Indonesia merupakan negara kepulauan dengan lahan yang cukup luas. Potensi lahan yang luas serta penduduknya yang gemar bercocok tanam membuat Indonesia terkenal dengan hasil pertaniannya. Kesuburan tanah merupakan faktor penting dalam pertumbuhan tanaman yang salah satunya ditentukan oleh kadar air dalam tanah. Dalam melakukan penyiraman tanaman, volume air yang diberikan mempengaruhi pertumbuhan tanaman. Kadar air yang terlalu banyak dapat menyebabkan tanaman membusuk, namun kadar air yang terlalu sedikit dapat menyebabkan tanaman layu atau terhambat pertumbuhannya. Untuk membantu penyiraman tanaman dengan volume air yang tepat, dirancang sebuah sistem penyiram tanaman otomatis yang menyesuaikan tingkat kelembaban tanah. Untuk tujuan tersebut, dikembangkan sistem penyiram tanaman yang memanfaatkan mikrokontroller NodeMcu dan sensor kelembaban untuk mendapatkan data kelembaban tanah yang kemudian ditampilkan dalam LCD. NodeMcu juga dimanfaatkan untuk memantau kelembaban tanah yang ditampilkan dalam smartphone yang terhubung melalui jaringan wifi dengan aplikasi Blynk sebagai user interface. Adapun informasi yang ditampilkan dalam smartphone meliputi persentase kelembaban tanah, kondisi tanah, nilai ADC pembacaan sensor, grafik nilai ADC serta tombol virtual yang dapat digunakan untuk menyalakan pompa secara manual. Berdasarkan hasil pembacaan sensor, pada kondisi kering, persentase tertinggi adalah 68% dalam media pasir kering, persentase terendah atau saat kondisi basah didapatkan nilai 22% dalam media air. Dari hasil test implementasi sistem, didapatkan pompa menyala ketika kondisi tanah kering dengan persentase 39%. Untuk pengujian jarak kendali pompa melalui smartphone, didapatkan jarak maksimal yang dapat dicapai adalah 12 meter.

The voltage generated by solar photovoltaic depends on sunlight intensity. Since the direction of sunlight changes during a day, it causes changing of sunlight intensity leading to voltage reduction. To maintain the voltage, the panel must be directed so that it stays facing toward the sun to get maximum light intensity. The algorithm of Hill Climbing is employed to search the most optimal panel position that enables providing maximum voltage. This algorithm explores and saves the most optimal condition and updates it if new situation takes place. The algorithm is implemented in a Maximum Power Point Tracking (MPPT) system that continuously directs the panel to generate maximum voltage. An Arduino microcontroller is employed to interpret the algorithm that instructs DC Motor to set the most optimal panel position. A set of current and voltage sensors is used to measure and provide feedbacks to the controller. The system is implemented on a 50 WP solar panel that enables providing higher power compared with that without MPPT. Since the microcontroller and actuator also consume power, this should also be taken into account. Inclusion of this additional power still makes the system provide net power higher compared with that without MPPT.

Reliable spatio-temporal rainfall prediction is a key element in disaster mitigation and water resource management in dynamic tropical regions such as the Bengawan Solo River Watershed. However, high climate variability and data limitations often pose significant challenges to the accuracy of conventional prediction models. This study introduces an innovative approach by applying ensemble stacking, which combines machine learning models such as Random Forest (RF), Extreme Gradient Boosting (XGB), Support Vector Regression (SVR), Multi-Layer Perceptron (MLP), Light Gradient-Boosting Machine (LGBM) and deep learning models like Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Temporal Convolutional Networks (TCN), Convolutional Neural Network (CNN), and Transformer architecture based on monthly Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) data (1981–2024). The novelty of this research lies in the systematic exploration of various model combination scenarios—both classical and deep learning and the evaluation of their performance in projecting rainfall for 2025–2030. All base models were trained on the 1981–2019 period and validated with data from the 2020–2024 period, while ensemble stacking was developed using a linear regression meta-learner. The results show that the optimal ensemble scenario reduces the MAE to 53.735 mm, the RMSE to 69.242 mm, and increases the R² to 0.795826—better than all individual models. Spatial and temporal analyses also indicate consistent model performance at most locations and times. Annual rainfall projections for 2025–2030 were then interpolated using IDW to generate a spatio-temporal rainfall distribution map. The improved accuracy provides a strong scientific basis for disaster preparedness, flood and drought management, and sustainable water planning in the Bengawan Solo River Watershed. Beyond this case, the approach demonstrates significant transferability to other climate-sensitive and data-scarce regions.

The increase use of vehicles with combustion engine has caused intensive exploration of fossil fuels and severe pollutions. The replacement of this engine with electric motor is expected to solve both problems. For optimal selection of the motor, assessment of its performance is necessary. This may be carried out by comparing the performance of the motors used for powering electric motorcycle. This paper presents the performance comparison of 2 motors powering a modified motorcycle. The engine of the motorcycle was successively replaced with BLDC motor and DC motor and their performances were measured. The motorcycle was loaded with 1 and 2 passengers with the total weight of 59 and 109 Kg, respectively. The motorcycle speed (km/h) was adjusted up to 30 km/h. The results of the test indicate that DC motor requires power of 557.74 Watt at the speed of 317.04 rpm and generates torque of 16.81 Nm with energy consumption of 41.55 km/kWh. For the BLDC motor, it requires power of 526.62 Watt at the speed of 316.78 rpm and generates torque of 15.88 Nm with energy consumption of 50.59 km/kWh. For the same distance, DC Motor enables generates higher torque than BLDC motor. However, BLDC motor may present lower energy consumption per kWh than DC motor.

Emergency power supply is necessary for a mosque particularly when prayer is happening while power cuts. The important devices required to remain alive at this event are lighting and sound system. For this purpose, a battery is needed to supply the devices and the lighting and movement sensors that used to control the emergency power supply. The battery is powered by a solar photovoltaic (PV) panel. The power supply switching between main power and battery is regulated by Automatic Transfer Switch. A 20 Ah, 12 Volt battery supplied by 50 WP solar PV panel is used to back up the power for 6 W LED light and sound system. The system is implemented on the Mosque of Al-Bakri, Mojosongo, City of Surakarta. Research purpose of implementing this system is to solve the problem of power cuts during worship. This research used survey and measurement methods. In conclusion of implementing this system the prayer may continue even the electricity went out.

Coastal region normally has sufficient wind power that has not been properly utilized. On the other hand, some places in this region do not have electricity supply from the utility due to some reason. People activity in these areas may need some electricity at least for lighting the area in the evening. For the purpose of generating electricity, a portable power generation is developed to use the wind power and used to supply the power for the light. Wind power plants have so far used propellers with horizontal configurations. In this model, the blades used in propellers have limited dimensions due to mechanical considerations. In addition, the direction of the propeller needs to be directed toward the wind flow, so that a steering wheel and a rotating base are required. To overcome this problem, it is necessary to utilize a number of wind impulse blades placed on the vertical axis. In addition to the expectation to obtain greater thrust, no mechanical equipment is necesary to direct the turbine toward the direction of wind flow. These advantages are expected to increase the output voltage of the generator coupled to it. The generator used in this research is a modified induction motor with some additional magnetic poles to become synchronous generator. The generated power is used to charge a battery which is used to power the light at the night. Small scale generator prototype was developed and tested for coastal locations or other open spaces to obtain wind flow with sufficient power to drive turbine blades.