Cocoa (Theobroma cacao L.) is one of the leading commodities that developed in quality and quantity. Efforts through socialization and counseling in the field of cocoa cultivation for the farmers are always reminding know the importance of identifying symptoms from pest attacks could earlier makeup so that preventive actions that do not damage the environment or agricultural land. The study aims to create an early detection system based on image processing on symptoms of pest attacks on cocoa fruits. The early detection system involves training the data and test the data as a result of capture pictures of ordinary cocoa fruits and reviews those attacked by pests in real time at the location of cocoa plantations. Image processing techniques are integrated into the application software to be Able to identify the pixel characteristics of capture images of cocoa fruits. The results of the study showed that the ability of the system to detect the symptoms of pests in training the data was 100% and the test of data was 70%. This result showed that the applications could be recommended to be developed on a larger scale so that it will be helpful for cocoa farmers.

Cocoa as leading plantation commodities, which is quite essential for the national economy that decreasing productivity from 2012 to 2018. The low productivity of cocoa is caused by the fact that cocoa plants that are planted do not meet the optimum growth requirements. Land quality as an optimal growth factor varies greatly in land and time quality, so it requires an in-depth study, one of which is the parametric approach. This approach analyzes the land requirements (soil and climate) for the suitability of specific cocoa plantations in particular regions, so this study aims to determine the characteristics of the land that correlate with cocoa productivity in a specific region. Also, this study aims to establish a land index through a deductive parametric approach in the PolewaliMandar Regency as a sample of research locations. Primary data were obtained from direct observation, while secondary data were obtained from related institutions. In addition, the determination of the profile location based on production data and cocoa crop distribution through satellite imagery and the Global Positioning System (GPS). Qualitative and quantitative analysis using regression data analysis was used. The results showed that the climate and soil conditions of the Polewali Mandar Regency were very suitable for the level of land suitability. All parameters tested in this study illustrate that land characteristics (climate and soil) in the PolewaliMandar Regency is very suitable for the optimum growth requirements of cocoa plants.

Cocoa is the main plantation crop in Indonesia after rubber and oil palm. Indonesia’s cocoa production is the sixth-largest after Ghana and Ivory Coast. Cocoa cultivation spreads to almost all islands in Indonesia. However, the largest is on the island of Sulawesi. West Sulawesi is one of the largest cocoa producers in Indonesia. The decline in cocoa production has continued since 2012. One of the causes of the decline in cocoa production is a decrease in acreage and low productivity of the cocoa plant. The current average cocoa productivity is only 797 kg/ha/year. This productivity is very low compared to the optimum productivity, reaching 2,000-3,000 kg/ha/year. One of the causes of low productivity is uneven land suitability. Cocoa is grown on land with a poor land index. This study aims to study the land index in West Sulawesi to develop land suitability for cocoa plants. His research took place in January-August 2020. The collection of representative points consisted of 30 points spread over four districts in West Sulawesi, namely Polewali Mandar, Majene, Mamuju and Mamasa Regencies. The results showed that there was a strong correlation between land index values and cocoa productivity. Each increase in the land index will increase the productivity of specific cocoa plants for the West Sulawesi Region. The highest Land Suitability Index value (53.56) was obtained on land with cocoa productivity of 2,000 kg/ha/year. The lowest Land Suitability Indexvalue is obtained on land with a 700 kg/ha/year productivity.

As Indonesia is one of the largest cocoa producing countries in the world, cocoa plays an important role in the Indonesian economy. However, cocoa bean production has continued to decline since 2012 in several cocoa producing regions in Indonesia, including West Sulawesi. The main problem for cocoa in Indonesia is the low productivity of the plants. The average productivity of cacao cocoa plants in West Sulawesi in 2019 was only 797 kg/ha/year. The productivity of the cocoa plants can reach 2,000-3,000 kg/ha/year. One of the causes of the low cocoa plant productivity of their cocoa plant is the mismatch between plant needs of and with soil chemical properties. This study uses quantitative methods with a deductive approach. Theis research took place in four districts in West Sulawesi, namely : Polewali Mandar, Majene, Mamasa and Mamuju Regencies. The determination of the 30 sampling point stations to provide representative profiles was based on cocoa productivity data. The results showed that there was a significant correlation between cation exchange capacity (CEC) and cocoa productivity. The amount abundance of exchangeable bases cations (Ca+, Ma+ and K+) hads a significant effect on cocoa plants in the high productivity category . There was a negative correlation between salinity for and cocoa plant productivity in the high (1500-2500 kg/ha/year) and low (<800kg/ha/year) productivity categories productivity category (1500-2500 kg / ha / year. Higher salinity causes lower productivity of cocoa plants. Likewise in the low productivity category (<800kg/ha/year). There was no correlation between pH H2OH2O pH with and cocoa productivity at all the representative profile points stations. There was a positive correlation between pH H2O pH and four other soil chemical characteristics, namely: C-Organic carbon, salinity, base saturation and the abundance of the number of exchangeable base cations can be exchanged.