Masters of Science

URI for this collectionhttps://rps.wku.edu.et/handle/987654321/9

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Start date: 2021Has files: Yes

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    DETERMINATES OF MARKET SUPPLY OF COFFEE BY SMALLHOLDER FARMERS IN MESKAN DISTRICT, EAST GURAGE ZONE, ETHIOPIA
    (wolkite universty, 2025-09) BELAYNEH KASSA NIBERIE
    This study aimed to assess the determinants of market supply of coffee by smallholder farmers in Meskan Woreda, East Gurage Zone, Ethiopia. A survey of 386 households was conducted using simple random sampling methods during the 2014/15 Ethiopian calendar year. The study used structured questionnaires to collect primary data, which were analyzed using descriptive and inferential statistical techniques, including multiple linear regression and chi-square tests. The results revealed that factors such as the sex of the household head, family size, livelihood diversification strategies, access to irrigation, and average annual coffee production significantly influenced the market supply of coffee. The chi-square test further indicated a significant relationship between the market supply of coffee and factors like livelihood diversification strategies, access to irrigation, access to credit, proximity to markets, cooperative membership, and access to infrastructure. The study found that 63.2% of the variation in coffee supply to the market could be explained by these factors. The study recommends targeted policies and interventions to enhance the productivity of coffee farmers, including improving access to irrigation and credit, providing training and support, fostering collaboration, and encouraging diversification to ensure a steady supply of coffee to the market while promoting sustainable agricultural practices.
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    THE EFFECT OF ACTIVE LEARNING METHOD ON GRADE TEN STUDENTS IN THE ACHIEVEMENT OF CHEMISTRY: THE CASE OF ROMAN DEGA SECONDARY SCHOOL, KEDIDA GAMELA, KAMBATTA ZONE, CENTERAL ETHIOPIA REGION, ETHIOPIA
    (wolkite universty, 2024-12) SEWUNET SAMUEL WANORE
    Active learning requires students to do meaningful learning activities and think about what they are learning. This study aimed to investigate the effect of an active learning method on Grade 10 students in the achievement of Chemistry. The research was conducted at Roman dega Secondary School, kedida Gamela, Central Ethiopia Region. For the study purpose, a quasi-experimental design was employed. By using simple random sampling technique, 72 students were selected as a sample size from a total population of 360. Also 7 chemistry teachers, 3 the school principals and 1 supervisor were included in the study .A stratified sampling technique was used to maintain the proportional allocation of students from each section. The sampled students were assigned to two groups: experimental (N (exp) = 36) and control (N(con) = 36). The experimental group received instruction with active learning methods such as group discussion, question and answer, problem solving, experimental and visual-based learning. In contrast to that, the control group was taught with the traditional lecture method from the same chapter of "Energy Change and Electrochemistry" by the same teacher. The application took seven weeks. At the beginning of the first week, a pretest was administered for both groups. A post test was given for both groups at the end of the seventh week. To ensure the validity of the tool, the test was presented to the study advisor and four experienced high school teachers. The data obtained was analyzed using SPSS version 20. A T-test was used to test the statistical significance of the hypothesis generated in the study. The significance level of the results was tested at alpha = 0.05 significance level. Results showed that there was a significant difference between the means of experimental group pretest and post test ( p ≤ 0.05) in the achievement of chemistry. But there was no significant difference between the means of the control group pretest and post test after intervention (P > 0.05). Questionnaires were also administered before and after the intervention. The findings of the study revealed that incorporating an active learning approach in chemistry enhanced the learning achievement of 10th grade students. In light of the obtained results, the researcher recommended the utilization of an active learning method in teaching chemistry so as to enhance students’ achievement in chemistry and positive perceptions towards chemistry.
