Publication Search

Penelitian ini bertujuan untuk merancang dan merealisasikan antena mikrostrip patch berbentuk segitiga (triangular) yang bekerja pada frekuensi 1800 MHz, sebagai penguat jaringan internet di kawasan Kebun Raya Balikpapan. Lokasi tersebut diketahui memiliki kualitas sinyal yang kurang baik untuk beberapa provider. Antena yang dirancang menggunakan dua konfigurasi, yaitu MIMO 8x8 dengan teknik pencatuan langsung dan array 8x1, yang kemudian disimulasikan menggunakan CST Studio Suite 2019 dan diuji performansinya menggunakan metode Speedtest. Hasil simulasi menunjukkan bahwa antena 8x8 memiliki nilai VSWR sebesar 1,50, return loss -12,96 dB, dan gain 4,06 dBi dengan pola radiasi omnidirectional. Sementara itu, konfigurasi 8x1 array menunjukkan nilai VSWR 1,24, return loss -19,21 dB, dan gain 6,46 dBi, juga dengan pola radiasi omnidirectional. Hasil pengujian di lapangan dengan tiga kondisi tanpa antena eksternal, antena MIMO dan antena array 8x1 didapatkan hasil bahwa antena array 8x1 memberikan kecepatan unduh tertinggi mencapai 17,227 Mbps, unggah 4,072 Mbps, Jitter 34,9 ms  dan packet loss 14,18 % sedangkan antena MIMO 8x8 memberikan kecepatan unduh tertinggi mencapai 13,77 Mbps, unggah 2,462 Mbps, Jitter 49,9 ms  dan packet loss 18,43%. Kesimpulannya, kedua jenis antena eksternal yakni MIMO 8x8 dan array 8x1 mampu meningkatkan performa jaringan secara signifikan dan dapat menjadi solusi efektif untuk daerah dengan sinyal lemah. Antena ini diharapkan dapat memberikan kontribusi terhadap akses internet yang lebih stabil di area public yang sangat luas.

Penelitian ini bertujuan untuk mengembangkan sistem telemetri guna memantau kinerja panel surya pada beberapa lokasi dengan menggunakan komunikasi jarak jauh dan platform Internet of Things (IoT). Metode pemantauan konvensional memiliki keterbatasan dalam menyediakan data secara real-time pada area yang luas, sehingga evaluasi kinerja jarak jauh menjadi kurang efisien. Untuk mengatasi permasalahan tersebut, dirancang sebuah sistem pemantauan menggunakan mikrokontroler ESP32, sensor INA219 untuk mengukur tegangan dan arus, modul GPS Neo-M8 untuk identifikasi lokasi, modul Real-Time Clock (RTC) DS3231 untuk pencatatan waktu, serta modul LoRa RA-02 sebagai media komunikasi nirkabel. Setiap node pengirim dilengkapi dengan modul MicroSD untuk menyimpan data pengukuran secara lokal. Data hasil pengukuran dikirimkan melalui LoRa ke unit penerima dan ditampilkan secara real-time pada platform Thinger.io. Hasil kalibrasi menunjukkan bahwa sensor INA219 memiliki rata-rata galat pengukuran arus sebesar 0,71% dan galat pengukuran tegangan sebesar 0,1%. Pengujian GPS menunjukkan koordinat lokasi yang stabil dengan tingkat akurasi sekitar ±3 hingga ±8 meter. Seluruh data pengukuran berhasil dikirim, disimpan, dan ditampilkan tanpa kehilangan data yang signifikan. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan mampu menyediakan pemantauan parameter panel surya secara jarak jauh yang andal dan efisien dalam kondisi lapangan.

