Abstract:The major of this study was to estimate the impact of Adoption of Small-Scale Irrigation in Dugda district. Data were collected from both primary and secondary data sources. Primary data was collected from 384 household…
heads in four kebeles of the district using structured questionnaire. Descriptive, logit and propensity score matching techniques were used for data analysis. The study finding from the propensity score matching technique revealed that the incomes of adopters of small scale irrigation were increased by 37,696.06ETB per annum. This calls for strengthening the available irrigation facilities and expansion of irrigation sector in the study area.
Abstract:This study examines the digitalization of agriculture and its implications for food security in South Sulawesi, focusing on structural challenges, policy responses, and pathways toward sustainable self-sufficiency. Despite…
te relatively stable rice production, food security in the province remains vulnerable to climate variability, irrigation constraints, fragmented distribution systems, and uneven digital integration. Using a mixed-method approach that combines quantitative survey data and qualitative policy analysis, this research evaluates the relationship between digital adoption and farmer performance. The findings indicate that farmers utilizing digital tools demonstrate higher production stability, stronger market price awareness, and better planting planning accuracy compared to non-digital farmers. However, digital literacy gaps and limited institutional coordination constrain broader system transformation. Policy responses remain largely reactive and sectorally fragmented. The study proposes a Digital-Sustainable Self-Sufficiency Framework that integrates digital infrastructure expansion, smart irrigation governance, supply chain monitoring, and inter-agency coordination. The findings suggest that digitalization should be positioned not merely as technological adoption but as a governance transformation mechanism to strengthen adaptive capacity, enhance coordination, and achieve resilient and sustainable food security.
Abstract:This study analyzes the challenges of food security and the policy responses of the government in achieving food self-sufficiency in South Sulawesi in 2025. The research aims to identify production-consumption gaps, distribution…
ribution bottlenecks, and the impacts of climate variability and agricultural policies on food availability, accessibility, and affordability. A mixed-methods approach was employed, combining qualitative and quantitative techniques through household surveys, in-depth interviews with farmers and policymakers, field observations, and secondary data from the Central Statistics Agency and the South Sulawesi Agricultural Department.
The results reveal persistent production deficits for rice and soybeans, while corn has reached a surplus, illustrating structural imbalances among staple commodities. Approximately 62% of respondents reported difficulties in transportation and storage due to inadequate infrastructure, contributing to post-harvest losses and unstable food prices. Government programs such as irrigation development, input subsidies, and farmer training have provided partial benefits, yet 57% of farmers indicated irregular access to such support. Moreover, climate shocks such as El Niño continue to depress yields and increase vulnerability among smallholder farmers. Conversely, social capital, manifested in farmer groups and cooperative networks, has played a significant role in sustaining household food availability and resilience.
The findings suggest that food security in South Sulawesi cannot be addressed solely through production increases. A multifaceted strategy is required, emphasizing rural infrastructure development, climate-smart agricultural innovation, institutional and irrigation reform, and community-based mechanisms that strengthen social capital. This integrative approach provides empirical evidence for policy design and contributes to the broader discourse on sustainable food self-sufficiency in Indonesia.
Abstract:Abstract: The advancement of smart agriculture has become a promising solution to increase food productivity and land use efficiency in urban environments. This research aims to develop an Artificial Intelligence (AI)-based…
sed vertical hydroponic farming system integrated with LED grow light technology and catfish aquaponics. The proposed system combines vertical hydroponics and aquaponics to optimize plant growth and water utilization. Internet of Things technology enables real-time environmental monitoring through an Arduino Uno microcontroller integrated with LDR, soil moisture, pH, and NPK sensors. The obtained sensor data is processed using the Mamdani Fuzzy Logic algorithm, which performs fuzzification, rule inference, aggregation, and defuzzification to generate adaptive control decisions for irrigation, nutrient circulation, and LED grow light intensity. This research uses the Research and Development (R&D) method through prototype development and performance evaluation for 30 days using spinach (Amaranthus spp.) and mustard greens (Brassica juncea) as test plants. Experimental results showed that the developed system successfully maintained stable environmental conditions, with soil moisture ranging between 69–72%, a pH value between 6.4 and 6.6, and optimal nutrient availability. Plant growth increased significantly. The integration of IoT, AI and aquaponics improves cultivation efficiency, enabling environmental control as a smart and sustainable solution for urban agriculture.