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    THE IMPACT OF PRACTICAL LEARNING ON STUDENTS ACHIEVEMENT IN CHEMISTRY. THE CASE OF ADELE SECONDARY SCHOOL
    (wolkite universty, 2024-12) MULUGETA GOSSAYE TEKA
    The purpose of this study was to investigate the impact of practical work in enhancing students’ achievements in chemistry in Adele secondary school particularly in grade 10, Sodo Woreda East Gurage zone, Centeral Ethiopia. To achieve this objective i.e. to examine impact of practical learning on students’ performance in chemistry, and on the students attitude toward chemistry; this study was employed quasi-experimental design. among a total of six targets secondary school in Sodo Woreda Adele secondary school was selected purposively. 80 students as a sample size out of 600 total populations were selected by using random sampling method. To keep the proportional allocation of students from each section, stratified sampling technique was used. The sampled students were placed in to two groups; experimental group and control group. Both the groups were exposed to the pre-test. The experimental groups were taught using the practical approach for eight week while the control groups were taught using the conventional method. The study used three instruments namely chemistry achievement tests, students’ attitude questionnaires and observation checklists were used as a data collection tools. at the beginning of the first week, both groups give the pre-test chemistry achievements and the post-test achievements test at the end of the eight week. The data obtained were analyzed using SPSS version 20. T-test was used to test the statistical significance in the hypothesis generated in the study. The significance of the results was tested at α = .05 significance level. The findings of the students showed that practical approach resulted in higher students’ achievements in chemistry and lead to improved students’ attitude towards chemistry. The study concluded that, practical instructional approach towards chemistry is an effective teaching method which chemistry teachers should be encouraged to use to enhance students’ achievements in the subject. The study recommended adoption of the practical teaching approach in order to enhance students’ achievements and improve students’ attitude towards the subject.
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    THE EFFECT OF MARKETING MIX ELEMENTS ON CUSTOMER SATISFACTION: A COMPARATIVE STUDY ON SELECTED COMMERCIAL BANKS IN GURAGE ZONE
    (wolkite universty, 2025-08) MINTESNOT FIKRE
    The function of bank marketing mix is to act more as an "enabler" than as a provider of services. The objective of the study was to determine the effect of marketing mix elements on customer satisfaction: a comparative study on selected commercial banks in Gurage zone. The survey, which comprised a sample of 311 respondents, provided the information for the study through questionnaire. Comparative study of the service marketing tactics (7Ps) used by 3 private sector banks and 1 public sector banks in Gurage zone, Ethiopia. Moreover, both primary and secondary data were used in this method of descriptive analytical based approach study. The correlation analysis shows that there is positive and significant relationship between the marketing mix and customer satisfaction. The regression's findings showed that the R square value 0.707, this demonstrates that 70.7% of the variance in customer satisfaction can be attributed to the marketing mix. Descriptive statistics of marketing mix elements, customer satisfaction levels, reliability tests, correlation analysis, and regression results, with a focus on comparative insights. The descriptive result of the study indicates Awash Bank led in customer satisfaction due to strong People and Process performance. CBE lagged due to high service charges and slow processes. NIB struggled with loan accessibility and complaint resolution. BoA performed moderately but faced technology-related complaints. The study recommended the need for the Bank to continue to improve on these significant strategies as well as improving on other strategies that could attract, meet and exceed customer expectations such as enhancing transaction process flow, loan accessibility and providing the latest technological innovations to ensure error free transactions.
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    INTEGRATED EFFECTS OF VERMICOMPOST AND NPS FERTILIZER ON SELECTED SOIL PHYSICOCHEMICAL PROPERTIES AND YIELD AND YIELD COMPONENTS OF ONION CROPS IN MESKAN WOREDA, EAST GURAGE ZONE, CENTRAL ETHIOPIA.
