S2 Class Research Articles

Evaluasi Kesesuaian Lahan untuk Tanaman Kopi Robusta (Coffea canephora) di Kecamatan Belinyu Kabupaten Bangka

Robusta coffee (Coffea canephora) plays an important role in the national economy. Robusta coffee is one type of plantation plant that is widely cultivated by the people in Indonesia, including in Bangka Belitung. Evaluation of land suitability for robusta coffee plants is needed as land use planning that lead to more productive land use. The purpose of this study is to determine the class and distribution of actual and potential land suitability for robusta coffee plants base on order, class and sub-class levels in Belinyu District, Bangka Regency and find out recommendations of land improvement for cultivation of robusta coffee plants in Belinyu District, Bangka Regency. The study was conducted in May – September 2023 located in Belinyu District, Bangka Regency. This research uses survey methods and map analysis. The results showed that from the land area of Belinyu Subdistrict 74,812 Ha, 27,498.5 Ha of land can be developed for robusta coffee plant cultivation. The actual land suitability obtained after soil analysis is 25,781.1 Ha of land included in the S3 (marginally suitable) class and 1,717.4 Ha of land included in the N (unsuitable) class, after land improvement recommendations are made, the potential land suitability of robusta coffee plants in Belinyu District is classified into the S2 (moderately suitable) land suitability class with an area of 21,328.9 Ha, S3 (marginally suitable) 6,165.4 Ha and N (unsuitable) land area of 4.2 Ha. Limiting factors found in the research location are oxygen availability, rooting media, nutrient retention, available nutrients, erosion hazard and flood hazard. Recommendations for land improvement are the use of manure in improving soil physics, the addition of organic materials, liming and terracing

Assessing Soil and Land Suitability of an Olive–Maize Agroforestry System Using Machine Learning Algorithms

Exponential population increases are threatening food security, particularly in mountainous areas. One potential solution is dual-use intercropped agroforestry systems such as olive (Olea europaea)–maize (Zea mays), which may mitigate risk by providing multiple market sources (oil and grain) for smallholder producers. Several studies have conducted integrated agroforestry land suitability analyses; however, few studies have used machine learning (ML) algorithms to evaluate multiple variables (i.e., soil physicochemical properties and climatic and topographic data) for the selection of suitable rainfed sites in mountainous terrain systems. The goal of this study is therefore to identify suitable land classes for an integrated olive–maize agroforestry system based on the Food and Agriculture Organization (FAO) land suitability assessment framework for 1757 km2 in Khyber Pakhtunkhwa province, Pakistan. Information on soil physical and chemical properties was obtained from 701 soil samples, along with climatic and topographic data. After determination of land suitability classes for an integrated olive–maize-crop agroforestry system, the region was then mapped through ML algorithms using random forest (RF) and support vector machine (SVM), as well as using traditional techniques of weighted overlay (WOL). Land suitability classes predicted by ML techniques varied greatly. For example, the S1 area (highly suitable) classified through RF was 9%↑ than that of SVM, and 8%↓ than that through WOL. The area of S2 (moderately suitable) classified through RF was 18%↑ than that of SWM and was 17%↓ than the area classified through WOL; similarly, the S3 (marginally suitable) class area via RF was 27%↓ than that of SVM, and 45%↓ than the area classified through WOL. Conversely, the area of N2 (permanently not suitable class) classified through RF and SVM was 6%↑ than the area classified through WOL. Model performance was assessed through overall accuracy and Kappa Index and indicated that RF performed better than SVM and WOL. Crop suitability limitations of the study area included high elevation, slope, pH, and large gravel content. Results can be used for sustainable intensification in mountainous rainfed regions by expanding intercrop agroforestry systems in developing nations to close yield gaps.

INFLUENCE OF FAMILY LEVEL OF EDUCATION AND FAMILY SIZE ON STUDENTS’ DROPOUT IN SECONDARY SCHOOLS, IN KITAGWENDA DISTRICT. A CROSS-SECTIONAL STUDY.

