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Muhammad Taufiq Nuruzzaman
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JISKa (Jurnal Informatika Sunan Kalijaga)
Published by Universitas Islam Negeri Sunan Kalijaga Yogyakarta
ISSN : 25275836     EISSN : 25280074     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Library & Information Science
JISKa (Jurnal Informatika Sunan Kalijaga) adalah jurnal yang mencoba untuk mempelajari dan mengembangkan konsep Integrasi dan Interkoneksi Agama dan Informatika yang diterbitkan oleh Departemen Teknik Informasi UIN Sunan Kalijaga Yogyakarta. JISKa menyediakan forum bagi para dosen, peneliti, mahasiswa dan praktisi untuk menerbitkan artikel penelitiannya, mengkaji artikel dari para kontributor, dan teknologi baru yang berkaitan dengan informatika dari berbagai disiplin ilmu
Arjuna Subject : -
Articles 231 Documents
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Pembatasan Akses Menggunakan MAC Address dengan Metode Access Control List Muhammad Aditya Rabbani Adit; Martanto Martanto; Yudhistira Arie Wijaya
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 7 No. 3 (2022): September 2022
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2022.7.3.143-162

Abstract

The Cangehgar Cyber Command Center of the 14th Arhanud/ PWY Battalion from Cirebon City is one of the offices with IT equipment to assist the job. The servers, like the office PCs, are connected via the local network. Due to the risk of leaking secret data from within, network security concerns must be handled so that unauthorized users cannot mistakenly access the server. It seeks to limit access when there are administrative customers and employees in each room by utilizing the access control list approach using a MAC address. Access to the server is restricted to the administrator's computer, while access to the employee's PC is disallowed. Then the questionnaire was distributed to find out the respondent's assessment of the access control list. According to the results of the study on security indicators, access control lists containing MAC addresses are useful in limiting access to server computers.
Sistem Pendukung Keputusan Kesesuaian Lahan Tanaman Padi Menggunakan Metode AHP dan SAW Siti Retno Wulandari; Hamdani Hamdani; Anindita Septiarini
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 7 No. 3 (2022): September 2022
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2022.7.3.226-236

Abstract

Rice is one of the staple foods for most of the world's population. However, in planting rice, there are several things that must be considered, namely the aspect of land suitability. Errors in land determination can cause crop failure which results in reduced rice production. This system was built based on the website using the Analytical Hierarchy Process (AHP) method to calculate the weight of the criteria and the Simple Additive Weighting (SAW) method to determine the selection of land suitability for rice plants. In determining the suitability of paddy fields using 5 criteria, namely soil type, soil pH, rainfall, temperature, and irrigation waters. The purpose of this research is to assist farmers/farmer groups in selecting land. The results of this study indicate that the AHP and SAW methods have been successfully applied in the system with the results of land recommendations in the Sungai Kunjang sub-district with a preference value of 0,989.
Prototipe Alat Ukur Detak Jantung Menggunakan Sensor MAX30102 Berbasis Internet of Things (IoT) ESP8266 dan Blynk Muthmainnah Muthmainnah; Deni Bako Tabriawan
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 7 No. 3 (2022): September 2022
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2022.7.3.163-176

Abstract

The heart is an important organ of the human body. The heart functions to pump blood throughout the body. Health conditions can be seen in the condition of heart function. The heart’s function can be known through the beat when pumping blood.  The manufacture of a heart rate device has been carried out using the PPG method. This tool uses the MAX30102 sensor as input. The measurement results are displayed on the smartphone. This tool can calculate the heart rate by sticking the surface of the fingertips for ten seconds. The light waves emitted by the sensor source will hit the surface of the finger. Changes in blood volume cause changes in light intensity according to what is received by the sensor. Based on the test results, the average standard deviation of this tool's heart rate measurement is 1.176. If considered the data from the pulse oximeter is correct, then this tool has an accuracy of 98.804%.
Evaluasi Kesuksesan Penerapan Sistem Elektronik Kinerja (E-Kinerja) Menggunakan Enhanced Information System Success Model di Kecamatan Benda Tangerang Latansa Amalia; Anik Hanifatul Azizah
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 7 No. 3 (2022): September 2022
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2022.7.3.192-210

