Pengembangan Teknologi Smart Powerplant Untuk Mendukung Sistem Irigasi Lahan Kering menggunakan Metode Learning Vector Quantization

Penelitian ini akan merancang model pembangkit  listrik tenaga surya  cerdas yang akan dimanfaatkan untuk kebutuhan irigasi di  sawah  lahan kering. Sawah lahan kering adalah sawah yang  mengandalkan air hujan untuk memenuhi kebutuhan pengairannya. Untuk  memenuhi kebutuhan akan air sepanjang tahun, maka diperlukan pembangunan sistem irigasi  dengan bantuan pompa listrik yang dari tenaga surya.  Panel surya pada pembangkit yang dirancang dilengkapi dengan sensor untuk mendeteksi  arah cahaya dan memiliki kemampuan untuk bergerak mengikuti arah datangnya cahaya matahari, supaya dapat menyerap energi lebih optimal.  Metode yang akan digunakan pada pembangkit adalah metode Learning Vector Quantization (LVQ).   Pembangkit listrik cerdas ini juga mampu melakukan pemantauan  secara real time  kondisi pembangkit baik arus yang masuk ke baterai,  maupun arus yang keluar dari baterai sehingga meringankan dari sisi pemantauan dan pengawasan.   Diharapkan teknologi ini dapat menjadi alternatif bagi masyarakat yang membutuhkan sistem pertanian yang mandiri dan lebih maju

Perancangan Animasi Pembangkit Listrik Biomassa dan Sampah sebagai Bagian dari Listrik Kerakyatan untuk Media Pembelajaran

Kebutuhan akan listrik di Indonesia semakin meningkat. Salah satu USAha untuk memenuhi kebutuhan listrik di Indonesia adalah dengan melibatkan masyarakat untuk membangun pembangkit listrik yang berbahan bakar biogas dan biomassa, baik yang berasal dari sampah atau berbagai jenis tanaman yang sesuai. Pembangkit listrik yang dikenal sebagai Pembangkit Listrik Biomassa ini sudah banyak diterapkan di berbagai kota di Indonesia, namun proses pembuatannya masih belum diketahui oleh masyarakat. Oleh karena itu, penelitian ini akan menghasilkan animasi Pembangkit Listrik Tenaga Sampah (PLTSa) dan Pembangkit Listrik Biomassa untuk sarana edukasi bagi masyarakat. Pembuatan animasi ini menggunakan bahasa pemrograman Visual Basic.Net dan metode pengembangan Multimedia Development Life Cycle (MDLC), yang dimulai dimulai dari pengumpulan data, perancangan multimedia dan hasil yang dicapai adalah berupa animasi

Klasifikasi Sinyal EEG Menggunakan Model K-Nearest Neighbor Untuk Pengenalan Kata Yang Dibayangkan

Locked in syndrome (LIS) is a condition of complete paralysis in which people with LIS are conscious but unable to move or communicate verbally except to move their eyes or blink. One way that can help LIS sufferers to communicate and interact is through recording brain signals called Electroencephalogram (EEG). In this study, the data from the recording of the EEG signal has gone through the extraction stage. The extracted data is preprocessed and classified using the K-Nearest Neighbor (K-NN) algorithm to be visualized using a web-based application. The results of the classification using the K-Nearest Neighbor algorithm with a value of K = 1 resulted in 82% accuracy, 82% precision and 82% recall. Keywords: LIS, EEG, K-Nearest Neighbor

Optimization of smart traffic lights to prevent traffic congestion using fuzzy logic

One of the main causes of traffic congestion, especially at intersections, is because traffic lights have not been able to show the right time according to the existing traffic conditions. Time settings based on peak/off-peak traffic lights are not enough to handle unexpected situations. The fuzzy mamdani method makes decisions with several stages, the criteria used are the number of vehicles, the length of the queue and the width of the road to be able to optimize the time settings based on the real-time conditions required so that unwanted green signals (when there is no queue) can be avoided. The purpose of this research is to create a simulator to optimize traffic time management, so that the timers on each track have the intelligence to predict the right time, so that congestion at the intersection can be reduced by adding up to 15 seconds of green light from the previous time in the path of many vehicles

Denoising of EEG signal based on word imagination using ICA for artifact and noise removal on unspoken speech

The purpose of this research is to observe the effectiveness of independent component analysis (ICA) method for denoising raw EEG signals based on word imagination, which will be used for word classification on unspoken speech. The electroencephalogram (EEG) signals are signals that represent the electrical activities of the human brain when someone is doing activities, such as sleeping, thinking or other physical activities. EEG data based on the word imagination used for the research is accompanied by artifacts, that come from muscle movements, heartbeat, eye blink, voltage and so on. In previous studies, the ICA method has been widely used and effective for relieving physiological artifacts. Artifact to signal ratio (ASR) is used to measure the effectiveness of ICA in this study. If the ratio is getting larger, the ICA method is considered effective for clearing noise and artifacts from the EEG data. Based on the experiment, the obtained ASR values from 11 subjects on 14 electrodes amounted are within the range of 0,910 to 1,080. Thus, it can be concluded that ICA is effective for removing artifacts from EEG signals based on word imagination

