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Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi
Published by Universitas Dr. Soetomo Surabaya
ISSN : 25023470     EISSN : 25810367     DOI : 10.25139
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Library & Information Science
Inform: Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi is One of the journals published by the Informatics Engineering Department Dr. Soetomo University, was established in January 2016. Inform a double-blind peer-reviewed journal, the aim of this journal is to publish high-quality articles dedicated to the field of information and communication technology, Published 2 times a year in January and July. Inform with p-ISSN:2502-3470 and e-ISSN:2581-0367 has been accredited by the Ministry of Research and Technology of the National Research and Innovation Agency of the Republic of Indonesia Number 85/M/KPT/2020 dated April 1, 2020. Accreditation is valid for 5 years Vol.3 No.2 2018 to Vol.8 No.1 2023. Focus and Scope that is Scientific research related to information and communication technology fields, including Software Engineering, Information Systems, Human-Computer Interaction, Architecture and Hardware, Computer Vision, Pattern Recognition, Computer Application and Artificial intelligence, Game Technology, and Computer Graphics, but not limited to informatics scope.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 20 Documents
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Search results for , issue "Vol. 7 No. 1 (2022)" : 20 Documents clear
Smart Chicken Coop Ecosystem for Optimal Growth of Broiler Chickens Using Fuzzy on IoT Suprianto, Dodit; Pristiya, Ermi; Prasetyo, Arief
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4231

Abstract

Chicken consumption is one of the high-value economic sectors. In order to harvest chickens optimally, it is necessary to maintain the temperature and humidity of the chicken coop regularly. The application of IoT to monitor the temperature and humidity of the chicken coop is significant. Therefore, an automatic temperature-humidity control system based on decisions made using the Sugeno fuzzy method is also needed. Smart chicken coop with the fuzzy algorithm on platform internet of things can be used as an alternative process temperature and humidity control automatically replace conventional method. Based on the results of the tests, this system can control temperature and humidity at 30.3°C, which is the ideal temperature for the growing time of broilers.
Using ISO 9241-11 To Identify How E-Commerce Companies Applied UX Guidelines Fauza Adelma Syafrizal; Rahmat Izwan Heroza; Ermatita; Mgs. Afriyan Firdaus; Pacu Putra; Lovinta Happy Atrinawati; Monterico Adrian
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4261

Abstract

A lot of the company's business activities failed due to not adapting to user needs and technological developments. Previous studies show that there is no way to implement UX guidelines that explain the specific user needs for the UX of e-commerce systems. Therefore, we need a way of implementing UX for e-commerce websites. We used usability parameters in ISO 9241-11, namely effectiveness, efficiency, and satisfaction, to measure the system's usability and then conduct an interview to follow up the result. This research identifies how e-commerce companies implement UX best practices for their systems that can be used for other people who want to design their e-commerce applications.
Mapping COVID-19 in a Region Using IP Geolocation and Fuzzy Inference System Aris Widodo, Anang; Muslim Alamsyah
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4269

Abstract

The spread of COVID-19, which is getting faster every day, has made people wary. If residents suffer from the symptoms and risks of COVID-19, they are afraid and ashamed because they feel ostracized by their neighbors, relatives, and families. It is a shame and fear of reporting that causes the transmission of COVID-19 to accelerate. Therefore, it is necessary to create a system that can answer the problem, namely a system that can detect first aid symptoms and risks of COVID-19 suffered by residents, so that residents know their health status without checking the health of the COVID-19 task force in each area. The system is made by reading the location of residents who report their health to know where they are and their health status. A method for reading the location of system users based on IP addresses is called IP Geolocation, which stands for Internet Protocol Geolocation. The determination of the health status of residents is in the category of Negative COVID-19, ODR, ODP, PDP, or Positive COVID-19 using the Fuzzy Inference System (FIS) method. The IP Geolocation and FIS results will be displayed on a map (google maps). Implementing this system will make it easier for the Government to monitor the spread of COVID-19 based on public reports and information. By testing using the black box method based on partition equivalence with seven facilities in the system, one mistake makes the facility a weakness of IP Geolocation.
Grouping Student Awareness on Security Of E-Learning Information Using Fuzzy C-Means Method Arie Budi Suprio, Yoyon; M. Rizky Maulana
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4281

