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Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika
Published by Universitas Muhammadiyah Surakarta
ISSN : 2621038X     EISSN : 2477698X     DOI : -
Core Subject : Science,
Computer Science & IT
Khazanah Informatika: Jurnal Ilmiah Komputer dan Informatika, an Indonesian national journal, publishes high quality research papers in the broad field of Informatics and Computer Science, which encompasses software engineering, information system development, computer systems, computer network, algorithms and computation, and social impact of information and telecommunication technology.
Arjuna Subject : -
Articles 249 Documents
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Application of Low Back Pain Myogenic Therapy Based on Multimedia Alfian Gema Negara; Niken Sylvia Puspitasari
Khazanah Informatika Vol. 8 No. 2 October 2022
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v8i2.15645

Abstract

Low back pain restricts activity and causes work absenteeism. Cases of low back pain are common worldwide. This paper presents the design of multimedia-based low back pain myogenic therapy aids. Data collection involves observation and interviews with medical rehabilitation specialists and physiotherapists. The collected data is represented using a production ruler in the form of if - then.  Rule-based reasoning can be used as an expert system knowledge base in cases of myogenic low back pain. Forward chaining can be used as an inference engine for similar cases because the reasoning starts from the facts section before reaching the hypothesis. Design of this assistive device model is expected to provide information regarding the choice of therapy for low back pain myogenic by patients, independently at home or with the help of close family. Application design is multimedia-based to make it easier for users to look at examples visually. The expert system application is well accepted by users. Ten physiotherapists and one doctor consider the application performance good because it attains an acceptable value of 0.80 or 80%. The physiotherapists suggest that this assistive device model will likely increase the intensity of therapy because it can be carried out by the patient's family independently.
Job Scheduling on Grid Computing Using First Fit, Best Fit, and Worst Fit Ardi Pujiyanta; Fiftin Novianto
Khazanah Informatika Vol. 8 No. 2 October 2022
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v8i2.17069

Abstract

Grid computing can be considered large-scale distributed cluster computing and parallel distributed network processing. The two most important issues in managing user work are resource allocation and scheduling of required resources. When user jobs are submitted, they are managed by resource intermediaries who find and allocate the right resources. After the resource allocation stage, work scheduled on the existing resources according to the user's required resources. In most grid systems with traditional scheduling, jobs are submitted and placed in waiting room queues to wait for the required resources to become available. Each grid system can use a different scheduling algorithm to execute jobs based on other parameters, such as resources, delivery time, and execution duration. There is no guarantee that these traditional scheduling algorithms will get the job done. The First Come First Serve Left Right Hole Scheduling (FCFS-LRH) reservation strategy improves resource utilization in a grid system by using a local scheduler. Compared to traditional strategies. There are two objectives of this research. First, compare the first fit, best fit, and worst fit algorithms to find empty timeslots and place them in a virtual view. Second, reduce the idle time value. The results showed that the FCFS-LRH method could reduce the idle time value of the FCFS-EDF and FCFS methods. The overall execution time of the first fit with the FCFS-LRH strategy is better than the FCFS-EDF
Android-Based Short Message Service Filtering using Long Short-Term Memory Classification Model M. Laylul Mustagfirin; Giri Wahyu Wiriasto; I Made Budi Suksmadana; Indira Puteri Kinasih
Khazanah Informatika Vol. 8 No. 2 October 2022
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v8i2.17995

Abstract

Short Message Service (SMS) is a technology for sending messages in text format between two mobile phones that support such a facility. Despite the emergence of many mobile text messaging applications, SMS still finds its use in communication among people and broadcasting messages by governments and mobile providers. SMS users often receive messages from parties, particularly for marketing and business purposes, advertisements, or elements of fraud. Many of those messages are irrelevant and fraudulent spam. This research aims at developing android-based applications that enable the filtering of SMS in Bahasa Indonesia. We investigate 1469 SMS text data and classify them into three categories: Normal, Fraudulent, and Advertisement. The classification or filtering method is the long short-term memory (LSTM) model from TensorFlow. The LSTM model is suitable because it has cell states in the architecture that are useful for storing previous information. The feature is applicable for use on sequential data such as SMS texts because every word in the texts constructs a sequential form to complete a sentence. The observation results show that the classification accuracy level is 95%. This model is then integrated into an Android-based mobile application to execute a real-time classification.
Risk Management in Software Development Projects: A Systematic Literature Review Marzuki Pilliang; Munawar Munawar
Khazanah Informatika Vol. 8 No. 2 October 2022
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v8i2.17488