Abstract

E-Kinerja Benda District Tangerang City is an E-Government in the form of an Employee Performance Management Information System in charge of recording and reporting the performance of all employees in the government environment. The system should aim to simplify employee performance management and measure the efficiency and creativity of employees at work, in its implementation, there are still problems that occur. Many employees complain about the system, the implementation of the E-Kinerja system either directly or indirectly is considered troublesome, the internet network is not widely connected, the presence of technology devices (computers) is limited, and the lack of employees in understanding and utilizing the E-Kinerja system, and the lack of attendance and knowledge of information about IT as part of the supporting components in the process of presenting the information. So that an evaluation of the application of E-Kinerja is carried out, with the aim of this study being able to measure evaluation to prove the success rate of implementing E-Kinerja-based performance evaluations in Benda District, Tangerang City and knowing what factors or variables influence it. This study evaluates success using the Enhanced Information System Success Model with 7 evaluation variables: information quality, system quality, service quality, user satisfaction, trust, use, and net benefits. This study will use a qualitative and quantitative data approach through observation, interviews, literature studies, and questionnaires where the total respondents obtained are 62 respondents with PLS-SEM data analysis and SmartPLS 3.3 assistance. Based on the results of the research conducted, it is proven that from the 14 hypotheses proposed there are 5 hypotheses accepted while 9 other hypotheses are rejected. This evaluation also produces recommendations from the seven variables used which contain alternatives to improve and increase the success of the implementation of E-Kinerja.
Pengenalan Tulisan Tangan Huruf Latin Bersambung Menggunakan Local Binary Pattern dan K-Nearest Neighbor Vivin Oktavia; Novan Wijaya
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 7 No. 3 (2022): September 2022
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2022.7.3.211-225

Abstract

There are 26 Latin letters in Indonesia, 5 of which are vowels and 21 consonants. This study will translate handwriting with a Latin object using the K-Nearest Neighbor method with the Local Binary Pattern extension. The research is being done with a focus on experimentation using a few methods that have already been discussed. Concatenated Latin letters have a few variations that depend on the work's author, so research will be conducted to identify cursive Latin letters based on these variations. Each of the 30 respondents wrote 26 capital letters and 26 lowercase letters on paper, which was then scanned to provide the image data. Black, blue, and red pens were used to write by every ten responders. The recognition procedure is broken into two halves, capital and non-capital letter recognition using 780 picture datasets each. In the study, k-fold cross-validation is used, with k = 6. The best value was reached at k = 7 with 29.49 percent accuracy, 33.88 percent precision, recall 33.46 percent, and F1-score 27.65 percent according to the research utilizing KNN with values k = 3, 5, and 7. and for recognizing non-capital characters, the best result was found at k=3 with accuracy, precision, recall, and F1-score of 26.28, 27.27, and 22.7%, respectively.
Optimasi Seleksi Fitur Information Gain pada Algoritma Naïve Bayes dan K-Nearest Neighbor Muhammad Norhalimi; Taghfirul Azhima Yoga Siswa
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 7 No. 3 (2022): September 2022
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2022.7.3.237-255

Abstract

There was an increase in the number of late payments of tuition fees by 3,018 from a total of 5,535 students at the end of 2020. This study uses the Python library which requires data to be of numeric type, so it requires data transformation according to the type of data in the study, data that has a scale is transformed using an ordinal encoder, and data that does not have a scale is transformed using one-hot encoding. The purpose of this study was to evaluate the performance of the Naïve Bayes algorithm and K-Nearest Neighbor with a confusion matrix in predicting late payment of tuition fees at UMKT. The dataset used in this study was sourced from the financial administration bureau as many as 12,408 data with a distribution of 90:10. Based on the results of the calculation of the selection of information gain features, the best 4 attributes that influence the research are obtained, namely faculty, study program, class, and gender. The results of the evaluation of the confusion matrix that have the best performance using the Naïve Bayes with information gain algorithm obtain an accuracy of 55.19%, while the K-Nearest Neighbor with information gain only obtains an accuracy of 50.76%. Based on the accuracy results obtained in the prediction of late payment of tuition fees by using attributes derived from information gain, it influences increasing the accuracy of Naïve Bayes, but the use of the information gain attribute on the K-Nearest Neighbor algorithm makes the accuracy obtained decrease.
Summarizing Online Customer Review using Topic Modeling and Sentiment Analysis Muhammad Rifqi Maarif
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 7 No. 3 (2022): September 2022
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2022.7.3.177-191

Abstract

With the massive implementation of social media in various forms in various business domains, business or product owners have the opportunity to be able to take advantage of user review data that is available free of charge to evaluate the products they issue. User reviews on social media platforms, marketplaces, and e-commerce are User Generated Content (UGC) which is very useful for product owners to find out the extent of user preferences for their products. However, to be able to comprehensively read the data, the right technology is needed considering that the data is in the form of text in very large quantities. Reading one by one and then drawing conclusions is certainly not the right approach because it will take quite a lot of time. So, in this study, the researcher will use a text analysis-based approach, especially topic modeling and sentiment analysis to summarize user reviews in the comments or reviews column on the e-commerce platform. The case study used in this study is user reviews in the comments column on the Amazon site for the Lenovo K8 Note smartphone product. From the experiments carried out, the approach used can summarize the reviews written by quite many users in one summary that can be easily understood.
Pengelompokan Obyek Wisata Potensial dengan Self Organizing Maps (SOM) dan Sum Additive Weighting (SAW) Indra Dharma Wijaya; Muhammad Afif Hendrawan; Nurcahya Nania Anabela
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 8 No. 1 (2023): Januari 2023
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2023.8.1.1-9

