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All Journal Jurnal Tekno Insentif Infotekmesin REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat
DANI RUSIRAWAN
Institut Teknologi Nasional Bandung
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Security System Based on IoT in Karyawangi Parongpong Village: Design Phase Lita Lidyawati; Dani Rusirawan; Lisa Kristiana; Narisha Kalya Mahsa
REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Vol 2, No 1 (2021): REKA ELKOMIKA
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/rekaelkomika.v2i1.33-40

Abstract

Security is always an issue both in individuals and communal attentions. Any forms of threats and crimes that occur in the village area of Karyawangi Parongpong, such as motor vehicle theft, violence, drug abuse, gambling, and others are caused by a lack of supervision from local authorities. The limitation of surveillance distance is one of the problems. Thus, an effective and appropriate security system in a place is indispensable. In this paper, the design of the security system using IoT modules and ESP32 Camera, will be elaborated for karyawangi Parongpong's village. The system secures a village environment by detecting an intruder on the road, triggering Passive Infra Red (PIR) sensor, capturing all activities with ESP32 camera, and then sending data to a smart mobile phone through with Telegram application. These service activities were aimed at the improvement of security systems and increase knowledge of technology advances for rural communities in the Karyawangi Village environment, especially in security systems based on IoT.
Analisa Prestasi Pembangkit Listrik Tenaga Uap (PLTU) Berbahan Bakar BatuBara Hasil Upgrading Cecep Deni Mulyadi; Tarsisius Kristyadi; Alexin Putra; Dani Rusirawan
Infotekmesin Vol 12 No 1 (2021): Infotekmesin: Januari 2021
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v12i1.370

Abstract

Coal is a cheap fuel, so it is widely used by steam power plants (PLTU). With many PLTUs using coal, the demand for coal  increases and the quality of the coal is decreasing and the price continues to rise. With this problem, it is necessary to improve  coal quality, one of which is by upgrading using a gas exhaust boiler. With using rotary dryer, the coal will be upgraded from low calorie to high calorie by reducing the moisture content, which will then be applied to the tempo cycle software 5.1. After application at cycle tempo 5.1, the best efficiency increase for PLTU can be increased efficiency and decrease coal rate, which is best obtained in the third experiment which achieved 37,041% efficiency with a coal rate of 17,567 kg / s.
Forecasting Produksi Energi PLTS 1 kWp Menggunakan Mesin Pembelajaran Dengan Algoritma Support Vector Machine Hasanudin Gufron; Dani Rusirawan; Lita Widyawati
Jurnal Tekno Insentif Vol 16 No 2 (2022): Jurnal Tekno Insentif
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah IV

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36787/jti.v16i2.843

Abstract

Abstrak Isu krisis energi menuntut orang mencari sumber energi alternatif, PLTS menjadi pilihan yang menjanjikan untuk menjawab tantangan krisis energi tersebut. Namun PLTS tergantung oleh kondisi cuaca, sangat sulit memperkirakan berapa produksi energi pada suatu system PLTS. Penelitian peramalan produksi energi 1kWp menggunakan mesin pembelajaran dan support vector machine (SVM) telah dilakukan dan dibandingkan dengan model multiple linear regression (MLR), model peramalan dengan pendekatan deret waktu, data training periode Januari – Desember 2021 dan data tes periode Januari – Mei 2022. Konstruksi ramalannya adalah hasil produksi tiga hari kebelakang meramalkan produksi energi hari berikutnya. Hasil evaluasi MAPE pada data training SVM dan MLR adalah 19.79% dan 23.96%, sedangkan pada testing 21,79% dan 20.45%. Hasil peramalan harian diakumulasi perbulan dan dievaluasi, hasilnya MAPE 4.13% dan 5.56% masing-masing untuk SVM dan MLR. Kedua model SVM dan MLR layak dikembangkan lebih lanjut pada forecasting PLTS 1 kWp berdasarkan data deret waktu. Abstract The issue of the energy crisis requires people to look for alternative energy sources, SPP is a promising choice to answer the challenges. However SPP depends on weather conditions, it is very difficult to estimate energy production. Research on forecasting 1kWp energy production using machine learning and SVM has been carried out and compared with MLR, forecasting models with a time series approach, training data for the period January – December 2021 and test data for the period January – May 2022. MAPE evaluation results on SVM and MLR training data were 19.79% and 23.96%, while testing was 21.79% and 20.45%. Daily forecasting results are accumulated monthly and evaluated, the results are MAPE 4.13% and 5.56% for SVM and MLR, respectively. Both SVM and MLR models deserve to be further developed in forecasting PLTS 1 kWp based on time series data.
PEMODELAN PRODUKSI ENERGI PEMBANGKIT LISTRIK TENAGA SURYA 1000 WP DENGAN ALGORITMA NAIVE BAYES Arif Fahrizal; Dani Rusirawan; Lita Lidyawati
Jurnal Tekno Insentif Vol 16 No 2 (2022): Jurnal Tekno Insentif
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah IV

