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High feed costs remain a major constraint in Nile tilapia (Oreochromis niloticus) aquaculture, requiring alternative feed formulations based on local ingredients with adequate nutritional quality. This study aimed to evaluate the proximate composition of fish feed formulated from snail meal, Azolla meal, and turmeric as a phytobiotic supplement. The study used an experimental method with a Completely Randomized Design consisting of three treatments and three replications. The feed formulations were P1, consisting of 55% snail meal, 25% Azolla meal, 5% turmeric, 10% corn flour, and 5% tapioca flour; P2, consisting of 39% snail meal, 39% Azolla meal, 7% turmeric, 10% corn flour, and 5% tapioca flour; and P3, consisting of 25% snail meal, 51% Azolla meal, 9% turmeric, 10% corn flour, and 5% tapioca flour. The analyzed parameters included protein, moisture, fat, ash, crude fiber, and carbohydrate contents. Data were analyzed using analysis of variance followed by the Least Significant Difference test. The results showed that feed formulation significantly affected all proximate parameters. P3 produced the highest protein content of 43.87%, fat content of 3.68%, crude fiber of 3.11%, and carbohydrate content of 7.28%, while also producing the lowest ash content of 28.46%. Moisture content ranged from 1.11% to 1.30%, indicating good feed storage stability. These findings demonstrate that the integration of snail meal, Azolla, and turmeric can improve the nutritional quality of alternative Nile tilapia feed and support locally based sustainable aquaculture feed development.

The use of local raw materials in Nile tilapia feed formulation needs to be developed to reduce dependence on increasingly expensive conventional feed ingredients. This study aimed to analyze the effect of different formulations of chicken feather meal and moringa leaf meal with turmeric addition as a phytobiotic on the chemical composition of Nile tilapia (Oreochromis niloticus) feed. The study used a completely randomized design with three treatments and three replications. P1 consisted of 55% chicken feather meal, 25% moringa leaf meal, 5% turmeric, 10% corn flour, and 5% starch; P2 consisted of 40% chicken feather meal, 40% moringa leaf meal, 5% turmeric, 10% corn flour, and 5% starch; and P3 consisted of 25% chicken feather meal, 55% moringa leaf meal, 5% turmeric, 10% corn flour, and 5% starch. The parameters analyzed were crude protein, moisture, ash, crude lipid, crude fiber, and carbohydrate. Data were analyzed using analysis of variance followed by the least significant difference test when significant differences occurred. The results showed that P3 produced the highest protein content (22.60%), ash content (6.65%), crude fiber (6.55%), and carbohydrate (8.45%), whereas P2 produced the highest lipid content (6.54%). Based on chemical analysis, P3 was the most prominent formulation for most proximate parameters. However, this formulation cannot be directly concluded as the best feed for fish growth because digestibility, palatability, feed conversion ratio, growth, survival, and health responses were not evaluated. Further biological testing is therefore required to confirm its feasibility for Nile tilapia culture.

Odot grass (Pennisetum purpureum cv. Mott) is an important ruminant forage because of its high palatability, adaptability to tropical environments, and potential for high biomass production. This study aimed to evaluate the effect of solid organic fertilizer on the growth and production of odot grass as a basis for developing productive and sustainable forage cultivation. The experiment was conducted in Pangi Village, Dulupi District, Boalemo Regency, from February to March 2026 using a completely randomized design with five treatments and three replications. The treatments consisted of P0 without solid organic fertilizer, P1 at 10 t/ha, P2 at 20 t/ha, P3 at 30 t/ha, and P4 at 40 t/ha. Observed variables included plant height, leaf number, tiller number, and fresh weight production. Data were analyzed using analysis of variance followed by Duncan’s multiple range test at the 5% significance level. The results showed that P4 produced the best response for all measured parameters. The highest plant height was 77.83 ± 43.80 cm, with 18.83 ± 3.67 leaves, 2.42 ± 1.38 tillers, and fresh weight production of 52.33 ± 10.12 t/ha. These improvements indicate that 40 t/ha solid organic fertilizer enhanced nutrient availability and supported biomass formation. Solid organic fertilizer is therefore a promising locally based cultivation input for improving ruminant forage productivity.

Stock market volatility represents a key indicator of financial market uncertainty, particularly in emerging economies where market structures are still evolving and are highly sensitive to global shocks. This study aims to analyze and compare the volatility dynamics of stock markets in four Asian emerging economies: Indonesia, India, Malaysia, and Thailand. The research employs a quantitative approach using daily stock index data from January 2011 to January 2026 obtained from Yahoo Finance. Stock returns are calculated using logarithmic transformation and analyzed using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH(1,1)) model. Prior to model estimation, stationarity and ARCH effect tests are conducted to ensure the validity of volatility modeling. The empirical findings indicate that all return series exhibit non-normal distribution, strong volatility clustering, and significant ARCH effects. The estimation results show that both ARCH and GARCH parameters are statistically significant, with persistence levels close to unity across all markets, implying that volatility shocks tend to persist over a long period. These findings suggest that emerging stock markets in Asia are highly sensitive to external shocks and exhibit long-memory volatility behavior. The results provide important implications for investors and policymakers in designing effective risk management and market stabilization strategies.

This community service activity aims to improve the effectiveness of clean water distribution management through the implementation of a Water Level Control (WLC) system as an automatic control for water pumps and three-phase motors at a regional drinking water supply company in Lamongan. The methods employed include field observation, problem identification, system design and implementation, as well as periodic evaluation of system performance. The activity focuses on the water treatment unit by conducting control and monitoring of operational parameters such as frequency (Hz), pump pressure, and flow stability to ensure optimal water distribution according to consumer needs. The results indicate that the implementation of the WLC system enhances operational efficiency, minimizes human error, and supports more structured and sustainable equipment maintenance. In addition, this activity contributes to improving the knowledge and technical skills of personnel in operating, monitoring, and maintaining automated control systems. In managing automation-based technology in a professional and independent manner, human resource capacity is strengthened, while the quality of clean water services is also improved through this community service program.

The relatively high volatility of Robusta coffee prices creates uncertainty for farmers, business actors, and policymakers in making economic decisions. This study aims to analyze the price movement patterns of Robusta coffee, determine the most appropriate Autoregressive Integrated Moving Average (ARIMA) model, and conduct short- to medium-term price forecasting for Robusta coffee. The data used consist of monthly Robusta coffee price data from January 2023 to September 2025, sourced from the World Bank Commodity Price Data. The analytical method employed is ARIMA using EViews software, beginning with stationarity testing using the Augmented Dickey-Fuller (ADF) test, model identification through ACF and PACF, parameter estimation, and residual diagnostic testing. The results show that Robusta coffee price data are non-stationary at the level but become stationary at the first difference, indicating integration of order one I(1). Based on model identification and diagnostic testing, the ARIMA (0,1,0) model is found to be the most appropriate and satisfies the white noise assumption. Forecasting results indicate that Robusta coffee prices are projected to remain relatively stable with a moderate upward trend through December 2026. These findings are expected to serve as a reference for decision-making by farmers, business actors, and the government in responding to Robusta coffee price dynamics.