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All Journal Jurnal Teknik ITS Bulletin of Electrical Engineering and Informatics JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Kursor Jurnal Ilmiah FIFO Syntax Literate : Jurnal Ilmiah Indonesia Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Sewagati Jurnal Pengabdian Masyarakat Nasional
Santoso, Bagus Jati
Departemen Informatika, Fakultas Teknologi Informasi Dan Komunikasi, Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo, Surabaya
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences

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Journal : JUTI: Jurnal Ilmiah Teknologi Informasi

 1 
DATA REFINEMENT APPROACH FOR ANSWERING WHY-NOT PROBLEM OVER K-MOST PROMISING PRODUCT (K-MPP) QUERIES Permadi, Vynska Amalia; Ahmad, Tohari; Santoso, Bagus Jati
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 16, No. 2, Juli 2018
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v16i2.a754

Abstract

K-Most Promising (K-MPP) product is a strategy for selecting a product that used in the process of determining the most demanded products by consumers. The basic computations used to perform K-MPP are two types of skyline queries: dynamic skyline and reverse skyline. K-MPP selection is done on the application layer, which is the last layer of the OSI model. One of the application layer functions is providing services according to the user's preferences.In the K-MPP implementation, there exists the situation in which the manufacturer may be less satisfied with the query results generated by the database search process (why-not question), so they want to know why the database gives query results that do not match their expectations. For example, manufacturers want to know why a particular data point (unexpected data) appears in the query result set, and why the expected product does not appear as a query result. The next problem is that traditional database systems will not be able to provide data analysis and solution to answer why-not questions preferred by users.To improve the usability of the database system, this study is aiming to answer why-not K-MPP and providing data refinement solutions by considering user feedback, so users can also find out why the result set does not meet their expectations. Moreover, it may help users to understand the result by performing analysis information and data refinement suggestion.
ANSWERING WHY-NOT QUESTIONS ON REVERSE SKYLINE QUERIES OVER INCOMPLETE DATA Santoso, Bagus Jati; Connery, Tosca Yoel
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 17, No. 1, Januari 2019
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v17i1.a824

Abstract

        Recently, the development of the query-based preferences has received considerable attention from researchers and data users. One of the most popular preference-based queries is the skyline query, which will give a subset of superior records that are not dominated by any other records. As the developed version of skyline queries, a reverse skyline query rise. This query aims to get information about the query points that make a data or record as the part of result of their skyline query.     Furthermore, data-oriented IT development requires scientists to be able to process data in all conditions. In the real world, there exist incomplete multidimensional data, both because of damage, loss, and privacy. In order to increase the usability over a data set, this study will discuss one of the problems in processing reverse skyline queries over incomplete data, namely the "why-not" problem. The considered solution to this "why-not" problem is advice and steps so that a query point that does not initially consider an incomplete data, as a result, can later make the record or incomplete data as part of the results. In this study, there will be further discussion about the dominance relationship between incomplete data along with the solution of the problem. Moreover, some performance evaluations are conducted to measure the level of efficiency and effectiveness.
CONTINUOUS MULTIQUERIES K-DOMINANT SKYLINE ON ROAD NETWORK Muttaqi, Syukron Rifail; Santoso, Bagus Jati
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 18, No. 2, July 2020
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v18i2.a999

Abstract

The increasing use of mobile devices makes spatial data worthy of consideration. To get maximum results, users often look for the best from a collection of objects. Among the algorithms that can be used is the skyline query. The algorithm looks for all objects that are not dominated by other objects in all of its attributes. However, data that has many attributes makes the query output a lot of objects so it is less useful for the user. k-dominant skyline queries can be a solution to reduce the output. Among the challenges is the use of skyline queries with spatial data and the many user preferences in finding the best object. This study proposes IKSR: the k-dominant skyline query algorithm that works in a road network environment and can process many queries that have the same subspace in one processing. This algorithm combines queries that operate on the same subspace and set of objects with different k values by computing from the smallest to the largest k. Optimization occurs when some data for larger k are precomputed when calculating the result for the smallest k so the Voronoi cell computing is not repeated. Testing is done by comparing with the naïve algorithm without precomputation. IKSR algorithm can speed up computing time two to three times compared to naïve algorithm.
MAPPING POTENTIAL ATTACKERS AGAINST NETWORK SECURITY USING LOCATION AWARE REACHABILITY QUERIES ON GEO SOCIAL DATA Firdausi, Hafara; Santoso, Bagus Jati; Qudus, Rohana; Ciptaningtyas, Henning Titi
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 2, Juli 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i2.a1071

Abstract

Attacks on network security can happen anywhere. Using Geo-Social Networks (GSN), i.e., a graph that combines social network data and spatial information, we can find the potential attackers based on the given location. In answering the graph-based problems, Reachability Queries are utilized. It verifies the reachability between two nodes in the graph. This paper addresses a problem defined as follows: Given a geo-social graph and a location area as a query point, we map potential attackers against network security using location-aware reachability queries. We employ the concepts of Reachability Minimum Bounding Rectangle (RMBR) and graph traversal algorithm, i.e., Depth-First Search (DFS), to answer the location-aware reachability queries. There are two kinds of the proposed solution, i.e., (1) RMBR-based solution map potential attackers by looking for intersecting RMBR values, and (2) Graph traversal-based solution map potential attackers by traversing the graph. We evaluate the performance of both proposed solutions using synthetic datasets. Based on the experimental result, the RMBR-based solution has much lower execution time and memory usage than the graph traversal-based solution.
Co-Authors Adhitya Bhawiyuga Annisa Puspa Kirana Arina Qona'ah Ary Mazharuddin Shiddiqi Baskoro Adi Pratomo Chastine Fatichah Connery, Tosca Yoel Dany Primanita Kartikasari Didit Prasetyo Dini Adni Navastara, Dini Adni Endyka Erye Frety F.X. Arunanto Fathoni Adi Kurniawan Fatmala Ulfa Nurliyana Firdausi, Hafara Henning Titi Ciptaningtyas Hertiari Idajati, Hertiari Hudan Studiawan Imamah Imamah Iska Desmawati Kartika Kusuma Wardani Maria Nicolas Ganden Gondho Winoto Mokh. Suef Muttaqi, Syukron Rifail Naufan Noordyanto Nugrahardi Ramadhani Nurina Orta Darmawati Putri Dwitasari Qudus, Rohana Rabendra Yudistira Alamin Radityo Anggoro, Radityo Ridho Rahman Hariadi Royyana Muslim Ijtihadie Royyana Muslim Ijtihadie Saptarini, Dian Satria Adi Kharisma Siti Rochimah Supeno Djanali Tohari Ahmad Vynska Amalia Permadi Waskitho Wibisono Yogantara S. Dharmawan Yuhana, Umi Laili