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IPTEK The Journal for Technology and Science
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : 08534098     EISSN : 20882033     DOI : -
Core Subject : Science,
Computer Science & IT
IPTEK The Journal for Technology and Science (eISSN: 2088-2033; Print ISSN:0853-4098), is an academic journal on the issued related to natural science and technology. The journal initially published four issues every year, i.e. February, May, August, and November. From 2014, IPTEK the Journal for Technology and Science publish three times a year, they are in April, August and December in online version.
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol 32, No 3 (2021)" : 6 Documents clear
User Story Extraction from Online News with FeatureBased and Maximum Entropy Method for Software Requirements Elicitation Nafingatun Ngaliah; Daniel Siahaan; Indra Kharisma Raharjana
IPTEK The Journal for Technology and Science Vol 32, No 3 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i3.11625

Abstract

Software requirements query is the frst stage in software requirements engineering. Elicitation is the process of identifying software requirements from various sources such as interviews with resource persons, questionnaires, document analysis, etc. The user story is easy to adapt according to changing system requirements. The user story is a semi-structured language because the compilation of user stories must follow the syntax as a standard for writing features in agile software development methods. In addition, user story also easily understood by end-users who do not have an information technology background because they contain descriptions of system requirements in natural language. In making user stories, there are three aspects, namely the who aspect (actor), what aspect (activity), and the why aspect (reason). This study proposes the extraction of user stories consisting of who and what aspects of online news sites using feature extraction and maximum entropy as a classifcation method. The systems analyst can use the actual information related to the lessons obtained in the online news to get the required software requirements. The expected result of the extraction method in this research is to produce user stories relevant to the software requirements to assist systems analysts in generating requirements. This proposed method shows that the average precision and recall are 98.21% and 95.16% for the who aspect; 87,14% and 87,50% for what aspects; 81.21% and 78.60% for user stories. Thus, this result suggests that the proposed method generates user stories relevant to functional software.
A Systematic Literature Review of The Role of Ontology in Modeling Knowledge in Software Development Processes Evi Triandini; Marco Ariano Kristyanto; Ravi Vendra Rishika; Franky Rawung
IPTEK The Journal for Technology and Science Vol 32, No 3 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i3.12998

Abstract

Ontology in software development is explained as presenting the properties of things within a domain knowledge and how they are interrelated to each other by defining a set of notions and taxonomies that exemplify the knowledge. It is used to deter- mine the ambiguity in the software requirements specification. Though averred to be useful, the software engineering communities are still unfamiliar with the role of Ontology in modeling knowledge in software development processes. Moreover, not much has been known about the role of Ontology in software engineering processes. The objective is to map and explain the substantiation about the role of Ontology in Modelling Knowledge and the challenge faced by the software engineering team to understand how far ontology can help them determine the ambiguity in model- ing and software development processes. We have carried out a methodical review of the literature issued between 2012 and 2021 and recognized 150 publications that talk over the role of ontology in modeling knowledge in software development pro- cesses. This study conveyed and employed particular inclusion and exclusion criteria in bi-rounds to establish the utmost pertinent publications for our research objec- tive. The review acknowledged 22 applications that explain ontologies’ primary role in software development processes. However, our findings suggest ontology’s role in software engineering as a investigation background requires extra consideration. A further experimental result I needed to better understand the role of ontology in modeling knowledge in software development with quality requirements as well as self-organizing groups.
Prototype Portable Electrical Resistance Tomography Ahmad Zaenal Hayat; Agung Tjahjo Nugroho; Nurul Priyantari
IPTEK The Journal for Technology and Science Vol 32, No 3 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i3.8843