Abstract

Risk Management is an integral part of every project. Risk management must estimate the risks’ significance, especially in the SDLC process, and mitigate those risks. Since 2016, many papers and journals have researched planning, design, and risk control in software development projects over the last five years. This study aims to find the most exciting topics for researchers in risk management, especially in software engineering projects. This paper takes a systematic approach to reviewing articles containing risk management in software development projects. This study collects papers and journals included in the international online library database, then summarizes them according to the stages of the PICOC methodology. This paper results in the focus of research in the last five years on Agile methods. The current issue is that many researchers are trying to explicitly integrate risk management into the Agile development process by creating a comprehensive risk management framework. This SLR helps future research get a theoretical basis to solve the studied problem. The SLR explains the focuses of previous research, analysis of research results, and the weaknesses of the investigation. For further study, take one of the topic papers, do a critical review, and find research gaps.
Recommendation System to Propose Final Project Supervisors using Cosine Similarity Matrix Zulfa Fajrul Falah; Fajar Suryawan
Khazanah Informatika Vol. 8 No. 2 October 2022
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v8i2.16235

Abstract

The selection of a supervisor is an important thing and one of the determinants of whether or not a student's final project research is successful. At the location of this research, students select a supervisor by considering his academic records, and recommendations from classmates or seniors. Words of mouth dominate their motivation, and many students do not have a basis for their choice. Selection of the fit supervisor has a significant impact on students' progression. Students will be more enthusiastic about doing the final project and may get facilitation in their research because the topics of students' projects match supervisors' interests and ongoing works. This study aims to make a recommendation system that suggests a supervisor for a student. The student fills in the title, abstract, and keywords of his proposal. The application proposes a prospective supervisor by calculating the similarity of the data with titles, abstracts, and keywords of published articles found in Google Scholar. This recommendation system uses the content-based filtering method to produce a list of recommendations. The cosine similarity algorithm calculates how similar the topic proposed by students is to the lecturer's interests. In building a website-based recommendation system, the author uses two Django web frameworks as the backend and ReactJs as the frontend. The system is successful in suggesting final project supervisors that have matched interest and expertise with students' proposals.
Backtracking and k-Nearest Neighbour for Non-Player Character to Balance Opponent in a Turn-Based Role Playing Game of Anagram Yosa Aditya Prakosa; Alfa Faridh Suni
Khazanah Informatika Vol. 8 No. 2 October 2022
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v8i2.16902

Abstract

Anagram is a turn-based role-playing game where two players construct words by arranging given letters. A significant aspect of playing a game is the challenge. A good challenge comes from an opponent with a close ability. In a two-player game like Anagram, the second player can be a nonhuman player called Non-Playable Character (NPC). A balanced game is more engaging. Therefore, it is imperative to insert artificial intelligence (AI) into an NPC to make it possess a balance ability. This study investigates the AI algorithm that is the most appropriate to make a balance NPC for Anagram games. We tested three scenarios: Descending AI, Random AI, and AI with k-Nearest Neighbour (k-NN). Descending AI gets an Anagram solution by selecting a word with the highest score from all possible answers. Random AI picks a word randomly from the possible answers, while AI with k-NN chooses a word closest to one of the human players. The results show that Descending AI is the best algorithm to make the strongest NPC, which always gets the highest score, followed by Random AI and AI with k-NN. However, AI with the k-NN algorithm makes the constructed NPC has the highest number of turns at an average of 18, while Descending AI gets 14 turns and Random AI has 15 turns. Looking at the remaining lives at the end of the game, AI with k-NN makes the NPC has 25 lives left, while Descending AI has 59 lives, and Random AI has 48 lives. Less remaining lives suggest that NPC containing AI with the k-NN algorithm matches closer to the human player and therefore is more suitable for Anagram NPC.
Object Detection to Identify Shapes of Swallow Nests Using a Deep Learning Algorithm Denny Indrajaya; Adi Setiawan; Djoko Hartanto; Hariyanto Hariyanto
Khazanah Informatika Vol. 8 No. 2 October 2022
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v8i2.16489

