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All Journal Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Jurnal Pengembangan Riset dan Observasi Teknik Informatika KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT INSANtek – Jurnal Inovasi dan Sains Teknik Elektro PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Jurnal Universal Technic Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Jurnal Ilmiah Teknik Informatika dan Komunikasi Jurnal Komputer dan Elektro Sains Jurnal Elektronika dan Teknik Informatika Terapan Jurnal Rekayasa Proses dan Industri Terapan Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer Journal of Engineering, Electrical and Informatics Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Desmira Desmira
Unknown Affiliation
Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Analisis Selisih Suhu Komponen Panel LVMDP Menggunakan Alat Infrared Thermography di PT. Dongjin Indonesia Rovino Alghafari; Desmira Desmira
JURAL RISET RUMPUN ILMU TEKNIK Vol. 5 No. 2 (2026): Agustus: Jurnal Riset Rumpun Ilmu Teknik
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurritek.v5i2.8695

Abstract

The Low Voltage Main Distribution Panel (LVMDP) is a critical component in industrial power distribution systems, functioning to regulate, control, and distribute electrical energy to various production equipment. During operation, LVMDP panels often operate under high electrical loads, which may lead to temperature increases in their components. Undetected temperature rise can result in performance degradation, equipment failure, and even fire hazards. Therefore, an effective monitoring method is required to detect the condition of electrical components at an early stage. This study aims to analyze the temperature difference (ΔT) of LVMDP components using the Infrared Thermography method as part of predictive maintenance. The research employs a quantitative descriptive approach with data collected through direct observation from July 1 to July 31 at PT. Dongjin Indonesia. The data consist of hotspot and ambient temperatures measured from several panel components, which are then analyzed to calculate the temperature difference (ΔT) as an indicator of component operating conditions. The results indicate that the highest temperature difference is 26.5 °C in the capacitor bank, while the lowest is 4 °C in other components. All ΔT values are below the threshold limit of 50 °C, indicating that the LVMDP components are in safe operating conditions and do not require corrective actions. Thus, Infrared Thermography is proven to be an effective method for early detection of component conditions and can enhance the reliability and safety of industrial power distribution systems.
Rancang Bangun Counter Up-Down Berbasis Bahasa Assembly Menggunakan Aplikasi MC-51 pada Mikrokontroler AT89C2051 Rayhan Al Hayubi; Desmira Desmira
JURAL RISET RUMPUN ILMU TEKNIK Vol. 5 No. 2 (2026): Agustus: Jurnal Riset Rumpun Ilmu Teknik
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurritek.v5i2.9309

Abstract

This study designs and implements an up-down counter system based on an AT89C2051 microcontroller programmed in assembly using the MC-51 application. The system modifies an existing digital clock board by mapping the display selector pins, seven-segment segment pins, pushbuttons, and buzzer to the microcontroller ports. The research method consists of literature review, hardware identification, algorithm design, assembly programming, program downloading, and functional testing using a 5 V DC supply. The implementation uses a four-digit common-cathode seven-segment display and a multiplexing routine to show the counter value in real time. The functional test shows that the system can display the initial value, increase the value through the up button, and decrease the value through the down button. The display is readable during operation, and the program can run on the target circuit after being downloaded to the AT89C2051. This study confirms that assembly programming on MC-51 can be applied to implement a simple counter system on a reused digital clock circuit. The main limitations are the absence of explicit button debouncing, overflow and underflow protection, quantitative response-time measurement, and non-volatile data retention.
Prototype Sistem Peringatan Dini Kualitas Udara Berbasis Internet of Things (IoT) Dhabit Fauzan; Didik Aribowo; Desmira Desmira
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 6 No. 2 (2026): Juli: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v6i2.7531

Abstract

The escalation of air pollution in urban environments and enclosed spaces, primarily driven by the accumulation of Carbon Monoxide (CO) and Carbon Dioxide (CO2), poses a latent threat to human health due to their colorless and odorless nature. This study aims to design and implement an Internet of Things (IoT)-based air quality early warning system prototype utilizing the ESP32 microcontroller as the core controller. The system architecture integrates an MQ-7 sensor to measure CO levels, an MQ-135 sensor to detect CO2 concentrations, and a DHT22 sensor to monitor ambient temperature and humidity in real-time. The research methodology employs an engineering experiment approach, encompassing hardware architecture design, software development, sensor calibration via average Analog to Digital Converter (ADC) values, and comprehensive system functional testing. Experimental results demonstrate that the device accurately classifies air quality into three distinct thresholds: Good (CO < 10 ppm, CO2 ≤800 ppm), Moderate (CO 10–25 ppm, CO2 801–1500 ppm), and Poor (CO 26 ppm, CO2 > 1500 ppm, or temperature 35ºC). Upon detecting hazardous air conditions, physical indicators including a red LED and a local buzzer are simultaneously activated. Concurrently, critical alerts are transmitted to the user's smartphone via the Blynk platform, exhibiting a response time ranging from 4 to 42 seconds, with an average of 17.7 seconds. The deployment of this early warning system successfully demonstrates the effectiveness of IoT technology integration in providing a highly responsive environmental protection mechanism.
Implementasi Adaptive Neuro Fuzzy Inference System (AN-FIS) Dalam Peramalan Evaluasi Konsumsi Listrik Untuk Efisiensi Energi Di Gedung A FKIP UNTIRTA Dede Eful Ginanjar; Desmira Desmira; Irwanto Irwanto
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 6 No. 2 (2026): Juli: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v6i2.7636

