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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 250 Documents
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Application of the Certainty Factor and Forward Chaining Methods to a Goat Disease Expert System Susanto, Dwi; Fadlil, Abdul; Yudhana, Anton
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.10867

Abstract

Goats are livestock that is financially very attractive to rural Indonesian. Efforts to solve problems related to goat farming are necessary. One of them is maintaining the health of the cattle by knowing how to cope with disease-stricken goats. Goat productivity will decrease if the treatment of the disease is sub-optimal. Goat diseases are very diverse, ranging from mild to severe. Breeders themselves can traditionally treat several diseases without the involvement of veterinarians or experts. However, a larger number of diseases need treatment with the help of experts. Expert systems are a potential solution to help farmers. It will automatically suggest decisions or conclusions in solving a problem. This study observes an expert system built using the Certainty Factor combined with Forward-Chaining. By combining the two methods, the information generated may discover the type of disease and suggest its management effectively with a high degree of certainty. The system can expectedly become a reference for goat breeders to consult about their goat livestock diseases. The knowledge base of the system uses 21 types of symptoms, eight types of diseases, and their solutions. The user does not need to input the belief value and the disbelief value that is usually input in the expert system. By involving the admin as a knowledge base processor, the correctness of the conveyed information maintains.
Design and Implementation of a Smart Home Security System Using Voice Command and Internet of Things Susanto, Heru; Nurcahyo, Agus
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.9320

Abstract

A smart home security system consists of various sensors and recorders to automatically provide data on the conditions of a house. Home electronic equipment may be controlled from distant places using the internet of things technology and speech recognition. This research aims to develop a smart home security system by monitoring fire hazards and theft. It helps also control electronic equipment using voice commands that is useful especially for the disabled. The system design consists of hardware, software, and application design. Hardware design uses ESP8266, Arduino Mega 2560, MicroSD Card module, VC0706 serial camera, DHT22, magnetic door switch, PIR HC SR501, and Google Assistant device. Software design uses Arduino IDE for programming Arduino Mega and ESP8266. Applications used in the design are Adafruit.io, Thingspeak, and IFTTT (If This Then That). Voice commands control home electronic devices (lights), while fire and theft are monitored through the use of sensors and cameras. The system test shows that voice command can control lights on and off at an accuracy of 88%. Temperature and humidity sensors acquire data and send them to Thingspeak application for online fire monitoring. Sensors to detect intruders in the form of door switch and PIR work well and automatically activate cameras that capture objects to store in a MicroSD card.
E-Prescription: Connecting Patients’ Prescriptions with Pharmacists and Cashiers Susilawati, Helfy; Wiharso, Tri Arif
Khazanah Informatika Vol. 7 No. 1 April 2021
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.12191

Abstract

The paper describes the development of an electronic prescription system. Electronic prescription or e-prescription is an innovation in the health sector that enables patients to read the types of medication they will receive along with its description and rational use. E-prescription shortens the waiting time to get a prescription, which is different from a manual prescription system. In conventional systems, patients must undergo several steps to get served. They have to give the prescriptions to the cashier and wait for the cashier to calculate the bill. They later submit the proof of payment to the pharmacists and wait for the pharmacist to produce the medicine. Using e-prescription, the patients only have to pay for prescription and wait for the pharmacists to bring the medicine. The waiting time may decrease from 4 complicated steps into 2 simple ones. The website-based e-prescription application enables physicians to electronically send prescriptions to pharmacy computers and send its bill to the cashier. The system allows patients to directly move to the pharmacy once they have paid the bill. The research adopts a quantitative method with a prototype research model and UAT (User Acceptance Test) model for testing.
Virtual Reality Visualization of Tongkonan Traditional House as Promotional Media for Cultural Tourism using ADDIE Model Hayat, Cynthia; Panggeso, David
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.11049