Keywords: artificial intelligence; aquaponic; hydroponic; LED grow light; vertical farming
Abstract: Kemajuan pertanian cerdas telah menjadi solusi yang menjanjikan untuk meningkatkan produktivitas pangan dan efisiensi penggunaan lahan di lingkungan perkotaan. Penelitian ini bertujuan untuk mengembangkan sistem pertanian hidroponik vertikal berbasis Kecerdasan Buatan (AI) yang terintegrasi dengan teknologi lampu tumbuh LED dan aquaponik ikan lele. Sistem yang diusulkan menggabungkan hidroponik vertikal dan aquaponik untuk mengoptimalkan pertumbuhan tanaman dan pemanfaatan air. Teknologi Internet of Things memungkinkan pemantauan lingkungan secara real-time melalui mikrokontroler arduino uno yang terintegrasi dengan sensor LDR, kelembaban tanah, pH, dan NPK. Data sensor yang diperoleh diproses menggunakan algoritma Logika Fuzzy Mamdani, yang melakukan fuzzifikasi, inferensi aturan, agregasi, dan defuzzifikasi untuk menghasilkan keputusan kontrol adaptif untuk irigasi, sirkulasi nutrisi, dan intensitas lampu tumbuh LED. Penelitian ini menggunakan metode Pengembangan (R&D) melalui pengembangan prototipe dan evaluasi kinerja selama 30 hari menggunakan bayam (Amaranthus spp.) dan sawi hijau (Brassica juncea) sebagai tanaman uji. Hasil eksperimen menunjukkan bahwa sistem yang dikembangkan berhasil mempertahankan kondisi lingkungan yang stabil, dengan kelembaban tanah berkisar antara 69–72%, nilai pH antara 6,4 dan 6,6, dan ketersediaan nutrisi yang optimal. Pertumbuhan tanaman meningkat secara signifikan. Integrasi IoT, AI dan aquaponik meningkatkan efisiensi budidaya, untuk pengendalian lingkungan sebagai solusi cerdas dan berkelanjutan untuk pertanian perkotaan.
Keywords: aquaponik; kecerdasan buatan; hidroponik; lampu tumbuh LED; pertanian vertikal
Abstract:Abstract: In agriculture, irrigation systems are vital for enhancing water management and maximising plant growth. Effective irrigation management involves distributing sufficient quantities of water evenly to condition…
soil fertility for plants. This study aims to design a prototype that can be monitored via the Telegram app. The research methodology employs a thinking framework approach. The system is implemented using an Arduino Uno microcontroller and supporting devices, including an ESP8266 Wi-Fi module, an ultrasonic sensor, a soil moisture sensor, a stepper motor and a servo motor. Telegram serves as the monitoring tool, sending notifications connected to the Arduino via a Wi-Fi network. Test results showed that the system operates effectively: the HC-SR04 ultrasonic sensor functions as a water level reader, and the stepper motor opens and closes the water gate. Soil moisture monitoring uses a soil moisture sensor to measure the water content in the soil. If the sensor detects dry soil conditions or a moisture level below 60%, the servo motor will rotate 15° to close the water channel. Conversely, if the sensor detects wet or moist soil conditions, the servo motor will rotate 0° to close the water channel.
