اُس کی قدرت کے ہزار کرشمے
بنا ستوں کھڑا کیا آسماں جس نے
شب دن میں دن شب میں ڈھلتاہے
وہ جانے کتنے ہی رنگ بدلتا ہے
یہ پہاڑ بھی اُس کی طاقت کا نشاں ہیں
کہ اس کی قدرت کی حد تو بے بیاں ہے
بحروں کی اتھاہ گہرائیوں میں بھی
اپنی بنائی مخلوق پالتا ہے
کبھی پانیوں کو فلک سے گراتا ہے
تو کبھی زمیں سے اُچھالتا ہے
ننھے سے بیج کے سینے سے
کیسے تن آور شجر نکالتا ہے
زمیں کا سینہ چیرتے ہوئے
آتش فشاں بھی تو بنائے اُس نے
اپنے قادر ہونے کے
کتنے ہی نشاں دکھائے اس نے
ناممکن سی شے تعریف اس کے ایک گُن کی ہے
کہ اس کے نزدیک تو بات کن فیکون کی ہے
جب وہ رب یہ سب معجزے دکھا سکتا تھا
اک ادنیٰ سا کرشمہ اور بھی تو دکھا سکتا تھا
وہ تجھے میرا بھی تو بنا سکتا تھا
This study aims to discuss the relationship between competence and job satisfaction on the performance of private Madrasah Tsanawiyah teachers in the city of Surabaya. The research method used is the type of research used that is explanatory with a quantitative approach with a sample size of 244 of 628 teachers from 44 private Madrasah Tsanawiyah in the city of Surabaya). The results showed that teachers’ competence had an effect on teachers’ job satisfaction with a value of 0.184. Teachers’ competence affected teachers’performance with a value of 0.118. Teachers’ job satisfaction affected teachers’ performance with a value of 0.222. Teachers’ job satisfaction on teachers’ performance showed a high influence with a CR value of 2.772 (greater than 2.00) and a significance level (p-value) of 0.006 (less than 5%). It can be concluded that teachers’ competence affected teachers’ job satisfaction and teachers’ competence affected teachers’ performance. Teachers’ job satisfaction had a strong effect on teachers’ performance.
Most of the real-world problems ranging from engineering to medical or social fields involve uncertainty in data. Soft computing models, including m-polar fuzzy sets, intuitionistic fuzzy sets, soft sets and rough sets are used to deal with uncertain and incomplete information. The objective of this thesis is to present certain novel hybrid models, namely, m-polar fuzzy N-soft rough sets, intuitionistic fuzzy N-soft sets and intuitionistic fuzzy N-soft rough sets, for modeling incomplete information in information systems. These models are obtained by the hybridization of N-soft sets with m-polar fuzzy sets, intuitionistic fuzzy sets and rough sets, which are more precise and flexible for modeling and processing of vague information. These models provide us information about the occurrence of ratings or grades and enable us to tackle multi-polar information. Certain novel concepts concerning these newly hybrid models are discussed. Four types of parameter reductions of bipolar fuzzy soft sets are presented. The significance of bipolar fuzzy sets is discussed, by analyzing relation systems and relation decision systems, specifically attribute reduction of bipolar fuzzy relation decision systems is presented. The proposed methods are applied to some real life decision making problems for representation of multi-attribute data, including multi-criteria selection of suitable place for tour. Efficient algorithms are developed to solve decision-making problems based on the proposed hybrid models.