Abstract

This research is motivated by the use of electrical energy that is not fully in accordance with the Energy Consumption Intensity (IKE) standard, where there are still rooms with excessive or suboptimal energy use. The study aims to evaluate and predict electrical energy consumption in Building A of the Faculty of Teacher Training and Education, Sultan Ageng Tirtayasa University in order to improve energy efficiency. The method used is quantitative research with a comparative approach, namely comparing manual calculations based on the IKE standard with the Adaptive Neuro Fuzzy Inference System (ANFIS) method. Data were obtained through observation and measurement of electrical power, room area, and duration of use which were then analyzed using Matlab with the stages of fuzzification, FIS formation, hybrid learning training, and evaluation using RMSE. The results showed that the ANFIS method produced a better level of accuracy than manual calculations. The lowest error value was obtained in the gbellmf membership function for training at 0.53 and gaussmf for testing at 0.45. These findings indicate that ANFIS is able to model nonlinear relationships effectively and has the potential to be applied as a support system for evaluating electrical energy efficiency
Implementasi Adaptive Neuro Fuzzy Inference System (ANFIS) Untuk Prediksi Konsumsi Energi Listrik Rumah Tangga Yogi Ramadani; Desmira Desmira; Didik Aribowo
Jurnal Komputer dan Elektro Sains Vol. 4 No. 2 (2026): Komets
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/komets.v4i2.669

Abstract

Konsumsi energi listrik pada rumah tangga terus mengalami peningkatan seiring bertambahnya penggunaan peralatan elektronik dalam aktivitas sehari-hari. Kondisi tersebut mendorong perlunya suatu metode yang mampu memperkirakan kebutuhan energi listrik secara akurat sehingga penggunaan energi dapat dikelola dengan lebih efisien. Penelitian ini bertujuan menerapkan metode Adaptive Neuro-Fuzzy Inference System (ANFIS) untuk memprediksi konsumsi energi listrik rumah tangga berdasarkan data hasil pemantauan menggunakan prototipe. Pengambilan data dilakukan selama 30 hari melalui sistem monitoring berbasis Arduino yang terintegrasi dengan sensor PZEM-004T, sensor DHT, Python, dan web sehingga mampu merekam parameter tegangan, arus, daya, energi listrik, suhu, serta kelembapan secara berkala. Data yang diperoleh kemudian melalui tahapan pembersihan, normalisasi menggunakan min-max scaling, pembagian data menjadi data pelatihan sebesar 70% dan data pengujian sebesar 30%, dilanjutkan dengan proses pembentukan serta pelatihan model ANFIS menggunakan fungsi keanggotaan segitiga. Tingkat kinerja model dianalisis menggunakan nilai Mean Absolute Error (MAE), Root Mean Square Error (RMSE), dan Mean Absolute Percentage Error (MAPE). Hasil pengujian menunjukkan bahwa model mampu mengikuti pola perubahan konsumsi energi listrik dengan tingkat kesalahan yang relatif rendah. Nilai MAE yang diperoleh sebesar 3,64, RMSE sebesar 5,64, dan MAPE sebesar 5,90%, sehingga tingkat akurasi model termasuk dalam kategori sangat baik. Berdasarkan hasil tersebut, metode ANFIS dinilai mampu memberikan prediksi konsumsi energi listrik rumah tangga secara andal serta berpotensi mendukung upaya penghematan dan pengelolaan energi listrik yang lebih efektif.
Co-Authors Adam Falrain Wibowo Agung Rizky Jamas Agus Gilang Hermawan Ahmad Fatoni Ahmad Kautsar Alief Maulana Andrias Widya Darmawan Anggito Wito Utomo Arum Wahyuni Purbohastuti Christin Hutagaol Dani Apriana Dede Eful Ginanjar Dhabit Fauzan Didik Aribowo Didik Aribowo Didik Aribowo Didik Ariwibowo Egi Tri Saputra Fajar Gumilang Hamdi Rahman Idris Shuhada Irwanto Irwanto M. Natsir Mastiri Mastiri Maya Selvia Laurin Muamar Ilham Zaini Muhamad Avicena H.B.H Muhammad Akmal Raihan Nur Rohima Oktiana Poppy Oktavia Rayhan Al Hayubi Riga Sahputra Dewa Rizal Fauzi romi wiryadinata Rovino Alghafari Yogi Ramadani