Background Education is important to any country’s social, economic, and political development. Globally education is recognized as a basic human right. The study aims to assess the Influence of family level of education and family size on students’ dropout in secondary schools, in Kitagwenda district. Methodology A cross-sectional descriptive survey design with both qualitative and quantitative approaches. The study population consisted of teachers, head teachers, officials in the education department of Kitagwenda District, and parents who are members of the committee of PTA students s.3 and s.4. After data collection, the responses to the questionnaire were coded, and then data entered into the computer for analysis. Results Most of the respondents (90.4%) were unmarried and only (9.2%) were married. Most (200) were students from s3 and s4 classes. The majority of the respondents (82.8%) had a PLE level of education (2.8 %) had a diploma level and (5.02%) had degrees. Most (94.4%) agreed that uneducated parents encourage their sons to go to school as a way of compensation for their parents’ education in the area (Mean= 4.48; Standard deviation= 0.666). (89.6%) agreed that parents with low levels of schooling involve their children with home activities that are not academically focused, thus frustrating students who end up dropping out (Mean= 4.34; Standard deviation= 0.694). Most (90.6%) agreed that parents with bigger families have higher chances of dropping out of school (Mean= 4.45; Standard deviation= 0.646). Conclusion Children from uneducated parents are more likely to drop out of school than children from educated parents. Recommendations There is a need to revive community sensitization on the impact of education among rural people who have been noticed to be reluctant to educate their children.

Land Suitability Analysis of Mung Bean Plants (Vigna radiate L.) by Growing Degree Days Method

Mung bean (Vigna radiate L.) is one of the most widely cultivated crops after soybean and peanut. Mung beans (Vigna radiate L.) became one of the crops that experienced a decline in production amid the increase in the area of harvested land in West Sumatra. The purpose of this study was to analyze the level of land suitability of mung bean crops using the Growing Degree Days method in West Sumatra Province. The research method used in this research is Scoring and Overlay using ArcGis 10.5 software. Land suitability analysis is carried out by giving scores to several parameters of land characteristics. The parameters used are slope, land use, rainfall, soil texture and soil pH. Growing Degree Days analysis was conducted by accumulating the daily temperature values of plants based on planting scenarios. These two analyses were combined with Overlay clustering. The results showed that the land area of West Sumatra whose GDD value is optimal for mung bean growth with the level of land suitability in physical characteristics in S1 class is 15,819.29 ha and in S2 class is 877,501.06 ha. Areas that are suitable in terms of physical characteristics and values with an area of > 100 ha are Lima Puluh Kota District, Pasaman District, Solok District, and South Solok District. The best planting time for mung bean based on the planting scenario is from December to March.

ANALISIS KESESUAIAN LAHAN UNTUK KAWASAN PERMUKIMAN DI KECAMATAN DAU BERDASARKAN ARAHAN RTRW KABUPATEN MALANG TAHUN 2010-2030

Dau Sub-district is one of the sub-districts in Malang Regency that functions as a settlement development due to the urban development orientation of Malang City. This research aimed to assess the suitability of settlement land in existing conditions and based on the direction of the Malang District RTRW 2010-2030. This research was conducted using a GIS-based process with the AHP weighting method. The AHP parameters consisted of slope, rainfall, COLE index, land movement vulnerability, flood vulnerability, land use, and distance from roads. AHP processing was carried out using Expert Choice 11 software. The land suitability of Dau Sub-district settlements obtained results: S1 class covering 37,12%; S2 class 26,05%; S3 class 16,48%; N1 class 16,32%; and N2 class 4,03% of the study area. Land suitability for settlements in Dau Sub-district based on the 2010-2030 Malang Regency RTRW obtained results: S1 class covers 39,96%; S2 class 47,08%; S3 class 8,23%; N1 class 4,55%; and N2 class 0.18% of the research area. Referring to the RTRW map with existing conditions, the development of residential land has deviated by 39.25%. Areas with classes S1 and S2, which are suitable classes for the development of residential areas, dominate with an even distribution across all villages in Dau Sub-district. The main inhibiting factors affecting the suitability value are slope and disaster vulnerability.

