On the Relation of Probability, Fuzziness, Rough and Evidence Theory

Since the appearance of the first paper on fuzzy sets proposed by Zadeh in 1965, the relationship between probability and fuzziness in the representation of uncertainty has been discussed among many people. The question is whether probability theory itself is sufficient to deal with uncertainty. In this paper the relationship between probability and fuzziness is analyzed by the process of perception to simply understand the relationship between them. It is clear that probability and fuzziness work in different areas of uncertainty. Here, fuzzy event in the presence of probability theory provides probability of fuzzy event in which fuzzy event could be regarded as a generalization of crisp event. Moreover, in rough set theory, a rough event is proposed representing two approximate events, namely lower approximate event and upper approximate event. Similarly, in the presence of probability theory, rough event can be extended to be probability of rough event. Finally, the paper shows and discusses relation among lower-upper approximate probability (probability of rough events), belief-plausibility measures (evidence theory), classical probability measures, probability of generalized fuzzy-rough events and probability of fuzzy events

Effect of Sugar replacement on chemical composition and organoleptic properties of Shrikhand

Shrikhand is a popular Indian dessert prepared by fermentation of milk. It has a semi-soft consistency and is sweetish sour in taste. Fresh Curd (dahi) prepared was partially strained through a cloth to remove the whey and produce a solid mass called chakka. Chakka was finely mixed with sugar and flavouring agents, to give a sweetish-sour taste. For the present study stevia powder and extract was used to replace sugar. Stevia powder and extract were added in different combination in the experimental products. Control, having 100% sugar was also prepared. The organoleptic evaluation of the products was done by a panel of judges to select the most acceptable level of stevia in shrikhand. The product with most acceptable level of stevia and the control sample was stored for 21 days at refrigeration temperature. During storage products were analyzed for the proximate composition, sensory attributes and microbial load at an interval of 7 days. It was found that shrikhand was acceptable upto 30% substitution of sugar with stevia extract and 20% substitution with stevia powder as compared to the control recipe. The storage study reveals that there was a decrease noticed in fat, protein, moisture and ash in both the control and sample shrikhand during storage. A significant (P≤0.05) decrease was noticed in the scores for sensory. The microbial load increased significantly (P≤0.05) during storage. Keywords: Shrikhand, Stevia, Calories, Nutritive valueÂ

PARTISIPASI MASYARAKAT PADA PEMILUKADA GUBERNUR DAN WAKIL GUBERNUR ACEH TAHUN 2012 (STUDI PADA MASYARAKAT PULAU ACEH DAN SABANG)