The development of renewable energy, particularly Solar Power Plants (PV), requires a reliable, real-time, and easily accessible electrical energy monitoring system to ensure optimal system performance. This study aims to design and implement an Internet of Things (IoT)-based electrical energy monitoring system for PV using the NodeMCU ESP32 microcontroller, the PZEM-004T sensor for measuring electrical parameters, and the Node-RED platform as the data visualization interface. The developed system is designed to monitor voltage, current, power, energy, frequency, and power loss in real time, and then display the data in the form of numerical values, graphs, and indicators on a dashboard accessible through a local network. The research method includes hardware design, software development (sensor reading, data processing, and communication), integration with Node-RED, and system testing on a small-scale PV installation. The test results show that the system is capable of monitoring electrical parameters in a stable and responsive manner. Variations in sunlight intensity were found to affect the current and power produced by the solar panels, whereas the inverter output voltage tended to remain within normal operating ranges. The Node-RED dashboard display was considered informative and helpful for users in monitoring and analyzing PV performance. Based on these results, it can be concluded that the IoT-based electrical energy monitoring system designed in this study functions well and is feasible for application in residential or educational-scale PV installations. The system still has the potential for further development through cloud service integration, the addition of environmental sensors, and enhancements to data analysis features and user interface design.

Information technology is currently developing and growing rapidly in all fields, supported by the advancement of computer technology. The application of information systems can also be applied to the financial services sector, including cooperatives like K.S.P Al Hudori. The loan service system remains ineffective due to the manual data management process, which involves writing data into ledgers, which are easily lost or damaged due to the paper-based nature of the data. This research aims to implement a loan information system at K.S.P Al Hudori that can assist with loan data verification, search, and report generation. This information system was designed using Embarcadero XE2 and Microsoft Access 2007 as its database. This system has been implemented at KSP Al Hudori. It is hoped that this information system will simplify the loan management process at K.S.P Al Hudori

Indonesian Sign Language (BISINDO) serves as a primary communication medium for the deaf community; however, limited public understanding often creates barriers during daily interactions. This study aims to develop a real-time BISINDO word-level translation system using hand landmark extraction and temporal modeling with Long Short-Term Memory (LSTM). The system employs MediaPipe Hands to detect 21 hand landmarks per frame, which are then processed as sequential motion patterns to classify five BISINDO words: saya, terima kasih, maaf, nama, and kamu. A total of 250 gesture samples were recorded under controlled lighting conditions as the primary dataset. The processed sequences were used to train the LSTM model, which was subsequently integrated with an ESP32 microcontroller and a DFPlayer Mini module to produce direct audio output. Experimental results show that the model achieved an average accuracy of 86%, with precision and recall values ranging from 0.81 to 0.94. The confusion matrix analysis indicates that most gestures were correctly classified, although some errors occurred in gestures with similar initial motion trajectories. Integration testing demonstrated an average system latency of 3.8 seconds and an audio output success rate of 85%. These findings indicate that the proposed system is capable of translating BISINDO word-level gestures accurately, responsively, and consistently in real-time conditions. This study provides a strong foundation for the broader development of sign language translation systems, with potential enhancements in vocabulary expansion, multi-user datasets, and hardware optimization for deployment in real-world environments.

Information technology is currently developing and growing rapidly in all fields, supported by the advancement of computer technology. The application of information systems can also be applied to the financial services sector, including cooperatives like K.S.P Al Hudori. The loan service system remains ineffective due to the manual data management process, which involves writing data into ledgers, which are easily lost or damaged due to the paper-based nature of the data. This research aims to implement a loan information system at K.S.P Al Hudori that can assist with loan data verification, search, and report generation. This information system was designed using Embarcadero XE2 and Microsoft Access 2007 as its database. This system has been implemented at KSP Al Hudori. It is hoped that this information system will simplify the loan management process at K.S.P Al Hudori.