Abstract

Object detection is basic research in the field of computer vision to detect objects in an image or video. the TensorFlow framework is a widely adopted framework to create object detection programs and models. In this study, an object detection program and model are designed to detect the shape of a swallow's nest which consists of three classes, namely oval, angular, and bowl. The purpose model creation is to find out the likeliness of the swallow's nest to the three classes for the swallow's nest sorting machine. The adopted architecture in the modeling is the MobileNet V2 FPNLite SSD since the model obtained from this architecture results in a good speed in detecting objects. Based on the evaluation results that has been carried out, the model can detect the shape of the swallow's nest which is divided into 3 classes, but in some cases swallow's nest are detected into two classes. This issues can still be handled by adjustmenting several parameterss to the object detection program. Results shows that the obtained mAP value of 61.91%, indicating the model can detect the shape of a swallow's nest moderately.
Development of Information and Management System of Student Competition Groups through User-Centered Design Approach Dinan Yulianto; Ahmad Raditya Cahya Baswara; Lugas Alhawariy; Marina Indah Prasasti; Gema Antika Hariadi
Khazanah Informatika Vol. 9 No. 1 April 2023
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v9i1.17974

Abstract

The majority of universities in Indonesia make maximum efforts to participate and excel in the implementation of the Student Creativity Program (namely: PKM). PKM requires students to collaborate interdisciplinary or multidisciplinary. The problem at the beginning of PKM implementation is establishing groups, where students find it difficult to have fellow students or supervisors from different disciplines in groups and according to the topic of their PKM. This research develops a user-oriented interaction and interface of information systems and group management. Development was carried out through a User-Centered Design which consisted of the following stages: plan the human-centered process; understand and specify the context of use; specify the user requirements; produce design solutions to meet user requirements; and evaluate the design against the requirements. Testing using System Usability Scale (SUS) and User Experience Questionnaire (UEQ) approach were conducted on 30 respondents who had competencies as business analysts, programmers, and testers. The results of the mean score of the SUS test are 80, and the mean Score of the UEQ test on the Attractiveness variable is 1.922, Clarity is 2.158, Efficiency is 2.042, Accuracy is 1.708, Stimulation is 1.967, and Novelty is 1.917. The system has achieved the goals and user experience because all the testing scores are above the standard provisions.
Serious Game to Training Focus for Children with Attention Deficit Hyperactivity Disorder: “Tanji Adventure to the Diamond Temple” Raden Bagoes Yudha Rangga Sanjaya; Rahadian Kurniawan; Sri Mulyati; Kukuh Eka Nugraha Chrisna Putra; Restu Rakhmawati
Khazanah Informatika Vol. 9 No. 1 April 2023
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v9i1.18393

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) affects the academic performance of youngsters. Children with ADHD struggle to remain focused during learning due to decreased attention and concentration. They are highly active and have trouble remembering teachers' instructions. Attention difficulties, focus disorders, and hyperactivity might hinder learning. This work aims to observe the impact of serious games with a platformer genre and puzzles titled "Tanji Adventure to the Diamond Temple" on the learning activities of kids with ADHD. The goal is to create a fun and engaging learning environment to boost the motivation and focus of those with ADHD. Game development process utilizes iterative prototyping. Each iteration yields a prototype that refines in the next iteration. The game was tested on children with ADHD by examining their behavior before and after playing to evaluate whether new game mechanics were necessary. The review procedure includes observing youngsters and interviewing teachers and involves specialists to evaluate its contents. The study confirms that the concentration of children with ADHD increase after playing the game. The game incorporates elements that help youngsters with ADHD concentrate and increase their attention span
Medical External Wound Image Classification Using Support Vector Machine Technique Syifa'ah Setya Mawarni; Murinto Murinto; Sunardi Sunardi
Khazanah Informatika Vol. 9 No. 2 October 2023
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v9i2.22541

Abstract

Diagnosis is an activity that refers to the examination of something. Diagnosis is often associated with medical activities as a determinant of a person's condition, in the health sector diagnosis means a procedure performed by a doctor to determine a patient's condition. Unfortunately, it is rare to diagnose disease using an object wound, whereas if the wound is not treated immediately it can lead to more serious illnesses such as ulcers and tetanus or in some cases it can cause infection which then becomes a complication, in the worst case amputation occurs. The skin protects the body from various threats, the skin is also the first fortress for the body. Before implementing a prototype external wound diagnosis, it is necessary to test the accuracy of the algorithm to be used. The algorithm that can be used for diagnosis or classification is the Support Vector Machine or SVM which in the process goes through 3 stages, namely data collection, preprocessing, and classification. This research obtained the results of feature extraction on the wound image test data using GLCM with a contrast value of 0.0082, a correlation value of 0.9769, an energy value of 0.6391, and a homogeneity value of 0.9959 as well as the accuracy of using the SVM algorithm which was measured using a confusion matrix to get an accuracy value of 96.39%, 93.06% precision, recall 92.85%, and F1-score 92.58%. The results of the accuracy of the classification of external wound images using the SVM algorithm are 92.85%.

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