Abstract

Probolinggo Regency is an area in East Java that has tourism potential. The condition is seen from the many tourists visiting various attractions in Probolinggo Regency. To increase the number of tourist visits, it is necessary to develop tourism objects. However, not all attractions in Probolinggo Regency can be developed at the same time. This is due to budget limitations for tourism development. Therefore, it is necessary to have a grouping of attractions according to the priority level of development. In this study, researchers utilized Self Organizing Maps (SOM) and Sum Additive Weighing (SAW) methods to group attractions based on their development priority levels. SOM is used to determine groups of tourist objects based on the parameters of the number of domestic tourists, the number of foreign tourists, infrastructure, and the number of attractions. Furthermore, SAW is used to find out which group has the highest priority among other groups based on these parameters. To measure the quality of the resulting group, researchers used the value of the silhouette coefficient. Results from the grouping process resulted in three groups. Group C1 consists of 4 attractions, group C2 consists of 20 attractions, and group C3 consists of 10 attractions. The value of the silhouette coefficient also holds a good value, especially in group 1, which is 0.75006. Furthermore, based on the ranking of groups by the SAW method, the C1 group is the group of tourist attractions with the highest priority for development.
Penerapan Data Mining dengan Metode Regresi Linear untuk Memprediksi Data Nilai Hasil Ujian Menggunakan RapidMiner Muhammad Sholeh; Erna Kumalasari Nurnawati; Uning Lestari
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 8 No. 1 (2023): Januari 2023
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2023.8.1.10-21

Abstract

Prediction is one of the methods in data mining. One of the models that can be used in prediction is using linear regression. Linear regression is used to make predictions on the data that has been provided. In this study, a linear regression model was made with a datasheet containing data that affected student achievement in achieving final exam scores. The linear regression model developed can be used to predict student test scores. The linear regression model developed can be used to predict student test scores. The datasheet used in the test uses a public datasheet, namely student_performance.csv. The datasheet consists of 395 records and 33 attributes. The attributes used are selected that influence the label. The selection of attributes is based on the results of the weighting in the process of checking the correlation matrix. Based on the weighting, the attributes used are seven attributes and one attribute becomes a label. The research method uses CRISP DM which consists of business understanding, data understanding, data preparation, model making, evaluation, and deploying. The data mining process uses the Rapid Miner application. The results of the study resulted in a linear regression model y=0.729-(0.024×Medu)-(0.020×Fedu)+(0.053×failures)-(0.077×goout)-(0.012×absences)+(0.126×G1)+(0.862×G2). The result of evaluating the performance of the RMSE value was 0.675. Based on these results, it can be concluded that the resulting model can be recommended for use in predicting student test scores.
Perbandingan Waktu Respon Aplikasi Database NoSQL Elasticsearch dan MongoDB pada Pengujian Operasi CRUD Theresia Liana Sinaga; Novrido Charibaldi; Nur Heri Cahyana
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 8 No. 1 (2023): Januari 2023
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2023.8.1.22-35

Abstract

Currently, humans live in an era of data oceans, where the amount of data production is increasing from time to time, which is followed by severe challenges in terms of processing, storing, and analyzing data, especially big data. The increase in the number of large data production can affect the speed of access to the database, effectiveness, and speed of response time in the data processing. Relational databases have been the leading model for data storage, analysis, processing, and retrieval for more than forty years. However, due to the increasing need for large-scale data storage, the scalability and performance of a data processing system, as well as the constant growth of the amount of data, another alternative to databases emerged, namely NoSQL technology. Based on previous studies regarding the comparison of response time and database performance, the average concludes that NoSQL performance is more effective and efficient than relational databases. Based on the implementation and testing, it can be concluded that the NoSQL database application MongoDB is proven to be superior in every command of CRUD tested compared to the Elasticsearch NoSQL database application, where in testing the create data command with a JSON file, the MongoDB database application is 42.5 times faster than the Elasticsearch database application. In testing the command to create data into a database containing different amounts of data, the MongoDB database application is 333.9 times faster than the average response time of the Elasticsearch database application. In testing the read command for data in a database containing different amounts of data, the MongoDB database application is 35.5 times faster than the Elasticsearch database application. In testing the update operation of data in a database containing different amounts of data, the MongoDB database application is 9.8 times faster than the Elasticsearch database application. in testing the delete operation of data in a database containing different amounts of data, the MongoDB database application is 58.9 times faster than the Elasticsearch database application.

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