Keywords: arduino uno; irrigation system; soil moisture; ultrasonic sensor;
Abstract:Abstract: Water irrigation is a crucial aspect of agriculture that often becomes the primary concern for farmers, especially because suboptimal management can lead to decreased crop yields and reduced income. So far, farmers…
mers have been practicing irrigation manually, where plants are watered twice a day, in the morning and evening, based on weather conditions without considering soil temperature or moisture levels. Based on the observations conducted, it was found that excessive water application increases water accumulation, resulting in nutrient loss from the soil and even root diseases. The objective of this study is to develop a system utilizing an ESP32 microcontroller and sensors to detect soil moisture, with a machine learning-based K-Nearest Neighbor (KNN) model, enabling farmers to remotely monitor and control their crops using an Android device. The testing results showed that with input data of 32°C temperature, 40% soil moisture, and 60% air humidity, the system produced a nearest distance of 0.000 and 0.541 from the closest k-nearest neighbors, with a status label of "needs water." As a result, the relay activates the water pump to irrigate the field. Meanwhile, for data with a nearest distance of 0.897, the system identified the status as "does not need water," indicating that the soil remains wet or moist. This study is expected to help reduce farmers' workloads by optimizing water usage according to plant needs and improving crop quality and yield.
Keywords: k-nearest neighbor (KNN); mikrokontroller ESP32; machine learning; water irrigation
Abstrak: Irigasi air merupakan aspek penting dalam pertanian yang menjadi perhatian utama petani, terutama karena pengelolaan yang kurang optimal berdampak pada penurunan hasil panen dan pendapatan. Selama ini, praktik irigasi oleh petani dilakukan secara manual, di mana penyiraman tanaman dilakukan dua kali sehari pada pagi dan sore berdasarkan kondisi cuaca tanpa memperhatikan suhu atau kelembaban tanah. Berdasarkan hasil observasi yang dilakukan, ditemukan masalah yaitu pemberian air secara berlebih menyebabkan akumulasi air meningkat mengakibatkan kehilangan nutrisi tanah dan bahkan penyakit akar. Tujuan penelitian ini menciptakan sistem yang dirancang menggunakan mikrokontroler ESP32 dan sensor untuk mendeteksi kelembaban tanah, dengan model K-Nearest Neighbor (KNN) berbasis machine learning sehingga memudahkan petani untuk mengontrol tanaman mereka dari jarak jauh menggunakan android. Hasil pengujian yang dilakukan dengan data inputan berupa suhu 32°C, kelembaban tanah 40% dan kelembaban udara 60%, sistem menghasilkan jarak terdekat sebesar 0.000 dan 0.541 dari k-nearest terdekat dengan label status "butuh air". Maka relay akan mengaktifkan pompa air untuk mengairi lahan. Kemudian, pada data dengan jarak terdekat 0.897, sistem mengidentifikasi status "tidak butuh air", menunjukkan bahwa kondisi tanah masih basah atau lembab. Penelitian ini diharapkan dapat membantu meringankan beban kerja petani mengoptimalkan penggunaan air sesuai dengan kebutuhan tanaman dan meningkatkan kualitas hasil panen.
Kata kunci: irigasi air; k-nearest neighbor (KNN); mikrokontroller ESP32; machine learning
Abstract:The Tudang Sipulung tradition represents the crystallization of deliberative consensus values that persist within the agrarian communities of South Sulawesi. This study aims to describe and analyze the implementation process…
cess of the Tudang Sipulung custom in Marannu Village, Maros Regency. Employing a qualitative research method with a distinct anthropological approach, data were gathered through participant observation and in-depth interviews with key informants. The findings reveal that the execution of Tudang Sipulung in Marannu Village is not merely a ceremonial ritual but a structured forum for collective decision-making. This procession involves a synergy between traditional leaders, village government officials, agricultural extension workers, and the farming community, particularly in preparation for the rice planting season. The primary agenda includes determining planting schedules, selecting seed varieties, and managing irrigation systems to minimize the risk of crop failure. Anthropologically, this tradition serves as a medium for social integration, bridging local wisdom with technical government policies. This study concludes that the sustainability of Tudang Sipulung is a crucial factor in maintaining food security and social harmony within the Marannu Village community.