Abstract

Indonesia is a country that is rich in culture and customs. Indonesia also has great potential in the field of tourism, especially cultural tourism. The key to attracting tourist visitors lies in the information media provided. In this paper, a desktop-based application is developed with 3D virtual reality graphics model technology with Tongkonan traditional house from the Toraja tribe and their environment as the object. This 3D virtual reality visualization aims to be an interactive promotional media for the millennial generation in introducing cultural tourism, especially the Tongkonan traditional house of Toraja. In this application, the user can explore the traditional house objects as a whole – with the help of navigation control in the form of keyboard and mouse. The ADDIE model method was used in designing this desktop application. The user response test was used to measure respondents' attitudes toward the application using the Likert scale and succeeded in getting the very good category in 17 questionnaire statements and the good category in three questionnaire statements. Therefore, it can be concluded that the VR visualization of Tongkonan Traditional House can act as an interactive promotional media to the millennial generation.
Performance Analysis of Isolation Forest Algorithm in Fraud Detection of Credit Card Transactions Waspada, Indra; Bahtiar, Nurdin; Wirawan, Panji Wisnu; Awan, Bagus Dwi Ari
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.10520

Abstract

Losses incurred due to fraud on e-commerce transactions, especially those based on credit cards, continue to increase, resulting in large losses each year. One mechanism to minimize the risk of fraudulent credit card transactions is to utilize a detection technique for ongoing transactions. Credit card transaction data in its original state does not have a label, and the amount of fraud data on the training data is very small so that it belongs to a very unbalanced category, and the pattern of fraud continues to change. Isolation forest is an unsupervised algorithm that is efficient in detecting anomalies. Several techniques can be applied to improve the performance of the Isolation forest model. Previous studies used the ROC-AUC metric in analyzing the performance of Isolation Forests, which could provide incorrect information. This study made two contributions; the first is to present a performance analysis with both the ROC-AUC and AUCPR. Thus, it can be seen that the high ROC-AUC value does not guarantee the model has the reliability in detecting fraud. In comparison, the information provided through AUCPR is more appropriate to describe the ability of the model to capture data fraud. The second contribution is to propose several techniques that can be applied to improve the performance of the Isolation forest model, namely to optimize the determination of the amount of training data, feature selection, the amount of fraud contamination, and setting hyper-parameters in the modeling stage (training). Experiments were carried out using a real-life dataset from ULB. The best results are obtained when the validation data split ratio is 60:40, using the five most important features, using only 60% of fraud data, and setting hyper-parameters with the number of trees 100, 128 sample maximum, and 0.001 contamination. The validation performance of this model is precision 0.809917, recall 0.710145, F1-score 0.756757, ROC-AUC 0.969728, and AUCPR 0.637993, while for Testing results obtained precision 0.807143, recall 0.763514, F1-score 0.784722, ROC-AUC 0.97371, and AUCPR 0.759228.
Corn Seeds Identification Based on Shape and Colour Features Yafie, Haddad Alwi; Rachmawati, Ema; Prakasa, Esa; Nur, Amin
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.10840

Abstract

Corn is one of the agricultural products that are essential as daily food sources or energy sources. Corn selection or sorting is important to produce high-quality seeds before its distribution to areas with varying conditions and agricultural characteristics. Hence, it is necessary to build corn seeds identification. In this paper, we propose a corn seed identification technique that incorporates the advantage of combining shape and colour features. The identification process consists of three main stages, namely, ROI selection, feature extraction, and classification using the Artificial Neural Network (ANN) algorithm. The shape feature originates from the eccentricity value or comparison value between a distance of minor ellipse foci and major ellipse foci of an object. Meanwhile, the color features are extracted based on the HSV (Hue-Saturation-Value) channel. The experimental result shows that the proposed system achieves excellent performance for the identification of poor and good corn quality for BIMA-20 and NASA-29 species. The classification result for BIMA-20 Good vs. BIMA-20 Bad gives an accuracy of 89%, while the classification accuracy of BIMA-20 Good vs. NASA-29 Good is 97%.
Classification of Pandavas Figure in Shadow Puppet Images using Convolutional Neural Networks Supriyanti, Wiwit; Anggoro, Dimas Aryo
Khazanah Informatika Vol. 7 No. 1 April 2021
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v7i1.12484