The manual employee attendance process at the Perjuk Village government level often results in inaccurate data, delayed recapitulation, and difficulties in real-time attendance monitoring. This study aims to develop an Internet of Things (IoT) and Radio Frequency Identification (RFID)-based village employee attendance system to simplify the administrative process and improve the efficiency of attendance recording. The development method used is the Research and Development (R&D) model with stages including needs analysis, system design, validation, field trials, and product revisions. The system was built using an ESP32 microcontroller, an RC522 RFID module, and a Wi-Fi connection to transmit attendance data to a web-based server. Testing was conducted using the black box method to ensure all system features run according to design. The results of the black box test show that all features run according to design. The system records attendance automatically with 100% accuracy, saves data to the server database, and displays reports in the form of tables, graphs, and statistical cards. The study concludes that this IoT and RFID-based attendance system is able to improve the accuracy, speed, and efficiency of recording compared to manual methods, and is in accordance with operational needs at the Perjuk Village Office.

The main problem with the water heating system on offshore platforms is the absence of water level monitoring and automatic overflow detection. This has the potential to cause hot water spills that endanger workplace safety and operational efficiency. This research designs and implements a water level monitoring system based on the Arduino Uno microcontroller with HC-SR04 ultrasonic sensors. The system is equipped with LED indicators, a buzzer alarm, and a 16x2 LCD to display water level status in real-time. Water levels are classified into three zones (low, medium, high), and overflow is detected if the water is within 3 cm of the sensor. Testing was conducted on a 5-liter simulation tank representing actual 500-liter tank conditions. Test results showed a reading accuracy of 96% and a quick system response to overflow conditions (<1 second). This system is economical, easy to develop, and highly applicable for offshore environments. In addition, this system can be integrated with IoT technology for remote monitoring.

This study presents a machine learning approach for predicting the dimensions of microstrip antenna slots based on antenna performance parameters such as frequency, gain, directivity, return loss (S11), radiation efficiency, and VSWR. A two-phase methodology was employed. In the first phase, ten regression algorithms were evaluated, and Random Forest was identified as the most effective model based on Mean Absolute Error (MAE) and R-squared (R²) scores. In the second phase, hyperparameter tuning was conducted using Grid Search to further improve the model’s performance. The optimized Random Forest model demonstrated consistent improvements in predictive accuracy, with R² values increasing across all output variables. These results indicate that the combination of regression-based modeling and systematic hyperparameter tuning is effective for capturing complex relationships in antenna design tasks. The proposed approach offers a promising data-driven alternative for geometric prediction in microstrip antenna development, particularly when analytical models are insufficient.

Produksi perhiasan emas PT Gemopia Indonesia melibatkan proses bombing, yang membutuhkan keakuratan tinggi untuk memastikan kualitas produk.  Beberapa kelemahan sistem pencatatan yang masih dilakukan secara manual menggunakan Microsoft Excel termasuk keterlambatan laporan, kurangnya keamanan data, dan kesalahan input yang tinggi. Tujuan penelitian ini adalah untuk mengembangkan dan membangun sistem informasi bombing emas berbasis web yang akan mempercepat proses pencatatan, meningkatkan akurasi data, dan memperbaiki alur pelaporan.  Pengembangan sistem ini menggunakan metode Waterfall, yang mencakup tahapan analisis kebutuhan, perancangan sistem menggunakan UML, pengembangan dengan framework Laravel dan database MySQL, dan pengujian dengan metode black box. Hasil pengujian menunjukkan bahwa seluruh fungsi sistem berjalan dengan baik dan sesuai dengan kebutuhan pengguna, dengan fitur seperti perhitungan otomatis, hak akses pengguna bertingkat, verifikasi dan koreksi data produksi, dan pembuatan laporan dalam format PDF. Sistem mampu menerima input, memproses data , dan menghasilkan output yang tepat dan sesuai dengan spesifikasi.Oleh karena itu, sistem ini dinyatakan layak untuk diimplementasikan secara penuh dalam rangka mendukung efisiensi dan transparansi pelaporan produksi di PT Gemopia Indonesia.

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring.