ixABSTRAKROLLY MARTAN PARTISIPASI MASYARAKAT PADA PEMILUKADA2015 GUBERNUR DAN WAKIL GUBERNUR 2012 (STUDI PADA PULAU ACEH DAN SABANG)Fakultas Ilmu Sosial dan Ilmu Politik Universitas Syiah Kuala (ix, 82), pp., bibl., tble. digrm. app.(Drs. Zainal Abidin AW, M.Si dan Radhi Darmansyah, M. Sc)Partisipasi masyarakat merupakan bagian dari sistem politik demokrasi yang dapat diartikan sebagai suatu mekanisme melalui setiap keputusan politik atau kebijaksanaan umum yang diatur, dirumuskan dan ditetapkan dengan mengikut sertakan masyarakat. Tingkat partisipasi masyarakat di wilayah kepulauan sangat tinggi pada ajang pemilihan umum gubernur dan wakil gubernur tahun 2012.Tujuan dari penelitian ini adalah untuk mengetahui bagaimana partisipasi masyarakat pulau Aceh dan pulau Sabang pada pemilihan umum Gubernur dan wakil Gubernur Aceh tahun 2012. Dan untuk mengetahui faktor-faktor yang mendorong partisipasi masyarakat pulau Aceh dan pulau Sabang.Metode yang digunakan dalam penelitian ini adalah metode deskriptif kualitatif. Teknik pengumpulan data yang digunakan yaitu penelitian lapangan dan penelitian kepustakaan. Studi lapangan untuk memperoleh data primer yang dilakukan dengan cara wawancara. Sedangkan penelitian kepustakaan untuk memperoleh data sekunder berdasarkan buku-buku dan bacaan terkait.Hasil penelitian ini mejelaskan bahwa partisipasi masyarakat di pulau Aceh lebih tinggi daripada pulau Sabang dilihat dari aspek-aspek partisipasi yang di ikuti dalam pemilukada Gubernur dan wakil Gubernur Aceh tahun 2012 faktor-faktor yang mendorong partisipasi politik masyarakat pulau Aceh dan pulau Sabang pada pemilukada Gubernur dan wakil Gubernur Aceh tahun 2012 ialah sebagai ajang aspirasi rakyat, keadaan sosial dan politik, ingin adanya perubahan di wilayah tersebut, Partisipasi politik atas dasar sukarela, sosialisasi dari KIP, peran tim sukses dan partai politik,pendekatan kandidat kandidat-kandidat, serta Peran ruang publik sebagai alat informasi.Mengharapkan pada pemerintah Aceh yang telah terpilih bisa membuktikan janji-janji yang yang telah di berikan kepada masyarakat khususnya masyarakat yang ada di daerah kepulauan. Kepada partai politik beserta para kandidat dan tim sukses agar menjalankan sesuai fungsinya masing-masing dan memberikan pendidikan politik yang baik kepada masyarakat,Kata Kunci : Partisipasi, Pulau Aceh, Sabang.xiABSTRACT ROLLY MARTAN CIVIL PARTICIPATION DURING GOVENOR AND VICE GOVENOR 2015 ELECTION (PEMILUKADA) IN 2012 (A CASE STUDY IN PULAU ACEH AND SABANG) Civil participation is a part of democracy system where public policies are discussed, constructed, and published by considering civil interest and opinion. Civilian who live in the island are often considered abstent due to their difficult access and distance. This condition is creating a mass apathetic situation where civilian is rather careless about their rights and participation in both public and political matter. The aim of this research is to investigate civilian participation in Pulau Aceh and Sabang during 2012 govenor and vice govenor local election (pemilukada). And also to gain insight about contributing factors regarding civilian participation in Pulau Aceh and Sabang. This research used descriptive qualitative method. Field research such as interviewing informants and documentation were used to collect primary data while literature studies were applied to collect secondary data. This research explains that civil participation in Pulau Aceh is higher than Sabang. Some of the reason of this finding is because alot of Sabang native people are working and living in Banda Aceh (outside Sabang) and the rest are just consciously abstent. Strong political will to contribute something, social and political situation, hope of better condition, voluntary participation, KIP socialization, various methods of political campaign, and the role of public space as medium of information were several factors mentioned in this reseach that could strogly contribute to higher civil participation. District and sub-district government is holding crucial position in investigating the reason of high rate of abstentions and is expected to tackle this problem with effective solutions. Village stakeholder is also critical in giving advice and persuade civilian to increase civil participation village by village. This matters are important because civil participation in the island especially their voting number during election have great impact in Aceh government electoral seat. Keywords: Participation, Pulau Aceh, Saban

Study on Rough Sets and Fuzzy Sets in Constructing Intelligent Information System