Evaluasi Kesesuaian Lahan untuk Tanaman Jagung (Zea mays L.) di Kecamatan Dulupi Kabupaten Boalemo

Dulupi is one of the districts in Boalemo Regency which is a center for maize production, but the high intensity of maize cultivation causes a decrease in the quality of the local land. This research aimed to determine the land suitability classes and limiting factor for maize (Zea mays L.). The research was carried out in Dulupi District of Boalemo Regency from September to Desember 2022. It employed a data matching method, matching the data for each land unit with suitability criteria. The findings revealed that the level of the land suitability for maize in Dulupi District, Boalemo Regency had theree classes of land suitability, namely moderately suitable (S2) of 88% (6314,54 Ha), marginally suitable (S3) of 10% (763,89 Ha), and not suitable (N) of 2% (41,15 Ha). In contrast, the yield-limiting factors were nutrient retention, avaible nutriens (N, P, K), erosion hazard, drainage, and effetive depth. With the improvment efforts, the yield limiting factors in the potential land and suitability increased to S2 and S3 classes.

LOCATION SUITABILITY AND PERFORMANCE OF FRESHWATER FISH FARMING IN FLOATING NET CAGES AT THE PAMARAYAN DAM, SERANG, BANTEN

The Pamarayan Dam is located in Cikeusal District, Serang Regency, Banten Province where many freshwater fish cultivators based on floating net cages are found. Important aspects that are assessed in aquaculture activities are measuring water quality, location suitability, and productivity. This study aimed to determine the site suitability criteria and analyze the existing performance of fish farming activities with floating net cages. The research was conducted from January to March 2023 at the Pamarayan Old Dam at 4 stations. Water sampling was carried out in situ and ex situ including temperature, pH, DO, TDS, current, brightness and depth, BOD, COD, total P, total N, TSS, and ammonia. Water quality analysis was carried out at the DLH laboratory in Serang City and UPT LABKES in Serang Regency. Additional data by conducting interviews with cultivators. The results showed that the Pamarayan Dam had suitability in the S2 class (appropriate) at all stations. This is based on water quality, most of which are still in accordance with class 3 quality standards including parameters of temperature, pH, BOD, TSS, DO, COD, total P, and ammonia. Cultivation performance at the Pamarayan Dam has a large advantage, where the average net profit per cultivation cycle is Rp. 41.332.000.

Utilization Technology Spatial in Making Class Maps Suitability of Mango Plantation Land in Kakas District, East Coast Minahasa

Land suitability evaluation is very important in the process of matching land types for specific uses. This research aims to create map of the distribution of land suitability classes for mango plants in Kakas District using technology Spatial . This research was carried out using field survey and geoprocessing methods . Data collection techniques include: documentation , observation and analysis laboratory . Determination class suitability land use method from FAO ie matching observation variables that is condition grow plant Mango and its qualities / characteristics land . In this study, 22 units were obtained land map (SPL) covering an area of 3927.07 Ha spread over several village in Kakas District . Class map suitability resulting land _ that is class suitability S1 land (very suitable ) for criteria nutrient retention and available nutrients . Whereas criteria temperature and rooting media included in class suitability S2 land ( enough appropriate ) scattered and for criteria water availability and levels danger erosion generally enter the S3 class ( according to marginal) spread across all SPL. Temporary level danger erosion is criteria give class N ( no appropriate ) for plant mango at 10 ( ten ) SPL with area 1351.93 Ha.

Land suitability study for sweet sorghum (Sorghum bicolor (L.) Moench) farming in Pleret Yogyakarta

Marginal land and geological disaster-prone in the Opak Fault zone area need to be studied for the basic potential for the development of multi-purpose crops for food, feed, and renewable energy. The study was aimed to determine the potential of the soil and evaluate the suitability of the land for sweet sorghum (Shorgum bicolor) crop in Gunung Kelir, Pleret District, Bantul, Yogyakarta as part of the Opak Fault line. A total of 20 sample points were collected based on geological data, land use, slope, and administrative maps. Analysis of soil physical and chemical properties was carried out to classify soil types and land suitability for sweet sorghum plants. The developing soils in the study area were originated from volcanic breccias, Young Merapi Volcano, and the alluvial of the Opak River, with included in orders of Entisols and Inceptisols. The cation exchange capacity of soils that develop from volcanic breccias is higher than those that develop from Merapi volcanic soils. Suitability of land for sweet sorghum plants includes S2 class with limiting factors for nutrient retention, temperature, and erosion hazard area of ± 24,011 Ha (76.23%), S3 class with limiting factors for erosion hazard and surface stonies of ± 3.85 Ha (12.22%), and N class with a root zone constraint of ± 0.139 Ha (0.44%), and others are not agriculture. Based on the results of this study it is expected that sweet sorghum is able to be developed in the Opak Fault zone to enhance the use of marginal land.