The Message Queue Telementary Transport (MQTT) protocol is able to adjust the sending and receiving of messages to monitor in accordance with the user's preferences because the sending and receiving of messages is topic based on a specified topic, making it necessary to routinely monitor the condition of patients who have been diagnosed with heart problems from a distance. With the aim to perform a Quality of Service (QoS) analysis with throughput, delay, and packet loss parameters using Unshielded Twisted Pair internet transmission media (UTP) and Wireless, the goal of this research is to design and implement (MQTT) a heart rate monitoring device with an EKG module as a sensor and ESP32 as a microcontroller. On the Ubidots website, EKG signals are transmitted over the internet and shown in real time. QoS analysis is performed using the Wireshark application. Data was collected on two scenarios at intervals of 30 minutes, 1 hour, 2 hours, 5 hours, 8 hours, 12 hours, 18 hours, and 23 hours. The throughput, latency, and packet loss metrics used in this study's results cause different value variations; these are influenced by the weather, internet bandwidth, computer, and router specifications. According to testing, the tool is portable and has a 3000mAh battery, but it has the restriction that it can only be used with reliable internet and bandwidth.

Abstrak  - Coal handling system berfungsi menangani pekerjaan mulai dari pembongkaran batu bara dari kapal/tongkang (unloading area) yang dipindahkan ke conveyor - conveyor, penimbunan/penyimpanan di stock area, ataupun pengisian ke bunker yang digunakan untuk pembakaran di boiler. Dalam proses pembongkaran tersebut tidak boleh terjadi penyumbatan / plugging terutama pada chute conveyor, maka dari itu diperlukan sensor proteksi untuk mencegah hal tersebut. Sensor lama yang digunakan yaitu berjenis Tilt Switch yang selama pemakaian tidak efektif karena banyak masalah sehingga dilakukan pemeliharaan, akibatnya dilakukan penggantian menggunakan sensor berjenis MBD (Microwave Beam Detector). Dari analisa setelah penggantian menggunakan sensor MBD, permasalahan penyumbatan chute berkurang dapat dilihat dari frekuensi pemeliharaan yang semakin berkurang.

SMA Negeri 1 Baturiti merupakan salah satu instansi pendidikan di bawah naungan Dinas Pendidikan Kabupaten Tabanan yang memiliki berbagai aset penunjang kegiatan belajar mengajar. Proses pelaporan aset selama ini masih dilakukan secara manual menggunakan Microsoft Word, sehingga kurang efisien dan sering mengalami keterlambatan dalam pelaporan kepada Dinas Pendidikan. Untuk mengatasi permasalahan tersebut, dirancang dan dibangun sistem dengan judul Optimalisasi Pengelolaan Inventaris Sekolah Melalui Sistem Inventory Berbasis Web di SMA N 1 Baturiti. Sistem ini dikembangkan menggunakan bahasa pemrograman PHP dan database MySQL, serta dilengkapi fitur pencetakan laporan dengan PHP Word dan PHP Excel. Sistem ini mempermudah proses input data aset dan menghasilkan laporan yang lebih cepat, akurat, dan terstruktur. Dengan adanya sistem ini, diharapkan pelaporan aset sekolah kepada Dinas Pendidikan dapat dilakukan secara lebih tepat waktu dan efisien.

The increasing need for electrical energy in Indonesia encourages the development of new renewable energy (EBT), including hydroelectric power plants (PLTA) as an environmentally friendly solution. This research was conducted at the Mentawa Dam, West Toili District, Banggai Regency, Central Sulawesi, to analyze the potential of water energy that can be utilized as a source of micro-hydro power plants (PLTMH). This dam currently functions as irrigation and a tourist attraction, but has significant potential to generate sustainable electrical energy. The research methods include measuring water discharge using the float method, measuring the height of the water fall (head) with an altimeter and GPS, and analyzing the potential for electrical power using the formula P = η ⋅ ρ ⋅ g ⋅ Q ⋅ H. The measurement results show an average water discharge of 3.01 m³ / s and a water fall (head) of 6.56 meters. With a turbine efficiency of 80%, the potential electrical power that can be generated reaches 154.76 kW. This study recommends the use of Kaplan turbines in Mentawa Dam, which are ideal for large discharge conditions and low to medium heads, and can adapt to discharge fluctuations, making it an optimal choice to maximize energy potential. This research is expected to provide sustainable energy solutions for the people of Toili Barat District and support the development of the tourism sector.