    (wolkite universty, 2025-08) MEKONEN ASEFAARGAW
    The reduction in soil fertility caused by nutrient depletion poses a significant challenge for lowinput crop production across many regions of Ethiopia. Onion (Allium cepa L.) exhibits a notable response to the application of NPS and vermin compost (VC) fertilizers. However, the optimal dosage of these fertilizers has yet to be determined in the study area. Additionally, there is limited understanding of their impact on soil properties and onion yield, primarily due to the low usage rates of both organic and mineral fertilizers by local farmers. Consequently, this study aims to examine the effects of combining vermin compost with NPS fertilizer on the physicochemical properties of the soil, as well as the yield and yield components of onion (Allium cepa L.). The research was conducted in the Dobbi Kebele of the East Gurage Zone, under irrigated conditions. The experimental design included factorial combinations of five NPS rates (0, 100, 200, 300, and 400 kg NPS ha-1 ) and three vermicompost rates (0, 2.5, and 5 tons ha-1 ), arranged in a randomized complete block design (RCBD) with three replications. Soil samples were analyzed for texture, bulk density, pH, total nitrogen, available phosphorus, sulfur, organic carbon, cation exchange capacity, organic matter, and exchangeable bases (calcium, magnesium, potassium, and sodium). The yield and its components were also assessed. The results from the soil analysis conducted from before and after crop harvest indicated that the application of vermicompost significantly (p available phosphorus (from 4.86 to 10.77), available sulfur (from 35.99 to 52.94),cation exchange capacity (from 37.98 to 78.68), and exchangeable potassium (from 0.55 to 1.64). These analyses were performed using SAS software version 9.4, employing analysis of variance. The study demonstrated that the application rates of NPS and VC, along with their interaction, had an impact on various phonological and yield parameters of onion crops. Specifically, factors such as neck thickness of the bulb (cm), the interaction of NPS and VC on days to maturity, and bulb length (cm) were favored, while the effect of NPS fertilizer on bulb length was found to be non-significant. Both fertilizers and their interaction influenced all selected physical and chemical properties of the soil following the harvest of onion crops. Notably, the highest marketable bulb yield (32.78 ton ha-1 ) and total bulb yield (33.33 ton ha-1 ) were recorded from the combination of 400 kg NPS ha-1 with 5 ton VC ha-1 . The largest bulb diameter (7 cm) and the highest average bulb weight (120 g) were also achieved with this interaction. The application of 100-400 kg NPS ha-1 combined with 2.5-5 ton of VC ha-1 resulted increases in organic carbon, total nitrogen, available potassium, available phosphorus, and cation exchange capacity compared to the control treatment. Consequently, it is concluded and recommended that the application of 5 ton VC ha-1 in conjunction with 400 kg of NPS ha-1 enhances soil physicochemical properties and onion crop yields in Meskan Woreda, East Gurage Zone. The highest marginal rate of return (MRR%) of 10855% was observed for plots receiving 100 kg NPS ha-1with 2.5 ton VC Ha-1 , while the highest adjusted marketable bulb yield of 32.78 ton ha-1 , along with the greatest net benefit and benefit-to-cost ratio of 1,204,612 Birr ha-1 and 108.55 Birr ha-1 , respectively, were recorded for plots treated with 400 kg NPS ha-1 combined with 5 ton of vermicompost for the production of Bombay red onions in Meskan Woreda.
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    DEVELOPING PART OF SPEECH TAGGINGMODELFORDAWUROOTSUWA LANGUAGE USING DEEP LEARNINGAPPROACH
    (wolkite universty, 2025-08) DAWIT DESTA DAEMO
    Part-Of-Speech tagger is a program that reads text in given language and assigns parts-of-speech such as noun, verb, adjective, etc. to each word and other token within the text. Previous study done on Part of speech tagging for other language as we reviewed there are several gaps such as high variance in training & testing datasets, when segmenting preposition and conjunction the morphology indicating gender, person, number and other information are missed. By incorporating this issue developing POS tagger forDawurootsuwa language using RNN based deep learning approach such as RNN, LSTM, GRU, Bi-LSTM and Bi-GRU with pre-trained FastText embedding done. To achieve this, we collected a dataset of 1251 sentences comprising 19,897 tokens and 7067 unique words, establishing a robust foundation for the NLP corpus. Our methodology includes comprehensive data collection, corpus development, data preprocessing, and application of deep learning techniques to train and evaluate models. Through experimentation, various deep learning models were evaluated for their ef ectiveness in POST for Dawurotsuwa, including Sequential and non-sequential Recurrent Neural Networks with pre-trained Fast Text embedding’s, as well as models like LSTM, GRU, Bi-LSTM, and Bi-GRU withFastText embedding’s. The Sequential Bi-GRU model delivered the best performance, achieving 97.43% accuracy on training data, 97.57% on validation data, and 97.79%on testing data. The model’s loss values were 0.09 for training, 0.08 for validation, and0.07fortesting, with weighted Average precision, recall, and F1-score reaching 94%, 93%, and93%, underscoring the model’s robustness. These findings indicate that deep learning models, especially Bi-GRU with Fast Text embedding’s, significantly improve POST performance forunder-resourced languages like Dawurotsuwa language.