Prognostic biomarkers in and selection of surgical patients with hepatocellular carcinoma.

Prognostic biomarkers in and selection of surgical patients with hepatocellular carcinoma.

Studi Kelayakan Lokasi Budidaya serta Pembuatan Masterplan di Kampung Perikanan Desa Patra Tani, Muara Enim, Sumatera Selatan

Kampung Perikanan Desa Patra Tani is located in Muara Enim Regency, precisely in Muara Belida district, a location that was once a place for aquaculture but the lack of care and management in that location has now become neglected. The objective of this research is to analyze the feasibility of land and make a master plan in Kampung Perikanan Desa Patra Tani, Muara Enim, South Sumatra as a location for aquaculture. Field observation activities include indirect (in situ) and direct (ex situ) water quality measurements at five observation stations, soil sampling, mapping using GPS, and market availability surveys. The results of data analysis on water quality using the scoring method show that in Kampung Perikanan Desa Patra Tani tends to be in the S2 class (moderately suitable) meaning that it has a few limiting factors in the waters so that several treatments are needed before cultivating. One of the commodities that are suitable for cultivation is tilapia because of high market demand is suitable to fill the shortage.

Noise simulation in classification with the noisemodel R package: Applications analyzing the impact of errors with chemical data

AbstractClassification datasets created from chemical processes can be affected by errors, which impair the accuracy of the models built. This fact highlights the importance of analyzing the robustness of classifiers against different types and levels of noise to know their behavior against potential errors. In this context, noise models have been proposed to study noise‐related phenomenology in a controlled environment, allowing errors to be introduced into the data in a supervised manner. This paper introduces the noisemodel R package, which contains the first extensive implementation of noise models for classification datasets, proposing it as support tool to analyze the impact of errors related to chemical data. It provides 72 noise models found in the specialized literature that allow errors to be introduced in different ways in classes and attributes. Each of them is properly documented and referenced, unifying their results through a specific S3 class, which benefits from customized print, summary and plot methods. The usage of the package is illustrated through four application examples considering real‐world chemical datasets, where errors are prone to occur. The software presented will help to deepen the understanding of the problem of noisy chemical data, as well as to develop new robust algorithms and noise preprocessing methods properly adapted to different types of errors in this scenario.

A study of land suitability for developing corn in West Sumatra: an approach of GIS-based multi-criteria and legacy soil data

In 2020 Indonesia imported 911,194 tons of corn. Therefore, each region needs to optimize their land-use. One of the potential areas for corn development is in West Sumatra. Therefore, this research was conducted with the objectives of a) assessing land suitability for corn and b) analyzing limiting factors and alternatives for land improvements. The geodatabase analysis used an approach of GIS-based multi-criteria and legacy soil data. Land suitability was analyzed using the Matching method with classes highly suitable (S1), moderately suitable (S2), marginally suitable (S3), and not suitable (N). The results showed that 33.9% of the land in West Sumatra was suitable for corn cultivation (1,210,592.9 ha). The suitability class consisted of an S1 of 169.5 ha, an S2 class of 143,761.2 ha, and an S3 class of 1,066,662.2 ha. As much as 66% of the land was not suitable for corn cultivation due to slope factors and rooting media. The S2 and S3 classes had main subclasses S2.tc.wa.eh widely distributed in Dharmasraya and Sijunjung, S3.wa.oa in Pesisir Selatan, and S3.wa in West Pasaman. The limiting factors of subclasses S2 and S3 of corn in West Sumatra were due to high rainfall, steep slopes, and poor drainage.