The election of the OSIS chairman at SMK Al-Ikhlas Losari often influences subjectivity, so a goal-oriented system is needed to select the best candidate. This study applies the WASPAS method in a Decision Support System to broadcast OSIS chairman candidates based on criteria such as attendance, integrity, academic achievement, and health. Data were collected through observation, interviews, and literature studies, then processed using Microsoft Excel. The results of the WASPAS calculation yield a Qi preference value, which determines the ranking of candidates transparently. This system reduces subjectivity, increases efficiency, and ensures the selection of competent leaders, supporting the OSIS vision.

This research aims to design and build a system for stirring and monitoring temperature and humidity for ESP32-based compost fertilizer. This system uses an ESP32 microcontroller to control compost mixing and monitor temperature and humidity conditions in real- time. Data obtained from sensors will be sent to the server for monitoring via Blynk. The implementation of this system is expected to increase the efficiency of the composting process and produce high quality compost through optimal monitoring and mixing.

Traditional doors usually consist of a housing or padlock and a flip key to open it. Usually found on office or mall doors, doors can be made more practical. The door will open automatically if there is physical energy (stimulus) that moves it. For example, when someone wants to enter the room, the door will automatically open. Doors like this are designed using automatic control using embedded system equipment. This automatic door system can be designed using automatic control combined with PIR sensors and servo motors. In terms of input equipment, a PIR (Passive Infrared Receiver) sensor is used which will detect humans approaching the door. This PIR sensor will send a signal to the Arduino process unit which contains a microcontroller chip. This microcontroller will send the processed data to the servo motor, so that it can open or close the door automatically.

Indoor air quality plays a vital role in public health, especially since people spend about 90% of their time indoors. Poor indoor air quality, often caused by chemical, physical, and biological pollutants, can severely impact health, comfort, and productivity. To tackle this issue, a robust air quality monitoring and control system was designed, featuring an ESP32 microcontroller paired with sensors such as the GP2Y1010AU0F dust sensor, MQ-7 carbon monoxide sensor, and MQ-2 smoke sensor, along with a fan to enhance air circulation. This system is capable of detecting air quality issues and taking corrective action. The ESP32 module, integrated with the Internet of Things (IoT) technology, enables real-time transmission of sensor data to a web server for continuous monitoring and prompt response. Researchers have made significant progress in creating an effective, system-based solution to improve and maintain indoor air quality

This paper presents the design and implementation of an automatic Virgin Coconut Oil (VCO) making device using an Arduino Uno microcontroller. Virgin Coconut Oil has gained popularity due to its health benefits and versatile uses in various industries. The traditional process of making VCO involves manual effort and precise timing, which can be tedious and inconsistent. The proposed automated system aims to streamline the VCO production process by integrating sensors, actuators, and a microcontroller to achieve precise control and monitoring of the process variables. The Arduino Uno microcontroller serves as the central unit for data acquisition, processing, and control, facilitating automation through programmed logic. Key components of the automated VCO maker include temperature sensors for monitoring heating stages, a motor for stirring, and relays for controlling heating elements. The system utilizes feedback loops to maintain optimal conditions during each phase of VCO production, ensuring reproducibility and quality. The design also emphasizes user-friendly operation, with an interface that provides real-time feedback on process parameters and allows manual intervention if necessary. Safety features are incorporated to prevent overheating and ensure operational reliability. Overall, the developed automatic VCO maker offers a practical solution to enhance the efficiency and consistency of VCO production, catering to both small-scale producers and commercial enterprises in the food and cosmetic industries