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All Journal ELKHA : Jurnal Teknik Elektro Jurnal IPTEK ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Indonesian Journal of Electrical Engineering and Computer Science International Journal of Engineering Continuity
Christiono, Christiono
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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The Influence of Olive Oil Additive on Sunflower Seed Oil to Improve The Breakdown Voltage of Insulation Oil CHRISTIONO, CHRISTIONO; FIKRI, MIFTAHUL; MULYANA, IWA GARNIWA; ABDUH, SYAMSIR; MAURIRAYA, KARTIKA TRESYA; FAHRI, MUHAMMAD
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 3: Published July 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i3.701

Abstract

ABSTRAKTegangan tembus isolasi minyak yang baru adalah sebesar >=30kV/2,5mm. Sesuai dengan standar IEC 601-56:2018. Minyak biji bunga matahari dipilih sebagai alternatif karena harganya terjangkau dan mudah diperoleh, akan tetapi minyak biji bunga matahari murni belum memenuhi standar IEC 61099:2010, dalam memenuhi standart tersebut dibutuhkan zat adiftif untuk meningkatkan nilai tegangan tembus isolasinya. Tujuan dari penelitian ini adalah untuk meningkatkan tegangan tembus isolasi minyak bunga matahari setelah ditambahkan aditive minyak zaitun untuk meningkatkan kemampuan isolasi, mengikuti standar IEC 61099:2010. Hasil penelitian menunjukkan bahwa minyak biji bunga matahari mempunyai nilai tegangan tembus sebesar 30,9 kV. Namun, setelah ditambahkan aditif minyak zaitun dengan perbandingan 60:40, nilai tegangan tembus meningkat menjadi 50,3 kV. Sehingga hasil pengujian minyak biji bunga matahari yang ditambahkan minyak zaitun memenuhi standar tersebut.Kata kunci: Minyak Isolasi, Minyak Bunga matahari, aditif, Tegangan Tembus ABSTRACTThe new oil insulation breakdown voltage is >=30kV/2.5mm. Compliant with IEC 601-56:2018 standards. Sunflower seed oil was chosen as an alternative because it is affordable and easy to obtain, however, pure sunflower seed oil does not meet the IEC 61099:2010 standard, to meet these standards additives are needed to increase the value of the insulation breakdown voltage. This research aims to increase the insulation breakdown voltage of sunflower oil after adding olive oil additives to increase its insulating ability, following the IEC 61099:2010 standard. The research results show that sunflower seed oil has a breakdown voltage value of 30.9 kV. However, after adding olive oil additives in a ratio of 60:40, the breakdown voltage value increased to 50.3 kV. So that the test results for sunflower seed oil added with olive oil meet the standards outlined.Keywords: Insulation Oil, Sunflower Seed Oil, additive, Breakdown Voltage
Lifetime estimation of DC XLPE cable insulation using BPNN-IPM improved with various schemes and optimization methods Fikri, Miftahul; Abdul-Malek, Zulkurnain; Mohd Esa, Mona Riza; Supriyanto, Eko; Mulyana Kartadinata, Iwa Garniwa; Abduh, Syamsir; Christiono, Christiono
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp86-98

Abstract

The world’s need for green energy is something that cannot be postponed any longer, where the transmission-distribution process requires power distribution in DC voltage. However, currently, the majority use AC voltage, so limited experience and lack of data regarding electrical cable aging under high voltage (HVDC) and their reliability are problems that must be resolved. Crosslinked polyethylene (XLPE) constitutes many insulation cables used today, so estimating the lifetime of DC XLPE cable insulation is urgent research, even though various model-optimization improvements are needed to obtain accurate results. This research begins with pre-processing for the input and output data. These results were then analyzed using two improved model schemes to accommodate the addition of variable space charge and thickness: backpropagation neural network (BPNN) and hybrid BPNN with inverse power model (BPNN-IPM). The learning process uses gradient descent (GD), genetic algorithm (GA), and Levenberg-Marquardt (LM) optimization methods. Finally, the proposed method was verified using experimental data from previous research. The results show that the hybrid BPNN-IPM with LM optimization method is the most accurate: training root mean square error (RMSE) achieved 0 days, and testing RMSE achieved 0.83 days. These results show that the method BPNN-IPM-LM used is most accurate in estimating the lifetime of DC XLPE insulation.
Clustering Suara Corona Discharge berdasarkan Tegangan menggunakan Metode Fuzzy C-Mean FIKRI, MIFTAHUL; CHRISTIONO, CHRISTIONO; MULYANA K., IWA GARNIWA; MAURIRAYA, KARTIKA TRESYA; PASRA, NURMIATI; SAMSURIZAL, SAMSURIZAL; ROMADHONI, MUHAMMAD LUTHFIANSYAH; THAHARA, ANDI AMAR
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 11, No 3: Published July 2023
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v11i3.609