Abstract

Many educational institutions have been forced to adapt how they present the teaching and learning process, including the creation of appropriate learning media due to the current Covid-19 pandemic. This is accomplished through the development of an integrated online learning system known as E-Learning. Aside from all of the benefits and positive outcomes that E-Learning can give, there are also drawbacks to student information security, such as assignment theft, piracy of E-Learning, the misuse of passwords by irresponsible students, and other problems. To anticipate this, the researcher intended to group students' awareness of their respective E-Learning information security by using the Fuzzy C Means method. Fuzzy C Means uses a fuzzy grouping model so that data can be members of all classes or clusters formed with different degrees or levels of membership between 0 to 1. The sample used to represent the population is 20 students of STIKOM PGRI Banyuwangi, Indonesia. The results obtained are to find out how well the grouping of student awareness clusters on E-Learning information security. There are 3 clusters of student E-Learning information security awareness. Cluster 1 consists of students with high awareness, cluster 2 contains categories of students with low awareness, and the third cluster consists of students with moderate awareness.
A Survey on Deep Learning Algorithms in Facial Emotion Detection and Recognition Baffour, Prince Awuah; Nunoo-Mensah, Henry; Keelson, Eliel; Kommey, Benjamin
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4282

Abstract

Facial emotion recognition (FER) forms part of affective computing, where computers are trained to recognize human emotion from human expressions. Facial Emotion Recognition is very necessary for bridging the communication gap between humans and computers because facial expressions are a form of communication that transmits 55% of a person's emotional and mental state in a total face-to-face communication spectrum. Breakthroughs in this field also make computer systems (robotic systems) better serve or interact with humans. Research has far advanced for this cause, and Deep learning is at its heart. This paper systematically discusses state-of-the-art deep learning architectures and algorithms for facial emotion detection and recognition. The paper also reveals the dominance of CNN architectures over other known architectures like RNNs and SVMs, highlighting the contributions, model performance, and limitations of the reviewed state-of-the-art. It further identifies available opportunities and open issues worth considering by various FER research in the future. This paper will also discover how computation power and availability of large facial emotion datasets have also limited the pace of progress.
A Survey of Trust Management Schemes for Social Internet of Things Kuseh, Simon Wewoliamo; Nunoo-Mensah, Henry; Klogo, Griffith Selorm; Tchao, Eric Tutu
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4284

Abstract

Social Internet of Things (SIoT) involves integrating social networking concepts in the Internet of Things (IoT) to enhance social interactions among IoT objects and users. SIoT is envisaged to provide adequate service selection and discovery. Trust is an essential factor whenever social concepts are discussed in communication networks. Trust usually leads to a mutual relationship between two parties (i.e., the trustor and trustee) where they both enjoy mutual benefits. For secure social relationships, Trust management (TM) is a crucial feature of SIoT. The primary aim of this work is to provide a comprehensive review of trust management proposals/schemes available for SIoT. Four main trust calculation algorithms for trust management were selected for this review, and they were examined in detail. The IEEE Xplore, Scopus, ResearchGate, and Google Scholar databases were searched for articles containing the terms "Trust aggregation approaches in IoT", and "Trust computation in SIoT" with a particular emphasis on works published between 2018 and 2021. The paper also discussed the pros and cons of each TM technique, trust metrics/features, contributions, and limitations of the state-of-the-art SIoT TM proposals in the literature. The paper further provides open issues and possible research directions for entry-level researchers in the domain of SIoT.
Implementation of Android-Based Parking Management Applications Pramono, Anang; M. Ali Shodikin
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4364

Abstract

Parking problems are one of the problems faced in every city, especially in big cities. The availability of limited parking spaces and the unavailability of a parking system that can support the ease of parking management are essential things that must be found as the best solution. The parking application developed can provide information easily. In addition, parking users also get convenience in placing orders, extending time, or canceling. The parking system can provide comfort for parking management to manage parking areas with an efficient system, not only in terms of information but also in terms of payment, by utilizing digital payment methods. The parking application developed based on Android is an alternative that provides user-friendly solutions and parking management. The application has worked well based on trials with various scenarios, both normal scenarios (without cancellation or without extension) and testing with abnormal conditions. From the usability test of 40 respondents with ten questions from the SUS method, an average score of 76 was obtained.
Implementation System of Health Care Kiosk for Detecting Cholesterol Disease, Uric Acid, Obesity and Hypoxia Yuniarti, Heny; Sigit, Riyanto; Zamzami, Amran
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4367