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    DEVELOPING PART OF SPEECH TAGGINGMODELFORDAWUROOTSUWA LANGUAGE USING DEEP LEARNINGAPPROACH
    (wolkite universty, 2025-08) DAWIT DESTA DAEMO
    Part-Of-Speech tagger is a program that reads text in given language and assigns parts-of-speech such as noun, verb, adjective, etc. to each word and other token within the text. Previous study done on Part of speech tagging for other language as we reviewed the rear several gaps such as high variance in training & testing datasets, when segmenting preposition and conjunction the morphology indicating gender, person, number another information are missed. By incorporating this issue developing POS tagger for Dawurootsuwa language using RNN based deep learning approach such as RNN, LSTM, GRU, Bi-LSTM and Bi-GRU with pre-trained Fast Text embedding done. To achieve this, we collected a dataset of 1251 sentences comprising 19,897 tokens and 7067 unique words, establishing a robust foundation for the NLP corpus. Our methodology includes comprehensive data collection, corpus development, data preprocessing, and application of deep learning techniques to train and evaluate models. Through experimentation, various deep learning models were evaluated for their ef activeness in POST for Dawurotsuwa, including Sequential and non-sequential Recurrent Neural Networks with pre-trained Fast Text embedding’s, as well as models like LSTM, GRU, Bi-LSTM, and Bi-GRU with Fast Text embedding’s. The Sequential Bi-GRU model delivered the best performance, achieving 97.43% accuracy on training data, 97.57% on validation data, and 97.79%ontesting data. The model’s loss values were 0.09 for training, 0.08 for validation, and0.07fo testing, with weighted Average precision, recall, and F1-score reaching 94%, 93%, and93%, underscoring the model’s robustness. These findings indicate that deep learning models, especially Bi-GRU with FastText embedding’s, significantly improve POST performance founder-resourced languages like Dawurotsuwa language.
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    ASSESSING AVAILABILITY AND UTILIZATION OF LABORATORY FACILITIES FOR TEACHING CHEMISTRY IN SECONDARY SCHOOLS OF SELECTED WOREDAS IN EAST GURAGE ZONE, CENTRAL ETHIOPIA.
