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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 32 Documents
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Search results for , issue "Vol. 6 No. 2 October 2020" : 32 Documents clear
Analysis of Communication Network Patterns of Home Industries (A Case Study in Tambaksari, Rowosari, Kendal) Maulan, Puteri Anidya; Manongga, Danny; Sembiring, Irwan
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.v6i2.10468

Abstract

Tambaksari is a village in Kendal Regency that has home industries (Industri Rumahan, IR). The local government classifies these industrial activities of BUMDes (Village-Owned Enterprises) into three groups, namely IR-1, IR-2, and IR-3. Each group or class has its specific criteria. The significant local potentials in Tambaksari include fish farming and processing. The advantage of the local potential in Tambaksari is inseparable from the synergy between the local government and the people of Tambaksari. This study observed the patterns of actor interactions in 64 IRs in Tambak Sari. Data were collected from questionnaires and analyzed using the Social Network Analysis (SNA) method. The results showed that Tambaksari IRs have a network density of 5.5%, which suggests that the relationship was weak. Network analysis using UCINET illustrates the separation of the IR group, which further reinforces the existence of competition in the network. The study reveals the dominant actor in the network interaction based on the measure of degree centrality, closeness centrality, and betweenness centrality. He is the actor with id # 29 who is the Chairman of IR-2, 54 years old, who has a Pindang Fish Processing.
Pesma Apps as Android-based Integrated Applications for Mahasantri Pesma KH Mas Mansur UMS Khafid, Bisrul; Putri, Devi Afriyantari Puspa
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.v6i2.10494

Abstract

Pesantren Mahasiswa Internasional KH Mas Mansur (Pesma) has a shuttle facility for everyone who lives there. However, the use of the shuttle is not optimal because the ordering procedure still uses manual techniques. It contrasts with the rapid development of industry 4.0 and the mission of Pesma to get digitalization. This paper describes the effort to improve Pesma shuttle bookings by developing an application. The application is built upon the Android Studio 3.5.1 platform and uses Firebase real-time database. The development method implements the System Development Life Cycle (SDLC), Waterfall. The research results in an application called “Pesma Apps” that can be used by staff and mahasantri. Testing the Pesma apps, we obtained sufficiently good results where the black box testing proves that all functions work well. A usability testing using SUS with 30 respondents produces a good result at the level of 72.6, which suggests that the application is accepted.
Utilization of Gas Sensor Array and Principal Component Analysis to Identify Fish Decomposition Level Sumanto, Budi; Fakhrurrifqi, Muhammad
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.v6i2.11013

Abstract

Fish meat is a source of minerals and protein and contains excellent nutrients for the human body. However, non-fresh (rotting) fish are sometimes in the market for sale. Consuming rotting fish puts people at risk of getting diseases. This paper describes research to build a smelling device (e-nose) to identify fish freshness. It aims at detecting unsafe fish flesh to sort them out from being sold. We cut red snapper into cubes and put them into an open space at room temperature for five days. During the period, a gas sensor array acquired data of gas smell from the rotting fish. The output voltage of the sensors was processed using the differential baseline method. Later, feature extraction took the maximum value from the response of the gas sensor array, while the Principle Component Analysis (PCA) method identified the pattern. The results suggest that the gas sensor array responds to changes in the smell of fish meat that undergo a decay process. The PCA method is capable of recognizing the pattern of the maximum value characteristic of the gas sensor array response, as evidenced by the cumulative values of PC1 and PC2 reaching 95.95% with an accuracy rate of 98.2%. It shows the correlation between the aroma profiles of fish meat during the spoilage process, which produces a sharper aroma due to microbiological growth in the fish meat.
Application of Context-Aware and Collaborative Mobile Learning System Design Model in Interactive E-Book Reader Using Design Thinking Methods Nalendro, Putu Aji; Wardani, Ratna
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.v6i2.10022

Abstract

E-books as a learning medium have been widely used and utilized to support learning processes. The presence of e-books as digital books can be accepted by users because of the interactive content and display. However, the current format of e-book has not provided a mechanism/platform that accommodates contemporary learning styles on a two-way networked learning basis. E-books are more static in the sense that it has minimal interaction context. E-books have not been able to integrate learners with their learning environment in an interaction construct to support a learning activity. To address this problem, this study recommends a new approach called context-aware and collaborative mobile learning system design model. The method used in implementing the design model is design thinking. Usability testing using the guerrilla usability testing method is carried out to determine the quality of the e-books produced. The results obtained at the stages of empathize and define produced list and learning problems experienced by students when using e-books. The ideate and prototype stages produced e-book prototypes developed based on context-aware and collaborative mobile learning system design model. In the test stage, usability testing of 30 students showed good results. It is said to be good because there are no assignments with a score of one in the rubric usability testing table. So it can be concluded that the design model applied to the prototype e-book is feasible and can be understood by users.
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.
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%.
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.

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