Abstract

The development of technological advances in the health sector in the last decades has grown very rapidly. Currently, most people do not receive routine medical check-ups because of the long lines of patients and the expensive rates they must pay to see a specialist doctor. This causes many people to ignore the importance of routine health checks as recommended by the National Health Agency. The purpose of this research is to make a device that can perform routine checks independently at home, using an Arduino microcontroller for checking cholesterol, uric acid, obesity, and hypoxia. This tool has several sensors, namely Ultrasonic & Load Cell sensors to measure weight and height, which are used to detect obesity through the BMI table. In addition, there is a Pulse and Oxygen in Blood Sensor (SPO2) sensor to detect heart rate and oxygen saturation to detect hypoxia using the fuzzy logic method. Cholesterol and uric acid examination using the Electrode Based biosensor method with a digital detection device (amperometric biosensor). Testing the Tsukamoto fuzzy logic method system obtained a data accuracy value of 100%, following the rules set for classifying hypoxic diseases. The trial phase was carried out as many as 10 trials, where 90% of patients did not experience hypoxia, and 10% had mild hypoxia. The results of testing the BMI table method system for obesity obtained a data accuracy value of 100% according to the calculation of the BMI calculator. In phase 10 trials, 30% of patients were lean, 50% obese, and 20% obese. The system test results use a range of values, each with a data accuracy value of 100% according to the classification of cholesterol and uric acid levels. Ten trials showed that 70% of patients were in normal condition, 20% of patients with low cholesterol, and 10% of patients were in high limits. As for gout, 70% of patients are in normal condition, and 30% of patients are in high uric acid condition.
MVPA and GA Comparison for State Space Optimization at Classic Tetris Game Agent Problem Armanto, Hendrawan; Dwi Putra, Ronal; Pickerling, Pickerling
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4381

Abstract

Tetris is one of those games that looks simple and easy to play. Although it seems simple, this game requires strategy and continuous practice to get the best score. This is also what makes Tetris often used as research material, especially research in artificial intelligence. These various studies have been carried out. Starting from applying state-space to reinforcement learning, one of the biggest obstacles of these studies is time. It takes a long to train artificial intelligence to play like a Tetris game expert. Seeing this, in this study, apply the Genetic Algorithms (GA) and the most valuable player (MVPA) algorithm to optimize state-space training so that artificial intelligence (agents) can play like an expert. The optimization means in this research is to find the best weight in the state space with the minimum possible training time to play Tetris with the highest possible value. The experiment results show that GAs and MVPA are very effective in optimizing the state space in the Tetris game. The MVPA algorithm is also faster in finding solutions. The resulting state space weight can also get a higher value than the GA (MVPA value is 249 million, while the GA value is 68 million).
3D Object Detection Based on Point Cloud Data Sari, Dewi Mutiara; Dadet Pramadihanto; Alfan Rizaldy Pratama; Bayu Sandi Marta
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/inform.v7i1.4417

Abstract

In the Industrial robotic, computer vision is an important part of the system. The popular object used in the industrial field is a 3D pipe. The problem that is currently being developed is how to detect an object. This research aims to estimate the object detection that is, in this case, is a 3D pipe in various lighting conditions. The camera used in this research is Time of Flight. The methods applied are Remove NaN data for Pre-processing, Random Sample Consensus (RANSAC) for Segmentation, Euclidean Distance for Clustering, and Viewpoint Feature Histogram (VFH) for the object detection. A study conducted on five different objects found that the system could detect each one with a success rate of 100% for the first object, 98.05 percent for the second object, 93.97 percent for the third object, 94 percent for the fourth object, and 99.48 percent for the fifth object. Overall, the system's accuracy in detecting the object is 97.1 percent when four different lighting conditions are applied to five different objects in total.

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