurnal Kajian Teknologi Pendidikan Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Journal of Engineering and Scientific Research (JESR) JURNAL ILMIAH GLOBAL EDUCATION Cakrawala: Jurnal Pendidikan Electron: Jurnal Ilmiah Teknik Elektro Jurnal Rekayasa Lampung (JRL) Electrician : Jurnal Rekayasa dan Teknologi Elektro Jurnal Komputasi
Helmy Fitriawan
Universitas Lampung
Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Other

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Pemetaan Posisi Perokok pada Suatu Ruangan Menggunakan Metode K-Nearest Neighbor (KNN) Anisa Ulya Darajat; Muhammad Qutham Najmi Abdillah; FX Arinto Setyawan; Helmy Fitriawan
ELECTRON Jurnal Ilmiah Teknik Elektro Vol 7 No 1 (2026): Jurnal Electron, Mei 2026
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/electron.v7i1.505

Abstract

Due to the high prevalence of smoking among individuals aged 15 and older in Lampung Province and limited enforcement of smoke-free areas, a system was developed to detect and map smoker locations within a 4 × 3.42-meter room using four MQ-7 sensors. The K-Nearest Neighbor (KNN) algorithm classified smoke source locations based on carbon monoxide (CO) concentrations across four designated observation zones. Experimental results indicated that the system had an average sensor reading error of 2.041%. The classification process for smoker positions achieved 93.75% accuracy and displayed smoker locations in Zones 1, 2, 3, and 4 on a dashboard map. Detection and classification data were stored in the InfluxDB database and visualized online using Grafana. The system also delivered real-time values in parts per million (ppm), the status of each zone, and a ten-minute history of ppm values
Analysis of Mill Motor Speed on the Sugar Value in Bagasse Using the Fuzzy Logic Method at the Sugar Factory of PT. Pratama Nusantara Sakti Ricky Rachman Nursa; Helmy Fitriawan; Sri Ratna Sulistiyanti
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 15 No. 3 (2026): June 2026
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v15i3.1130-1142

Abstract

The Indonesian sugar industry faces a serious challenge in the form of low efficiency in sugarcane milling, which is indicated by the high pol value in bagasse. This condition indicates that a considerable amount of sugar remains trapped in the bagasse, resulting in sugar losses and reduced productivity. One of the operational factors contributing to this phenomenon is the rotational speed of the mill motor, as non-optimal speed can affect the level of juice extraction and the amount of sugar remaining in the bagasse. Therefore, this study aims to analyze the effect of mill motor rotational speed on the pol value of bagasse and to optimize this parameter using the fuzzy logic method. The fuzzy system was designed to process machine variables (motor speed and motor load) as well as supporting factors (moisture content, temperature, service life, and harvesting age) through inference rules based on membership functions. Results show that most fuzzy predictions are consistent with the actual data from the quality control division, with a high level of accuracy indicated by an RRMSE of 7.84%, MAE of 0.0603, and MAPE of 3.34%. These findings demonstrate that fuzzy logic is capable of handling uncertainty and the complexity of variables in the milling process, while also providing a practical solution to reduce sugar losses, improve quality, and enhance the productivity of the national sugar industry.
Identifikasi Karakteristik Suhu Pada Kesehatan Baterai litium-ion Berbasis Citra Thermal Perdana Agung Nugraha; Sri Ratna Sulistiyanti; F.X. Arinto Setyawan; Helmy Fitriawan; Lukmanul Hakim
Electrician : Jurnal Rekayasa dan Teknologi Elektro Vol. 20 No. 1 (2026)
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/elc.v20n1.2891

Abstract

Over the past few decades, the demand for environmentally friendly energy has led to an increase in the use of energy storage technologies such as batteries. One type of battery that is widely used is the lithium-ion battery because it has high durability, high energy density, and is lightweight. However, this battery is sensitive to extreme conditions such as high temperatures and excessive charging or discharging, which can affect battery health. This study aims to determine the health condition of lithium-ion batteries based on temperature characteristics from thermal images, as well as to evaluate the accuracy of a fuzzy logic system in predicting battery health status. The fuzzy logic system is used because it can handle uncertainty within varying temperature data ranges. The data used consists of 20 battery samples categorized into three groups: Healthy, Warning, and Unhealthy. The input parameters include the battery's operating temperature and the difference between the battery temperature and the ambient temperature. Evaluation was conducted using confusion matrices such as accuracy, precision, recall, and F1-score. The analysis results show that the fuzzy model has an accuracy of 84% and a precision rate of 84% for the Healthy category, 75% for the Warning category, and 93.75% for the Unhealthy category, as well as a recall evaluation of 91.30% for the Healthy category, 54.55% for the Warning category, and 93.75% for the Unhealthy category. These findings indicate that the fuzzy method is quite effective in monitoring battery health through temperature analysis.
KLASIFIKASI JENIS KAIN BERDASARKAN EKSTRAKSI FITUR TEKSTUR MENGGUNAKAN METODE GRAY LEVEL CO-OCCURRENCE MATRICES (GLCM): CLASSIFICATION OF FABRIC TYPES BASED ON TEXTURE FEATURE EXTRACTION USING THE GRAY LEVEL CO-OCCURRENCE MATRICES (GLCM) METHOD Tiya Muthia; FX Arinto Setyawan; Helmy Fitriawan; Sri Ratna Sulistiyanti; Mutia Aini Lutfia
Jurnal Rekayasa Lampung Vol. 5 No. 1 (2026)
Publisher : Fakultas Teknik Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jrl.v5i1.113

