Publisher: Universitas Muhammadiyah Surakarta   (Total: 33 journals)   [Sort alphabetically]

Showing 1 - 33 of 33 Journals sorted by number of followers
JRAMathEdu : J. of Research and Advances in Mathematics Education     Open Access   (Followers: 5)
J. of Community Services and Engagement     Open Access   (Followers: 2)
Pharmacon : Jurnal Farmasi Indonesia     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access  
Media Mesin : Majalah Teknik Mesin     Open Access  
Sinektika : Jurnal Arsitektur     Open Access  
Iseedu : J. of Islamic Educational Thoughts and Practices     Open Access  
J. of Nutraceuticals and Herbal Medicine     Open Access  
Profetika Jurnal Studi Islam     Open Access  
Komuniti : Jurnal Komunikasi dan Teknologi Informasi     Open Access  
J. of Islamic Economic Laws     Open Access  
Indonesian J. on Learning and Advanced Education     Open Access  
Kajian Linguistik dan Sastra     Open Access  
Law and Justice     Open Access  
Suhuf     Open Access  
Jurnal Varidika     Open Access  
Benefit : Jurnal Manajemen dan Bisnis     Open Access  
Jurnal Kesehatan     Open Access  
Jurnal Jurisprudence     Open Access  
Jurnal Manajemen Dayasaing     Open Access  
Biomedika     Open Access  
Manajemen Pendidikan     Open Access  
Indigenous : Jurnal Ilmiah Psikologi     Open Access  
Riset Akuntansi dan Keuangan Indonesia     Open Access  
Forum Geografi     Open Access  
Tajdida : Jurnal Pemikiran dan Gerakan Muhammadiyah     Open Access  
Jurnal Pendidikan Ilmu Sosial     Open Access  
Warta LPM     Open Access  
Bioeksperimen : Jurnal Penelitian Biologi     Open Access  
Profesi Pendidikan Dasar     Open Access  
Khazanah Informatika     Open Access  
Jurnal Ekonomi Pembangunan : Kajian Masalah Ekonomi dan Pembangunan     Open Access  
Jurnal Ilmiah Teknik Industri     Open Access  
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Khazanah Informatika
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2477-698X
Published by Universitas Muhammadiyah Surakarta Homepage  [33 journals]
  • Recommendation System to Propose Final Project Supervisors using Cosine
           Similarity Matrix

    • Authors: Zulfa Fajrul Falah, Fajar Suryawan
      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.
      PubDate: 2022-10-30
      DOI: 10.23917/khif.v8i2.16235
      Issue No: Vol. 8, No. 2 (2022)
       
  • Android-Based Short Message Service Filtering using Long Short-Term Memory
           Classification Model

    • Authors: M. Laylul Mustagfirin, Giri Wahyu Wiriasto, I Made Budi Suksmadana, Indira Puteri Kinasih
      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.
      PubDate: 2022-10-30
      DOI: 10.23917/khif.v8i2.17995
      Issue No: Vol. 8, No. 2 (2022)
       
  • Object Detection to Identify Shapes of Swallow Nests Using a Deep Learning
           Algorithm

    • Authors: Denny Indrajaya, Adi Setiawan, Djoko Hartanto, Hariyanto Hariyanto
      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.
      PubDate: 2022-10-13
      DOI: 10.23917/khif.v8i2.16489
      Issue No: Vol. 8, No. 2 (2022)
       
  • Application of Low Back Pain Myogenic Therapy Based on Multimedia

    • Authors: Alfian Gema Negara, Niken Sylvia Puspitasari
      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.
      PubDate: 2022-10-13
      DOI: 10.23917/khif.v8i2.15645
      Issue No: Vol. 8, No. 2 (2022)
       
  • Backtracking and k-Nearest Neighbour for Non-Player Character to Balance
           Opponent in a Turn-Based Role Playing Game of Anagram

    • Authors: Yosa Aditya Prakosa, Alfa Faridh Suni
      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.
      PubDate: 2022-10-02
      DOI: 10.23917/khif.v8i2.16902
      Issue No: Vol. 8, No. 2 (2022)
       
  • Herbal Compound Screening with GPU Computation on ZINC Database through
           Similarity Comparison Approach

    • Authors: Refianto Damai Darmawan, Wisnu Ananta Kusuma, Hendra Rahmawan
      Abstract: Covid-19 is a global pandemic that drives many researchers to strive to look for its solution, especially in the field of health, medicine, and total countermeasures. Early screening with in-silico processes is crucial to minimize the search space of the potential drugs to cure a disease. This research aims to find potential drugs of covid-19 disease in the ZINC database to be further investigated through the in-vitro method. About 997.402.117 chemical compounds are searched about their similarity to some of the confirmed drugs to combat coronavirus. Sequential computation would take months to accomplish this task. The general programming graphic processing unit approach is used to implement a similarity comparison algorithm in parallel, in order to speed up the process. The result of this study shows the parallel algorithm implementation can speed up the computation process up to 55 times faster, and also that some of the chemical compounds have high similarity scores and can be found in nature
      PubDate: 2022-09-15
      DOI: 10.23917/khif.v8i2.16349
      Issue No: Vol. 8, No. 2 (2022)
       
  • Job Scheduling on Grid Computing Using First Fit, Best Fit, and Worst Fit

    • Authors: Ardi Pujiyanta
      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
      PubDate: 2022-09-15
      DOI: 10.23917/khif.v8i2.17069
      Issue No: Vol. 8, No. 2 (2022)
       
  • Risk Management in Software Development Projects: A Systematic Literature
           Review

    • Authors: Marzuki Pilliang, Munawar Munawar
      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.
      PubDate: 2022-09-15
      DOI: 10.23917/khif.v8i2.17488
      Issue No: Vol. 8, No. 2 (2022)
       
 
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