Abstract

Indonesia is a nation with various ethnicities and rich cultural backgrounds that span from Sabang to Merauke. One of the cultural products of Indonesian society is shadow puppet. Shadow puppet has been internationally renowned as a masterpiece of cultural art and recognized by UNESCO. The development of Indonesian society is very dependent on technological sophistication and it may shift the existing traditional culture out from the memory of the nation. Practices of modern life and the busy activities of the people exacerbate the condition and may make the society to ignore traditional culture. This study seeks to preserve traditional Indonesian culture by making shadow puppets as the object of classification. We use a deep learning algorithm called convolutional neural network (CNN) to classify 430 puppet images into 4 classes. The proportion of training, validation and test data is 70 by 20 by 10. The experiments show that the most efficient model is obtained with 3 convolution layer. It reaches an accuracy rate of 0.93 and a drop out rate of 0.2
Combination of K-Means and Simple Additive Weighting in Deciding Locations and Strategies of University Marketing Kasri, Muhamad Ali; Jati, Handaru
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.11281

Abstract

Every year UNIMUDA Sorong welcomes new students and keeps promoting to attract more. The process generates a growing number of student data. On the other hand, the promotional strategy to attract new students faces obstacles such as generalization among locations, ineffective time, limited personnel to carry out promotions, and cost inefficiency. This study examines the new student data and university marketing strategies to optimize time, effort, and cost. It uses the K-Means method for data grouping and the Simple Additive Weighting (SAW) for ranking the results of data grouping. The result of this research suggests that the location of promotion may be determined from the clustering process using the K-Means method. The silhouette coefficient test invalidates the data clustering, and the SAW method helps the ranking process to obtain a sequence of promotion locations. The ranking results reflect the predetermined decision table that directs promotion location selection according to the promotion strategy. The combination of the two methods helps to decide the location and marketing strategy to optimize time, effort, and cost. The results of this study may be used as a comparative reference for the management to decide the right promotion strategy based on the locations and student background.
The e-Learning Quality Model to Examine Students’ Behavioral Intention to Use Online Learning Platform in a Higher Education Institution Muqtadiroh, Feby Artwodini; Herdiyanti, Anisah; Puspitasari, Noptrina
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.11344

Abstract

This paper aims to understand the behavioral intentions of students in using e-learning in a public university in Indonesia. We apply the e-learning quality model to observe the quality factors that trigger intentions. The quality factors include assurance, empathy, responsiveness, reliability, and website content. Understanding how these quality learning factors may affect a student’s behavior intention to use e-learning is important to bring e-learning implementation success. We collected 502 responses from university students at a public university in Indonesia that implements a Moodle-based e-learning platform – namely ShareITS. Out of 5 (five) quality learning factors, we found only 2 (two) that significantly affect the e-learning quality – i.e., responsiveness and website content. The result shows that the teacher-student engagement in the e-learning platform and also the better visual design of ShareITS can improve the quality of the e-learning platform.
Customer Satisfaction Analysis Based On SERVQUAL Method to Determine Service Level of Academic Information Systems on Higher Education Buditjahjanto, I Gusti Putu Asto
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.10690

Abstract

Higher education institutions such as universities or institutes that create graduate students with high qualifications must be able to provide the best services to their stakeholders. One kind of higher education service is academic information system services. The service quality level of the academic information system in a university can be decided by measuring the level of users’ perception and the level of users’ expectations that can be fulfilled. As an organization that offers academic information system services, the university must be able to measure the level of academic information system services as an approach to ensure the quality of services. This study aims to determine the level of customer satisfaction index in terms of service of higher education academic information systems using the service quality method. The service quality method is used to identify academic information system services that are analyzed based on the service quality dimensions. The results show that the value of the customer satisfaction index is 77.37% which refers to the satisfied category.

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