Abstract

ABSTRAKCorona discharge (CD) atau peluahan permukaan merupakan faktor kegagalan isolasi pada sistem kelistrikan yang dipengaruhi oleh kondisi lingkungan tidak menentu dan perlu pemantauan secara terkini. CD menghasilkan gelombang suara yang digunakan sebagai parameter untuk langkah awal mencapai tujuan tersebut, penelitian ini mengkluster suara CD pada terminasi kubikel 20 kV. Penelitian menggunakan elektroda jarum-jarum berjarak 3 cm. Tercatat nilai sebelum breakdown voltage terjadi pada tegangan 33,4 kV, dan pengambilan data terbagi 3 klaster: 20-24 kV, 25-29 kV, 30-33 kV. Proses klasterisasi dengan metode LPC untuk menghasilkan ekstraksi suara. Kemudian menggunakan metode fuzzy c-mean untuk memperoleh akurasi dengan membandingkan pola suara training dan testing. Pada Kelembapan berkisar 70%-95% dengan suhu antara 27,5°C - 35.3°C diperoleh hasil akurasi 96,00% untuk data training dan 80,00% untuk data testing.Kata kunci: Corona discharge, fuzzy c-mean, linear predictive coding, kegagalan isolasi ABSTRACTCorona discharge (CD) is a factor in insulation failure in electrical systems, which is affected by uncertain environmental conditions and requires up-to-date monitoring. CD which produces sound waves, is used as a parameter for the initial step to achieve this goal. This research will cluster CD sounds at 20 kV cubicle terminations. The study used electrode needles spaced 3 cm apart. The value recorded before the breakdown voltage occurred was 33.4 kV, and data collection was divided into 3 clusters: 20–24 kV, 25–29 kV, and 30-33 kV. The clustering process with the LPC method produces sound extraction. Then use the fuzzy C-mean method to obtain accuracy by comparing trained and tested sound patterns. At a humidity range of 70%–95% and temperatures between 27.5°C–35.3°C, the results obtained an accuracy of 96.00% for training data and 80.00% for testing data.Keywords: Corona discharge, fuzzy c-mean, linier predictive coding, insulation failure
Clustering Fenomena Corona Discharge berdasarkan Suara menggunakan Metode LPC dan Euclidean Distance FIKRI, MIFTAHUL; CHRISTIONO, CHRISTIONO; MULYANA K., IWA GARNIWA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 10, No 3: Published July 2022
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v10i3.689

Abstract

ABSTRAKKegagalan isolasi akibat fenomena tegangan tinggi seperti corona discharge (CD) masih banyak terjadi pada sistem kelistrikan di Indonesia. Hal ini disebabkan belum dapat dilakukannya deteksi dini kegagalan isolasi. Salah satu bentuk CD berupa suara. Sebagai langkah awal deteksi dini kegagalan isolasi diperlukan suatu penelitian yang dapat mengklaster suara CD (pada kubikal 20 kV) yang merupakan tujuan penelitian. Berdasarkan pengamatan pada elektroda jarum-batang berjarak 3 cm diperoleh breakdown terkecil pada 34,3 kV. Klasifikasi suara CD ditetapkan menjadi 3 cluster yang dimulai dari tegangan cubicle 20 kV hingga sebelum breakdown terjadi yaitu 33 kV. Clustering dilakukan menggunakan metode linear predictive coding (LPC) sebagai ekstraksi ciri dan Euclidean distance sebagai pencocokan pola hasil ekstraksi. Adapun suhu di dalam kubikal antara 27,5℃ - 35,3℃ dan kelembaban berkisar 70% - 95%. Hasil akurasi clustering rata-rata yang diperoleh adalah 100% untuk data training dan 85,15% untuk data testing.Kata kunci: corona discharge, Euclidean distance, kegagalan isolasi, linear predictive coding, tegangan tinggi ABSTRACTInsulation failures due to high voltage phenomena such as corona discharge (CD) are still common in the electricity system in Indonesia. This is because early detection of insulation failure cannot be carried out. One form of CD is sound. As the first step in early detection, a study is needed to cluster CD sound (at 20 kV cubical). By observations on the needle-rod electrode at 3 cm, the smallest breakdown was at 34.3 kV. CD sound classification is set into 3 clusters starting from a cubicle voltage of 20 kV until before breakdown occurs, which is 33 kV. Clustering was carried out using linear predictive coding (LPC) as feature extraction and Euclidean distance as pattern matching extracted results. The temperature and humidity inside the cubical are 27.5℃-35.3℃ and 70%-95% respectively. For training and testing data average clustering accuracy results obtained are 100% and 85.15% respectively.Keywords: corona discharge, Euclidean distance,, insulation failure, linier predictive coding, high voltage
Optimization of Mechanical Performance Polymer Insulators SiR Using CFA Waste as Filler Fikri, Miftahul; K, Iwa Garniwa Mulyana; Christiono, Christiono; Thahara, Andi Amar
Jurnal IPTEK Vol 29, No 1 (2025)
Publisher : LPPM Institut Teknologi Adhi Tama Surabaya (ITATS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.iptek.2025.v29i1.4923