Since human being is not an omniscient and omnipotent being, we are actually living in an uncertain world. Uncertainty was involved and connected to every aspect of human life as a quotation from Albert Einstein said: �As far as the laws of mathematics refer to reality, they are not certain. And as far as they are certain, they do not refer to reality.� The most fundamental aspect of this connection is obviously shown in human communication. Naturally, human communication is built on the perception1-based information instead of measurement-based information in which perceptions play a central role in human cognition [Zadeh, 2000]. For example, it is naturally said in our communication that �My house is far from here.� rather than let say �My house is 12,355 m from here�. Perception-based information is a generalization of measurement-based information, where perception-based information such as �John is excellent.� is hard to represent by measurement-based version. Perceptions express human subjective view. Consequently, they tend to lead up to misunderstanding. Measurements then are needed such as defining units of length, time, etc., to provide objectivity as a means to overcome misunderstanding. Many measurers were invented along with their methods and theories of measurement. Hence, human cannot communicate with measurers including computer as a product of measurement era unless he uses measurement-based information. Perceptions are intrinsic aspect in uncertainty-based information. In this case, information may be incomplete, imprecise, fragmentary, not fully reliable, vague, contradictory, or deficient in some other way. 1In psychology, perception is understood as a process of translating sensory stimulation into an organized experience Generally, these various information deficiencies may express different types of uncertainty. It is necessary to construct a computer-based information system called intelligent information system that can process uncertainty-based information. In the future, computers are expected to be able to make communication with human in the level of perception. Many theories were proposed to express and process the types of uncertainty such as probability, possibility, fuzzy sets, rough sets, chaos theory and so on. This book extends and generalizes existing theory of rough set, fuzzy sets and granular computing for the purpose of constructing intelligent information system. The structure of this book is the following: In Chapter 2, types of uncertainty in the relation to fuzziness, probability and evidence theory (belief and plausibility measures) are briefly discussed. Rough set regarded as another generalization of crisp set is considered to represent rough event in the connection to the probability theory. Special attention will be given to formulation of fuzzy conditional probability relation generated by property of conditional probability of fuzzy event. Fuzzy conditional probability relation then is used to represent similarity degree of two fuzzy labels. Generalization of rough set induced by fuzzy conditional probability relation in terms of covering of the universe is given in Chapter 3. In the relation to fuzzy conditional probability relation, it is necessary to consider an interesting mathematical relation called weak fuzzy similarity relation as a generalization of fuzzy similarity relation proposed by Zadeh [1995]. Fuzzy rough set and generalized fuzzy rough set are proposed along with the generalization of rough membership function. Their properties are examined. Some applications of these methods in information system such as α-redundancy of object and dependency of domain attributes are discussed. In addition, multi rough sets based on multi-context of attributes in the presence of multi-contexts information system is defined and proposed in Chapter 4. In the real application, depending on the context, a given object may have different values of attributes. In other words, set of attributes might be represented based on different context, where they may provide different values for a given object. Context can be viewed as background or situation in which somehow it is necessary to group some attributes as a subset of attributes and consider the subset as a context. Finally, Chapter 5 summarizes all discussed in this book and puts forward some future topics of research

Application of Conditional Probability in Constructing Fuzzy Functional Dependency