Pembangunan Aplikasi Kepegawaian untuk SD Islam Terpadu Yasir Di Cipondoh Tangerang

SDIT Yasir is one of the schools under the management of the Ibnu Rusydi Islamic Education Foundation in Cipondoh, Tangerang. The school that aspires to create Indonesian young generations that resemble Ibnu Rusydi has several obstacles in carrying out daily teaching and learning activities. One of the issues is the teacher and staff data management. Therefore, the PKM team from the Informatics Engineering Department IT PLN intends to help the Yasir SDIT school by designing a web-based application for handling the employees. The application can be used to manage teacher and employee data, monitor teacher and employee attendances, and provide teacher performance assessments.   Keywords: SDIT Yasir, PKM, Employee Information Syste

The design of a smart home controller based on ADALINE

This paper proposes a prototype of an improved smart home controller that implements a neural network-based algorithm for enabling the controller to make decisions and act based on the current condition. Unlike previous approaches, this design also utilizes the use of IoT (internet of thing) technology and neural network based-algorithm for developing the controller. Since a smart home is equipped with various sensors, actuators, smart appliances, and mobile terminals, all of these devices need to be connected to the Internet to be able to communicate and provide services for its occupants. The construction of the proposed controller is carried out through several procedures, i.e. the implementation of the ADALINE (adaptive linear) as the neural network method, the design of the smart home controller prototype, and the validation process using mean average percentage error (MAPE) calculation. This prototype integrates functionalities of several household appliances into one application controlled by a smartphone. ADALINE is applied as an algorithm to predict output when the controller is in automatic mode. Although the obtained accuracy value is still not satisfactory, the value is bound to change when testing on more data. The work published in this paper may encourage the implementation of smart technology in more households in Indonesia.

COMPARATIVE STUDY OF CLOUD COMPUTING NETWORK SERVICES BASED ON QoS ANALYSIS USING TIPHON STANDARD

Currently, data plays a very important role for companies or agencies. The amount of data owned, processed, and exchanged is getting bigger, so companies need more and more resources to manage it. Cloud computing technology is an efficient and economical alternative that allows users to utilize Information Technology (IT) resources flexibly, in terms of infrastructure and applications. Its key advantages include cost efficiency, scalability, data security, disaster recovery, and fast global access. The rapid development of cloud technology has led to many Cloud Service Providers (CSPs). The performances of the CSPs vary widely, thus it is necessary to understand the network performance characteristic  from the CSPs  so that users can select a more suitable service. Network capabilities in cloud computing technology are crucial, considering that all company activities are carried out through the network.   In this study, the main focus was to test the network capabilities of the two biggest cloud services The results  of the Quality of Service (QoS) comparison  will provide recommendations or input for companies or agencies in choosing the cloud service provider that best fits their needs. Thus, it was obtained that this research can provide useful guidance in optimizing the use of cloud computing technology to support business activities and innovation in various fields, including the field of education.  Based on the results of the research, the network performance of the two CPS is very good in terms of the TIPHON standard. Based on QoS analysis, especially in terms of throughput, CPS “A” shows better upload activity results, while CPS B has  better  results  for downloading activities

IoT for smart home system

This paper examines the integration of smart home and solar panel system that is controlled and monitored using IoT (internet ofthings). To enable the smart home system to monitor the activity within the house and act according to the current conditions, it is equipped with several sensors, actuators and smart appliances. All of these devices have to be connected to a communication network, so they can communicate and provide services forthe smart home’s in habitants. The smart home system was first introduced to provide comfort and convenience, but later it should also address many other things, e.g. the importance of the efficient use of energy or electricity and hybrid use of energy sources. A solar panel is added to the smart home prototype and its addition is studied. Adaptive linear neural network is implemented in the prototype as an algorithm for predicting decisions based on the current conditions. The construction of the proposed integrated systemis carried out through several procedures, i.e. the implementation of the adaptive linear neural network (ADALINE) as the neural network method, the design of the prototype and the testing process. This prototype integrates functionalities of several household appliances into one application controlled by an Android-based framework

Teknologi Content Management System (CMS) Dinamis untuk Pengembangan Aplikasi Penerimaan Siswa Baru (PSB) SDIT Yasir Cipondoh

Penerimaan Siswa Baru adalah kegiatan tahunan yang diselenggarakan oleh semua sekolah pada setiap tahun ajaran baru, tidak terkecuali SDIT Yasir yang terletak di Cipondoh Tangerang. Untuk menjangkau para calon  siswa yang berdomisili diluar Cipondoh, diperlukan suatu pengembangan aplikasi Penerimaan Siswa Baru yang berbasis web dengan semua fitur standar yang diperlukan untuk memudahkan calon siswa baru dan pihak sekolah. Terdapat beberapa fitur menu diantaranya registrasi, verifikasi pembayaran, jadwal tes dan laporan pendaftaran siswa baru.&nbsp