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36787/jti.v16i2.864

Abstract

Abstrak Dalam penelitian ini, akan diuraikan pemodelan karakteristik produksi energi Pembangkit Listrik Tenaga Surya (PLTS) 1000 Watt peak (Wp) dalam periode Juni 2020-Desember 2021, dengan menggunakan salah satu algoritma machine learning, yaitu Naive Bayes. Fitur yang digunakan dalam pemodelan adalah radiasi matahari, temperatur & pancaran sinar, yang dibagi menjadi lima label kelas yaitu Very low, Low, Medium, High, dan Very High. Perbandingan data latih dan uji dibagi menjadi 3 skenario, yaitu 90%:10%, 80%:20%, 75%:25%. Hasil pemodelan memperlihatkan bahwa skenario perbandingan 75%:25% memiliki nilai mean absolute error (MAE), root mean squared error (RMSE) dan mean absolute percentage error (MAPE) terkecil (dibanding skenario lain), masing-masing sebesar 0,14; 0,38; dan 6,52, yang artinya skenario ini memiliki akurasi relative lebih tinggi (dibanding skenario lain), jika dibandingkan terhadap karakteristik produksi energi referensi. Abstract In this research, the modeling of energy production characteristics of 1000 Watt peak of the Solar Power Plant (SPP) will be elaborated for the period of June 2020-December 2021, using one of the machine learning algorithms, i.e., Naïve Bayes. The features used are solar radiation, temperature & light beam. Each of feature is divided into five class labels, namely Very low, Low, Medium, High, and Very High. The comparison of training and test data is divided into 3 scenarios i.e., 90%: 10%, 80%: 20%, 75%: 25%. Based on modeling, it is found that a 75%;25% scenario shows the smallest of MAE, RMSE, and MAPE, i.e., 0.14, 0.38, and 6.52, respectively. It means that this scenario has the highest accuracy in this modeling (if compared to the actual's energy production characteristics).
Desain Pembangkit Listrik Turbin Uap Berbahan Bakar Batu Bara yang Efektif dan Ramah Lingkungan Dadang Mulyadi; Dani Rusirawan; Novrita I
Jurnal Tekno Insentif Vol 17 No 1 (2023): Jurnal Tekno Insentif
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah IV

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36787/jti.v17i1.1083

Abstract

Abstrak Pembangkit Listrik Tenaga Uap (PLTU) merupakan salah satu sumber pembangkit listrik yang banyak digunakan di berbagai negara karena memiliki beberapa keunggulan diantara-Nya; teknologi sudah dikuasai, bahan bakar murah, dan usia pakai yang lama. Prinsip kerja PLTU adalah mengandalkan energi kinetik dari uap untuk menghasilkan energi listrik yang menggunakan generator untuk memutar turbin. Pembangkit ini menggunakan bahan bakar batu bara maupun bahan bakar minyak untuk memanaskan air. Penggunaan bahan bakar batu bara hingga saat ini masih menjadi andalan di Indonesia karena sumber yang tersedia banyak dan harga yang murah. Akan tetapi, penggunaan batu bara dapat menyebabkan pencemaran gas CO2 yang membahayakan lingkungan dan kesehatan. Untuk itu, desain dan karakteristik turbin uap yang baik, sangat diperlukan agar dapat menghasilkan pembakaran yang efektif dan optimal dengan emisi gas CO2 yang rendah. Dalam review paper ini disampaikan berbagai hasil penelitian yang menunjukkan desain turbin uap yang inovatif, efisien, dan ramah lingkungan dalam menghasilkan energi listrik. Abstract Steam Power Plant (PLTU) is a source of electricity that is widely used in various countries because it has several advantages including technology that has been mature, cheap fuel, and long lifetime. The working principle of the PLTU is to rely on the kinetic energy of steam to produce electrical energy that uses a generator to rotate the turbine. This power plant uses coal or oil as fuel to heat water. The use of coal as fuel is still a mainstay in Indonesia because of the available sources and low prices. However, the use of coal can cause CO2 gas pollution which is harmful to the environment and health. For this reason, the design and characteristics of a good steam turbine are needed in order to produce an effective and optimal combustion with low CO2 emissions. In this review paper, various research results are presented showing that steam turbine designs are innovative, efficient, and environmentally friendly in generating electricity power.
Co-Authors Alexin Putra Arif Fahrizal Cecep Deni Mulyadi Dadang Mulyadi Hasanudin Gufron KRISTIANA, LISA Kristyadi, Tarsisius LITA LIDYAWATI Lita Widyawati Narisha Kalya Mahsa Novrita I