In real-world application, information is mostly imprecise or ambiguous. Therefore, the motivation of extending classical (crisp) relational database [Codd, 1970] to fuzzy relational database by Buckles and Petry [1982] stems from the need to be able to process and represent vague, imprecise and partially known (incomplete) information. The concept of fuzzy relational database proposed by Buckles and Petry [1982] are necessary to be extended to a more generalized concept of fuzzy relational database, since the data value in domain attributes of the fuzzy relational model is still considered as a subset of atomic data. In this case, each data value stored in the more generalized concept of fuzzy relational database is considered as a fuzzy subset. An important feature of a relational database is to express constraints in sense of relation of data, known as integrity constraints (ICs). For instance, if a relational database contains information about student ID-number, course, unit, term and grade, some constrains such as: “A given ID-number, course, and term give a unique grade”, “number of courses are no more than 6 courses for a given ID-number and term” and “total units are no more than 16 for a given ID-number and term” might be hold. Many types of integrity constraints have been provided since 1970s along with the Codd’s relational database, such as multi-valued dependency proposed by Fagin [1977], join dependency [Nicolas, 1978] [Rissanen, 1978], etc. Among them, functional depen¬dencies (FDs) [Berstein, Swenson, & Tsichritzis, 1975] are one of the most important and widely used in database design. As we extend the classical relational database to fuzzy relational database, it would be necessary to consider integrity constraints that may involve fuzzy value. In fact, fuzzy integrity constraints, such as: “The higher an education someone has, the higher salary he should get”, “almost equally qualified employees should get more or less equal salary” will arise naturally and usefully in real-world application. Therefore, the objective of extending FDs to fuzzy functional dependencies (FFDs) is in necessary to apply FDs in fuzzy relational database [Intan, Mukaidono, 2000a, 2003, 2004]. Various definitions and the notion of a fuzzy functional dependency have been devised since 1988. Among them, Raju and Majumdar [1988] defined FFD based on the membership function of the fuzzy relation; Tripathy, [1990] proposed definition of the FFD in terms of fuzzy Hamming weight; Kiss, [1991] constructed FFD using weighted tuples; Chen [1995], Cubero [1994] and W. Liu [1992,1993] introduced definition of the FFD based on the equality of two possibility distributions, and they used a certain type of implication and expression of cut off; Liao [1997] gave design of the FFD by introducing semantic proximity. In this book, some properties of conditional probability and its relation with fuzzy sets are studied and discussed as an alternative concept to measure similarity of fuzzy labels. Even it could be understood that interpretation of numerical value between fuzzy sets and probability measures are philosophically distinct, basic operations, such as, intersection and union of two fuzzy values can be interpreted as maximum intersection and minimum union of two events. Considering this reason, it is necessary to define three approximate conditional probabilities of two fuzzy events based on minimum, independent and maximum probability intersection between two (fuzzy) events. Moreover, conditional probability of two fuzzy events can be interpreted as probabilistic matching of two fuzzy sets [Baldwin, Martin, Pilsworth, 1995], [Baldwin, Martin, 1996] and as basis of getting similarity of two fuzzy sets and constructing equivalence classes inside their domain attribute. By using this property and Cartesian product operation of fuzzy sets, a concept of fuzzy functional dependency (FFD) is proposed and defined to express integrity constraints that may involve fuzzy value, called fuzzy integrity constraints. It can be proved that the concept of FFD satisfies classical/ crisp relational database by example. Also, inference rules which are similar to Armstrong’s Axioms [Armstrong, 1974] for the FFDs are both sound and complete. Next, a concept of partial FFD is introduced to express the fact as usually found in data that a given attribute domain X do not determine Y completely, but in the partial area of X, it might determine Y. For instance, in the relation between two domains student’s name and student’s ID, student’s ID determines student’s name. It means a given student’s ID certainly gives a unique student’s name. On the other hand, a given student’s name may give more than one student’s ID because it is possible to have more than one student who has the same name. However, in a partial area of student’s name where some students have unique names, student’s name can be considered to determine student’s ID. In addition, approximate data reduction and projection of relations are investigated in order to get relation among the partitions of data values. Here, data values might be considered as crisp as well as fuzzy data. Finally, this book discusses the application of FFDs in constructing fuzzy query relation for query data and approximate natural join of two or more fuzzy query relations in the framework of extended query system [Intan, Mukaidono, 2001, 2002]. The structure of the book is following. In Chapter 2, some basic definitions and notations, such as conditional probability, classical relational database, functional dependency, fuzzy sets, transformation fuzzy set and probability, and fuzzy relational database are recalled. Chapter 3 firstly introduces conditional probability of two fuzzy sets based on the possibility theory [Baldwin, Martin, Pilsworth, 1995]. The next, it provides three approximate interpretations in constructing conditional probability of two fuzzy events (sets) based on minimum, independent and maxi¬mum probability intersection between two (fuzzy) events [Intan, Mukaidono, 2004]. Chapter 4 is devoted to the construction of FFDs based on the concept of conditional probability relations. It is proved that inference rules (Reflexivity, Augmentation and Transitivity) which are similar to Armstrong’s Axioms for FFDs are both sound and complete. A special attention will be given to partial FFD in order to find relation between two partial areas of two attribute domains [Intan, Mukaidono, 2004]. In Chapter 5, the application of FFDs in approximating data reduction and query data are presented [Intan, Mukaidono, 2001, 2002]. This chapter also discussed two other operations called projection and join operations in the relation to approximate data reduction and extended query system respectively [Intan, Mukaidono, 2004]. This book will be closed by summary including suggestion for future work in Chapter 6