Abstract

This study investigates the use of coal fly ash as a filler in Room Temperature Vulcanization (RTV) silicone rubber to enhance its mechanical properties. Fly ash, which contains silica, has the potential to improve the strength of the polymer. The research aims to optimize the composition of fly ash in RTV silicone rubber composites using the quadratic regression method, focusing on tensile strength and elongation performance. Tests were conducted according to ASTM D 412 standards for tensile strength and elongation. The results showed that the optimal fly ash composition for tensile strength was 38.11%, resulting in a tensile strength of 0.19 and a Mean Absolute Percentage Error (MAPE) of 13.64%. For elongation, the optimal composition was 14.95%, with an elongation value of 192.094 and a MAPE of 24.75%. This study provides valuable insights into how fly ash can be used to enhance the mechanical properties of RTV silicone rubber composites.
Optimization Objective Function Corona Discharge Acoustic Using Fuzzy c-Means (FcM ) Fikri, Miftahul; Christiono, Christiono; Mulyana K, Iwa Garniwa; Ratnasari, Titi; Atmadja, Kurniawan; Thahara, Andi Amar; Romadhoni, Muhammad Luthfiansyah
ELKHA : Jurnal Teknik Elektro Vol. 15 No.2 October 2023
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v15i2.63601

Abstract

In many electrical networks in Indonesia, insulation failure due to high voltage phenomena like Corona Discharge (CD) still happens. This is a result of our inability to perform early Corona Discharge (CD) identification. This study"™s objective is to optimalize the sound properties of Corona Discharge (CD) as a first step throught the early identification of insulation failure in the form of clustering 20 kV cubicle. Based on observations on the needle-rod electrode 3 cm apart, the smallest breakdown was obtained at 34.3 kV. So that the classification of CD sound by 3 clusters starting 20 kV cubicle voltage until before the failure occurs on 33 kV. The temperature in the cubical is between 27.5℃ - 35.3℃ and humidity ranges from 70% - 95%. It was stated in the study that the FcM method was the most widely used and successful method. In this case, FcM can obtain more flexible results that classify data into clusters easily. This research will be carried out using the Fuzzy c-Means (FcM) method. Feature extraction with linear predictive coding (LPC) method, then optimization by using the Fuzzy c-Means (FcM) method which is expected to be used as an initial step for early detection of insulation failure.
Comparative Study of PSO, GA, and ACO for Optimizing Dielectric Performance in Fly Ash Filled Silicone Rubber Thahara, Andi Amar; Christiono, Christiono; Fikri, Miftahul; Garniwa M. K., Iwa; Wirandi, Mohammad
International Journal of Engineering Continuity Vol. 4 No. 2 (2025): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v4i2.439

Abstract

This study investigates the optimization of coal fly ash composition as a filler in Silicone Rubber (SiR) insulator materials, aiming to enhance their dielectric characteristics. Compositional optimization was achieved by evaluating and comparing three advanced meta-heuristic algorithms Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Ant Colony Optimization (ACO), using the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) as performance metrics. The utilized fly ash, containing dominant silica, alumina, and iron oxides, was directly incorporated into the SiR matrix. Results indicate that, compared to PSO, GA and ACO exhibited superior performance and consistency. Specifically, for Relative Permittivity, the optimal composition of 80% yielded the lowest errors with GA and ACO (RMSE = 0.0751; MAPE = 0.9044). For Hydrophobicity, these two algorithms showed superior accuracy in the RMSE metric (RMSE = 0.8883) at 15.39% loading. These findings underscore the scientific contribution of this study by establishing the superior reliability of GA and ACO for optimizing fly ash composition in SiR, thus providing a robust analytical methodology to advance the use of industrial waste for high-performance dielectric materials.
Co-Authors Abdul-Malek, Zulkurnain Atmadja, Kurniawan Eko Supriyanto Fikri, Miftahul Fikri, Miftahul Garniwa M. K., Iwa K, Iwa Garniwa Mulyana Kartika Tresya Mauriraya Mohd Esa, Mona Riza Muhammad Fahri, Muhammad Mulyana K, Iwa Garniwa MULYANA K., IWA GARNIWA Mulyana Kartadinata, Iwa Garniwa Mulyana, Iwa Garniwa Pasra, Nurmiati Ratnasari, Titi ROMADHONI, MUHAMMAD LUTHFIANSYAH Samsurizal Samsurizal Syamsir Abduh THAHARA, ANDI AMAR Wirandi, Mohammad