    (wolkite universty, 2024-12) ABU TESFAYE GEDA
    Laboratories are of the utmost importance in the teaching and learning of science subjects, including chemistry. This study was premised on assess the availability; evaluate the utilization of laboratory facilities for teaching chemistry. The studies that would be used were a descriptive survey study conducted in East Gurage Zone Selected Woredas. It targeted a population of 12 public secondary schools, from which seven secondary schools, 8 chemistry teachers, 7 head of chemistry department, 320 chemistry students from each sampled schools top ten students and 4 laboratory technicians were selected using a combination of simple random sampling and purposive sampling techniques. Questionnaires, interview schedules and observation schedules were used to collect data, which was analyzed using descriptive statistics quantitatively percentages, frequencies, and means with the aid of the Statistical Package for Social Sciences version 20 and qualitatively using words. The study revealed that schools had laboratory room with storage space, space for class work and sample preparation room but, they lack most common facility such as, equipment, sufficient chemicals and well trained manpower. Teachers were found to prefer demonstrations and students were not familiar with use of common apparatus and therefore could not be in a position to handle a practical activities. Insufficient availability of chemistry laboratory resources and its ineffective utilization was one of the major causes of students‟ poor performance in chemistry in the study area. It is recommended that all schools should have adequately equipped laboratories; qualified technicians should be employed to support the teachers‟ work to enable proper utilization of the laboratories. Students be given sufficient opportunity to be engaged in practical lessons in secondary schools will enhance good performance in practical work and ultimately the overall chemistry grades in internal and national examinations
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    END-TO-END SPEECH RECOGNITION FOR GURAGIGNA LANGUAGE USING DEEP LEARNING TECHNIQUES
    (wolkite universty, 2025-08) ABDO NESRU EBRAHIM
    Speech recognition entails converting long sequences of acoustic features into shorter sequences of discrete symbols, such as words or phonemes. This process is complicated by varying sequence lengths and uncertainty in output symbol locations, making traditional classifiers impractical. Current automated systems struggle with speaker-independent continuous speech, particularly inlow-resource languages like Guragigna, where the Cheha dialect poses additional challenges dueto its purely spoken nature and lack of a rigid grammatical structure. To address these issues, this research develops an end-to-end speech recognition model utilizing deep learning techniques, specifically a hybrid CNN-BIGRU architecture combined with CTC and attention mechanisms. This approach aims to enhance alignment and robustness in noisy environments. To train and testthe model, a text and speech corpus was created by compiling dataset from different sources likein Wolkite FM, the Old and New Testaments. Experimental results indicate that the CNN-BIGRU model achieves a Word Error Rate (WER) of 2.5%, showcasing improved generalization capabilities. Additionally, four recurrent neural network models LSTM, Bilstm, GRU, and BIGRUwere evaluated, each configured with 1024 hidden units and optimized using the Adam optimizer over 50 epochs. The BIGRU model outperformed the others, achieving an accuracy of 97.50%,while the LSTM, Bilstm, and GRU models achieved maximum accuracies of 95.99%, 96.92%, and96.25%, respectively. The successful implementation of this end-to-end speech recognition system significantly advances communication technologies for low-resource languages, enhancing accessibility for diverse linguistic communities. The findings underscore the effectiveness of deep learning methods in improving speech recognition performance in challenging linguistic contexts.
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    REMOVAL OF FLOURIDE FROM GROUND WATER BY SURFACE MODIFICATION OF RED SOIL ON THE POLYANILINE: ACASE OF MAREKO SPEACIAL WOREDA, ETHIOPIA
    (wolkite universty, 2024-08) KORU JEBENO DUTEBO
    Surface modification of natural adsorbents for enhanced adsorption of water pollutants is strategy developed by varieties of research groups. The purpose of this study was to analyses physicochemical properties and to develop adsorbent material by modifying the electronic structure of red soil via facile in situ chemical oxidative polymerization techniques to remove fluoride from groundwater. The as-synthesized materials were also characterized using powder xiiXRD, FT-IR, UV- Vis spectroscopy, and Conduct meter, and their adsorption performance was tested. The XRD studies reveal that the crystal structures of embedded red soil were amorphous, while PANI, PANI/red soil nano particles distorted and become polycrystalline. The maximum adsorption capacity (qmax) of fluoride ions by PANI/RS was 9.35mg/g. The maximum adsorption performance of PANI/RS at different optimization parameter fluoride ions at pH 4.0, contact time for the adsorption process was 50 minutes, temperature was 350c, initial concentration15mg/L with 2mg adsorbent is 99.9%. Both Langmuir and Freundlich isotherm data for fluoride have a good fit with the experimental data (R2 = 0.94 and 0.95), respectively. Therefore, PANI/RS is remarkably outperformed red soil can be a promising candidate to be used as and sorbent material to remove fluoride ions from groundwater