PENERAPAN PENDEKATAN KETERAMPILAN PROSES UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR ILMIAH DAN PRESTASI BELAJAR SISWA

Penelitian ini bertujuan untuk mendeskripsikan penerapan pendekatan keterampilan proses untuk meningkatkan kemampuan berpikir ilmiah siswa, untuk mendeskripsikan penerapan pendekatan keterampilan proses untuk meningkatkan prestasi belajar siswa dan untuk mendeskripsikan penerapan pendekatan keterampilan proses efektif untuk meningkatkan prestasi belajar siswa. Desain penelitian yang digunakan adalah penelitian tindakan kelas dan kuasi eksperimen. Subjek penelitian adalah siswa kelas XII MIPA SMA Negeri 4 Lahat semester ganjil tahun pelajaran 2022/2023. Melalui teknik purposive sampling diperoleh sampel penelitian tindakan kelas adalah kelas XII MIPA 1, dan kuasi eksperimen adalah kelas XII MIPA 2 serta kelas kontrol adalah kelas XII MIPA 4 SMA Negeri 4 Lahat. Teknik pengumpulan data penelitian menggunakan lembar observasi dan tes. Data penelitian dianalisis dengan statistik deskriptif, rata-rata (mean), persentase, dan uji-t. Hasil penelitian menunjukan bahwa penerapan pendekatan keterampilan proses dapat meningkatkan kemampuan berpikir ilmiah dan prestasi belajar pada mata pelajaran Biologi Siswa Kelas XII MIPA SMA Negeri 4 Lahat. Penerapan keterampilan proses lebih efektif untuk meningkatkan prestasi belajar siswa pada mata pelajaran Biologi siswa kelas XII MIPA SMA Negeri 4 Lahat

Sniify : Social Network Influential People Identification on Ontology

ABSTRAKSI: Most important things on Social Customer Relationship Management field is focusing on managing engagement between industry and customers. The engagement created by industry-customer relationship based on social activity. However, the industry have limitation to interact with every single customer, because high cost and maintenance. Furthermore, they choose other methods to keep the relationship with effective and efficient resources.The customer have social activity, interact each other and tied each other. This social activity creating a graph called social network. The graph consisting nodes as central point and edges as relation between nodes. The social network with customer as nodes and activity as edges will be have same behavioral with graph, have influential nodes or influential people as customer. This study was to propose a method of industry-customer engagement to find influential people in social network based on their relation activities.Influential people identification starts with model design of social network. The model uses Ontology as knowledge representation design. The calculation conducted on the model with centrality measurement. The measurement uses in friendship relationships and activities data. The study have influential people by the result of measurement not only by their relationship status, but also use activity data.Kata Kunci : Social Customer Relationship Management; Influential People; Social Network; Ontology;CentralityABSTRACT: Most important things on Social Customer Relationship Management field is focusing on managing engagement between industry and customers. The engagement created by industry-customer relationship based on social activity. However, the industry have limitation to interact with every single customer, because high cost and maintenance. Furthermore, they choose other methods to keep the relationship with effective and efficient resources.The customer have social activity, interact each other and tied each other. This social activity creating a graph called social network. The graph consisting nodes as central point and edges as relation between nodes. The social network with customer as nodes and activity as edges will be have same behavioral with graph, have influential nodes or influential people as customer. This study was to propose a method of industry-customer engagement to find influential people in social network based on their relation activities.Influential people identification starts with model design of social network. The model uses Ontology as knowledge representation design. The calculation conducted on the model with centrality measurement. The measurement uses in friendship relationships and activities data. The study have influential people by the result of measurement not only by their relationship status, but also use activity data.Keyword: Social Customer Relationship Management; Influential People; Social Network; Ontology;Centralit