Abstract

Tomography is a way to describe something non-destructively. Some types of Tomography are Electrical Resistance Tomography (ERT), Electrical Impedance Tomography (EIT), and Electrical Capacitance Tomography (ECT). This study aims to combine the ECT and ERT systems. The combination uses the ERT technique (Borehole method) and develops until it can be used like ECT. This research conducts three significant stages (design making, designed realization, and examination). The examination is carried out by simulation and experimental measurement. The simulation result is compared to the result of the experimental measurement. The result shows that both have the same patterns, but it has the amplitude of voltage difference pattern. It is because the resistivity result affects the measured voltage difference result. The higher the resistivity result of the medium, the smaller the measured voltage difference.Tomography is a way to describe something non-destructively. Some types of Tomography are Electrical Resistance Tomography (ERT), Electrical Impedance Tomography (EIT), and Electrical Capacitance Tomography (ECT). This study aims to combine the ECT and ERT systems. The combination uses the ERT technique (Borehole method) and develops until it can be used like ECT. This research conducts three significant stages (design making, designed realization, and examination). The examination is carried out by simulation and experimental measurement. The simulation result is compared to the result of the experimental measurement. The result shows that both have the same patterns, but it has the amplitude of voltage difference pattern. It is because the resistivity result affects the measured voltage difference result. The higher the resistivity result of the medium, the smaller the measured voltage difference.
Model Reference Adaptive Control for Single Phase Buck Boost Inverter Purwadi Agus Darwito; Mega Arintika Yuliana
IPTEK The Journal for Technology and Science Vol 32, No 3 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i3.6950

Abstract

An inverter is a device that converts DC voltage into AC voltage. AC output voltage is usually expected to be fixed and symmetrical at certain amplitudes and frequencies. Most inverters use a pulse width modulation circuit to regulate the output voltage. There are many topologies in building inverter circuits. In this research, the BuckBost topology is used to meet the output voltage greater or smaller than the input voltage. In this research, a Buck-Boost inverter is designed to convert a 12 volts DC input voltage to a 220 volts AC output voltage. In addition to the magnitude, the output voltage must also be considered of quality, in the sense that if there is a ripple, it should be as small as possible. For this purposed MRAC control is used, and simulated using Matlab. The test results with simulation show that the response of the SPBBI system with the MRAC controller with the MIT rule method can achieve the expected output voltage of 220V at the reference frequency of 49.95 Hz, 50 Hz, 50.05 Hz, and 60 Hz. System response is very dependent on the value of the adaptation gain. The adaptation gain that produces the best system response is 0.000001 with a settling time of 0.095 seconds.
A Semantic Comparison of Feature Requirements Extraction Methods Patricia Gertrudis Manek; Abdullah Faqih Septiyanto; Adi Setyo Nugroho
IPTEK The Journal for Technology and Science Vol 32, No 3 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i3.13003

Abstract

Requirement engineering is an essential part of software development. The initial process in software development is to determine the needs of the stakeholders. To convert stakeholder needs into features of the system to be developed takes a long time, so it is a challenge for researchers to be able to extract features automatically based on the description of the needs of stakeholders. Previous research has also implemented feature extraction using user reviews on applications that public users have used. The feature extraction results will be used for feature development in future updated versions. The extraction process can use several proven methods to provide results that match the needs of the stakeholders in the system. This study compared the automatic feature extraction method using Natural Language Processing (NLP) with Hierarchical Pattern Recognition (HPR) on the dataset requirements and user reviews. Performance evaluation was conducted to test feature extraction results using Accuracy, precision, recall, and F-measure. The study results show that each method has advantages when implemented on both datasets. The NLP method excels in classifying the NL Requirement dataset. The HPR method has its advantages in extracting user review data.
A Systematic Comparison of Software Requirements Classification Fajar Baskoro; Rasi Aziizah Andrahsmara; Brian Rizqi Paradisiaca Darnoto; Yoga Ari Tofan
IPTEK The Journal for Technology and Science Vol 32, No 3 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i3.13005

Abstract

Software requirements specification (SRS) is an essential part of software development. SRS has two features: functional requirements (FR) and non-functional requirements (NFR). Functional requirements define the needs that are directly in contact with stakeholders. Non-functional requirements describe how the software provides the means to carry out functional requirements. Non-functional requirements are often mixed with functional requirements. This study compares four primarily used machine learning methods for classifying functional and non-functional requirements. The contribution of our research is to use the PROMISE and SecReq (ePurse) dataset, then classify them by comparing the FastText+SVM, FastText+CNN, SVM, and CNN classification methods. CNN outperformed other methods on both datasets. The accuracy obtained by CNN on the PROMISE dataset is 99% and on the Seqreq dataset is 94%.

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