Abstract

Klasifikasi jenis kain secara manual berdasarkan karakteristik tekstur melalui pengamatan dan perabaan dapat bersifat subjektif, sehingga diperlukan pendekatan otomatis berbasis citra. Penelitian ini bertujuan mengklasifikasikan lima jenis kain, yaitu drill, katun, polyester, satin, dan wool, berdasarkan karakteristik tekstur menggunakan metode Gray Level Co-Occurrence Matrix (GLCM) dan algoritma K-Nearest Neighbor (K-NN). Citra kain diperoleh menggunakan mikroskop digital yang terhubung dengan komputer. Tahapan pengolahan citra meliputi resizing dan konversi citra RGB menjadi grayscale. Ekstraksi fitur tekstur menggunakan enam fitur GLCM, yaitu dissimilarity, homogeneity, correlation, contrast, angular second moment (ASM), dan energy, dengan empat orientasi, yaitu 0°, 45°, 90°, dan 135°. Pengujian dilakukan menggunakan 250 citra data latih dan 50 citra data uji dengan variasi jarak piksel 1–5 dan nilai K=13. Hasil pengujian menunjukkan bahwa kinerja terbaik diperoleh pada jarak 4 piksel dengan akurasi 78%, precision 46%, recall 46%, dan F1-score 46%. Waktu komputasi tercepat diperoleh pada jarak 4 sebesar 0,044 detik, dengan rata-rata waktu pengujian sebesar 0,047 detik. Hasil penelitian menunjukkan bahwa kombinasi GLCM dan K-NN dapat digunakan untuk klasifikasi jenis kain berbasis karakteristik tekstur citra.
FFR-based radio resource allocation for RIS-aided D2D communication in multicell cellular network Misfa Susanto; Soraida Sabella; Helmy Fitriawan; Ayu Purwarianti; Azrina Abd Aziz
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.11612

Abstract

Device-to-device (D2D) communication and reconfigurable intelligent surfaces (RISs) are two technologies that are attractive components of future wireless networks. D2D allows nearby devices to communicate directly, which helps boost network efficiency by reducing the load on base stations. However, since D2D often uses the same frequency bands as regular cellular users, it can cause interferences. RIS, on the other hand, enhances signal coverage by intelligently reflecting signals toward their intended destinations, but it can also unintentionally reflect interfering signals, especially in crowded multicell networks during downlink transmission. To address these interference challenges, this paper explores the application of a fractional frequency reuse (FFR) strategy purposed for networks that integrate both D2D and RIS technologies in multicell cellular network scenarios. The simulation outcomes imply that the proposed FFR method notably expands performances i.e., raising the signal quality in term of signal-to-interference-plus-noise-ratio (SINR) from 0.47 dB to 1.93 dB, enhancing throughput from 10.8 Mbps to 13 Mbps, and improving the bit error rate (BER) to 21 errors per 100 bits, demonstrating its effectiveness in improving network reliability and efficiency.
Co-Authors Agus Trisanto Ahmad Surya Arifin Anisa Ulya Darajat Ayu Purwarianti Azrina Abd Aziz Bambang Hermanto Bambang Sundari Tamtosutrisno Danny Mausa F X Arinto Setyawan Hery Dian Septana Isna oktadiani Lukmanul Hakim Mardiana Mardiana Mareli Telaumbanua Misfa Susanto Muhammad Iqbal Muhammad Qutham Najmi Abdillah Mutia Aini Lutfia Nandi Haerudin Niken Widyastuti Perdana Agung Nugraha Ricky Rachman Nursa Riswandi, Riswandi Rita Anggraini Rohimah Rohimah Setyawan, FX Arinto Siti Khodijah Soraida Sabella Sri Ratna Sulistiyanti Tiya Muthia Witaningsih Witaningsih