Evaluation of land suitability for cocoa (Theobroma cacao L) in Kebonagung District, Pacitan Regency, East Java, Indonesia

Pacitan Regency is one of the potential areas for the development of cocoa (Theobroma cacao L). Plants need certain conditions to produce optimally. Land suitability is a way to find out whether land conditions in Kebonagung District are suitable or not for cocoa plants. This study evaluates land suitability for cocoa plants in Kebonagung District, Pacitan Regency. The research was conducted using descriptive method through a survey approach. Based on the overlay of soil type maps, topographic maps, rainfall maps, and administrative maps, ten land map units (LMU) were obtained. Morphological analysis and soil characteristics were carried out qualitatively in the field and quantitatively in the laboratory. Determination of land suitability is done by matching the characteristics of the land with the conditions for growing cocoa plants. The results showed that at LMU 2, 3, 4, 5, 6, 8, 9, and 10 were moderately suitable for the class of land suitability, while LMU 1 and 7 were marginally suitable. The limiting factors are the length of the dry month, humidity, pH, available potassium, base saturation (BS), erosion hazard and slope. After improving the limiting factor, the potential land suitability class was obtained in the S2 class (moderately suitable) for all LMUs.

EVALUASI KESESUAIAN LAHAN UNTUK TANAMAN JAGUNG (Zea mays L.) DI KECAMATAN POPAYATO KABUPATEN POHUWATO

Utilization of land resources requires information of the potential and limitations of land use so that the commodity that will be cultivated can achieve optimal yields. The aim of this study was to determine land suitability class of maize (Zea mays L.) of agriculture land in Popayato District, Pohuwato Regensy. This research was conducted from July 2022 to December 2022. Land suitability classes, both actual and potential, were determined based on the matching method between land characteristics of each land unit with the land suitability criteria for maize. The results showed that the actual land suitability class for maize in Popayato District was dominated by marginally suitable (S3 class) respectively at about 95.32% and not suitable (N class) about 4.68% of total area. Limiting factors consisting of class S3 includes: rainfall and humidity, soil depth, base saturation and pH, while the limiting factors in class N was soil depth. After improvement efforts were made, the potential land suitability class for maize plants became S3 class for all land units with an area of 3,587.37 ha.

Indirect and direct land evaluation for red chili on low fertility soil under high annual rainfall with significant dry periods

The red chili productivity highly depends on land suitability, climate factors, and cultivation practices. Some cultivation engineering has been implemented and continues to be developed to curb problems of land with unsuitable actual soil conditions. The same approach is also taken to overcome rainfall constraints, by using mulch to optimize soil moisture. This study aims to assess and directly measure the productivity of red chili on land with good soil physic but requires chemical amelioration and has high annual rainfall. The research location is part of the Cikabayan Educational Field (CEF). Land suitability evaluation concept of FAO with the BBSDLP criteria was used to classify the land suitability for red chili. The growth of chili was monitored by observing 45 random samples, and the yield was measured based on the harvest of all plants. The result showed that the actual land suitability of the CEF for red chili was S3. The land suitability from a direct assessment based on the actual harvest until the plant age reaches four months, also show the S3 class. When the actual yield was extrapolated to three more months of yield prediction (ideal red chili productive period), the suitability class was counted as S2.

Characterization of Sulfides in Atmospheric Residue Fractions Using Selective Oxidation Followed by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

An improved analytical method was developed for identifying sulfide compounds from aromatic fractions in Lungu atmospheric residue (LGAR). Sulfides in residue aromatics were selectively oxidized into sulfoxides using tetrabutyl ammonium periodate (TBAP) and identified by positive-ion Electrospray Ionization Source (ESI) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Results showed that sulfides with lower polarity in LGAR aromatics could effectively ionize in ESI using this approach. Additionally, the oxidized sulfides were mainly S1 and S2 class species. The most abundant oxidation-generated sulfoxides O1S1 and O1S2 in LGAR aromatics had DBE values of 3~10 and 8~12, respectively. The S2 class species, whose condensation degree was higher than that of S1, were likely in the form of containing both cyclic sulfides and thiophenic compounds.

Land Suitability Analysis as a Tool for Evaluating Soil-Improving Cropping Systems

Agricultural land use planning is based on the capacity of the soil to support different types of crops and is a prerequisite for better use of cultivated land. Land Suitability Analysis (LSA) is used to measure the level of suitability of growing a specific crop in the area and can also be used to evaluate future scenarios as a means for sustainable agriculture. LSA was employed to calculate current land suitability, as well as four scenarios of Soil-Improving Cropping Systems (SICS): (a) Conservation Tillage (CT), (b) Cover Crop (CC), (c) Crop Residue Management (CRM), and (d) Manure Application (MA). The scenarios of SICS were derived by increasing soil organic matter and cation exchange capacity values depending on the SICS hypothetically applied for a period of 100 years in the future. LSA was evaluated for maize in three sites: (a) Flanders (BE), (b) Somogy (HU), and (c) Hengshui (CH). LSA was performed using the Agricultural Land Use Evaluation System (ALUES) considering soil and climatic and topographic parameters. Weighing factors of input parameters were assigned using the Analytical Hierarchy Process (AHP). The results show that in Flanders, the highly suitable (S2) class covered 3.3% of the total area, and the best scenario for improving current LS was CRM, in which S2 expanded to 9.1%. In Somogy, the S2 class covered 18.3% of the total area, and the best scenarios for improving current land suitability were CT and CC, in both of which the S2 class expanded to 70.5% of the total area. In Hengshui, the S2 class covered 64.7% of the total area, and all SICS scenarios performed extremely well, converting almost all moderately suitable (S3) areas to S2. The main limiting factor that was recognized from a limiting factor analysis in all cases was the climatic conditions. This work proves that LSA can evaluate scenarios of management practices and recognize limiting factors. The proposed methodology is a novel approach that can provide land suitability maps to efficiently evaluate SICS scenarios by projecting soil characteristics and LSA in the future, thus facilitating management decisions of regional policy makers.

STUDY ON POTENTIAL FEASIBILITY OF AQUACULTURE LAND USING GEOGRAPHIC INFORMATION SYSTEM (GIS) IN NORTH SEMARANG SEA

Marine culture in the North Semarang area is still not optimally utilized by the surrounding community. The selection of the location of aquaculture activities is needed to determine the feasibility of suitable land for aquaculture in the sea. However, due to the large number of fishing activities, ports, and dense settlements have an impact on water quality which affects marine aquaculture activities. The purpose of this study was to determine the condition of the waters, determine the level of land suitability using GIS, and the area of ​​land that can be used as a location for marine culture in the waters of North Semarang. The method used is by scoring and GIS. Parameters observed included protection, brightness, temperature, depth, current velocity, substrate, wave height, salinity, DO, BOD, COD, and pH. Furthermore, a scoring calculation is carried out to determine the suitability value which is then processed using GIS to produce a suitability map. The results showed that North Semarang waters were classified as S2 class (quite suitable) for marine aquaculture activities and with an area of ​​250,000 ha

Modeling crop suitability under micro irrigation using a hybrid AHP-GIS approach

Crop suitability analysis using novel models is a pillar for sustainable land-use planning. In this work, the analytical hierarchy process (AHP) was integrated with GIS to produce suitability maps for wheat and maize under sprinkler irrigation and broad bean under drip irrigation. The study was conducted in an arid area, west Nile Delta of Egypt. The characteristics of local climate, landscape, and groundwater quality were matched with crop requirements and assigned scores. A GIS-based model was implemented to integrate scores and AHP weights and generate crop suitability maps. The climate conditions fitted optimum crop requirements; however, slight slope limitations affected wheat and maize. The electrical conductivity (EC), exchangeable sodium percentage, and CaCO3 were the most important soil factors affecting broad bean, and these factors besides coarse fragments affected wheat and maize. The EC, Na+, and Cl– were the most influential factors for wheat and maize irrigation, while EC and sodium adsorption ratio had the greatest priority for broad bean irrigation. Irrigation water quality had the highest specific weight (0.38) followed by soil (0.36), slope (0.15), and climate (0.10). The final suitability maps showed that 97 and 3% of the total area were suitable (S2) and moderately suitable (S3) for wheat, respectively. Moreover, 85 and 15% of the total area fitted the S2 and S3 classes for broad bean. For maize, 36 and 64% of the total area fitted the S2 and S3 classes. Integrating AHP and GIS would provide effective land-use planning and also suggest proper management practices in arid areas.