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JISKa (Jurnal Informatika Sunan Kalijaga)

JISKA
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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 7 Documents

Search results for , issue "Vol. 6 No. 3 (2021): September 2021" : 7 Documents clear

Implementasi Deep Learning untuk Entity Matching pada Dataset Obat (Studi Kasus K24 dan Farmaku) Rivanda Putra Pratama; Rahmat Hidayat; Nisrina Fadhilah Fano; Adam Akbar; Nur Aini Rakhmawati
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 3 (2021): September 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Data processing speed in companies is important to speed up their analysis. Entity matching is a computational process that companies can perform in data processing. In conducting data processing, entity matching plays a role in determining two different data but referring to the same entity. Entity matching problems arise when the dataset used in the comparison is large. The deep learning concept is one of the solutions in dealing with entity matching problems. DeepMatcher is a python package based on a deep learning model architecture that can solve entity matching problems. The purpose of this study was to determine the matching between the two datasets with the application of DeepMatcher in entity matching using drug data from farmaku.com and k24klik.com. The comparison model used is the Hybrid model. Based on the test results, the Hybrid model produces accurate numbers, so that the entity matching used in this study runs well. The best accuracy value of the 10th training with an F1 value of 30.30, a precision value of 17.86, and a recall value of 100.

Klasifikasi Tingkat Kepuasan Mahasiswa Terhadap Pembelajaran Secara Daring Menggunakan Algoritma Naïve Bayes Ami Natuzzuhriyyah; Nisa Nafisah; Rini Mayasari
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 3 (2021): September 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Since the spread of Covid-19 in Indonesia, in early March 2020, the activities of Educational Institutions have not been disrupted. As conventional learning. Learning at Singaperbangsa University began with regulation from the Ministry of Education and Culture of the Republic of Indonesia, from learning that boldly affects concentration, influences concentration, such as signals, learning atmosphere, and teaching methods, so that factors affect the level of student satisfaction in learning. This study aims to determine the level of student satisfaction with learning who dares to use the Bayes naive algorithm using RapidMiner tools with results obtained with an accuracy rate of 76.92%, class precision of 100.00%, class recall 57.14%, and an AUC value of 0.881 or close to, so the resulting model is good. In other words, the results obtained using the Naïve Bayes algorithm can be used as material for making decisions about the level of online learning satisfaction.

Optimasi Keamanan Web Server terhadap Serangan Broken Authentication Menggunakan Teknologi Blockchain Imam Riadi; Herman; Aulyah Zakilah Ifani
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 3 (2021): September 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

The aspect of the internet that needs to be considered a security is the login system. The login system usually uses a username and password as an authentication method because it is easy to implement. However, data in the form of usernames and passwords are very vulnerable to theft, so it is necessary to increase the security of the login system. The purpose of this research is to investigate the security of the system. Whether the system is good at protecting user data or not, minimizing execution errors from the system and minimizing risk errors on the system so that the login system can be used safely. This research is conducted to test the system security with Burp Suite on the login system that has been built. Testing the security of this system by experimenting with POST data which is secured using blockchain technology makes the data sent in the form of hash blocks safer and more confidential so that the system is safer than before. Blockchain technology has successfully secured usernames and passwords from broken authentication attacks. By using the Burp Suite testing system, login is more specific in conducting security testing.

Implementasi Algoritma RC4 pada Sistem Pengamanan Dokumen Digital Soal Ujian Fauziyah Suwarsita Febriyani; Arief Arfriandi
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 3 (2021): September 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

The development of science and technology has led to changes in the use of documents in life to become digital data. However, this can cause problems, namely regarding data security and confidentiality. To increase security and confidentiality can be done with cryptographic algorithm RC4. The research method uses the Waterfall method. The result of this research is a website that can secure document files with * doc extension using the RC4 algorithm. The test was carried out using the blackbox test and the CrackStation test for encryption testing. The results of the test show that the website can run well and successfully implements the RC4 algorithm.

Peramalan Pelayanan Service Mobil (After-Sale) Menggunakan Backpropagation Neural Network (BPNN) Novianti Puspitasari; Haviluddin; Arinda Mulawardani Kustiawan; Hario Jati Setyadi; Gubtha Mahendra Putra
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 3 (2021): September 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

The automotive industry in Indonesia, primarily cars, is getting more and more varied. Along with increasing the number of vehicles, Brand Holder Sole Agents (ATPM) compete to provide after-sale services (mobile service). However, the company has difficulty knowing the rate of growth in the number of mobile services handled, thus causing losses that impact sources of income. Therefore, we need a standard method in determining the forecasting of the number of car services in the following year. This study implements the Backpropagation Neural Network (BPNN) method in forecasting car service services (after-sale) and Mean Square Error (MSE) for the process of testing the accuracy of the forecasting results formed. The data used in this study is car service data (after-sale) for the last five years. The results show that the best architecture for forecasting after-sales services using BPNN is the 5-10-5-1 architectural model with a learning rate of 0.2 and the learning function of trainlm and MSE of 0.00045581. This proves that the BPNN method can predict mobile service (after-sale) services with good forecasting accuracy values.

Analisis Perbandingan Algoritma Decision Tree, kNN, dan Naive Bayes untuk Prediksi Kesuksesan Start-up Adhitya Prayoga Permana; Kurniyatul Ainiyah; Khadijah Fahmi Hayati Holle
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 3 (2021): September 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Start-ups have a very important role in economic growth, the existence of a start-up can open up many new jobs. However, not all start-ups that are developing can become successful start-ups. This is because start-ups have a high failure rate, data shows that 75% of start-ups fail in their development. Therefore, it is important to classify the successful and failed start-ups, so that later it can be used to see the factors that most influence start-up success, and can also predict the success of a start-up. Among the many classifications in data mining, the Decision Tree, kNN, and Naïve Bayes algorithms are the algorithms that the authors chose to classify the 923 start-up data records that were previously obtained. The test results using cross-validation and T-test show that the Decision Tree Algorithm is the most appropriate algorithm for classifying in this case study. This is evidenced by the accuracy value obtained from the Decision Tree algorithm, which is greater than other algorithms, which is 79.29%, while the kNN algorithm has an accuracy value of 66.69%, and Naive Bayes is 64.21%.

Perbandingan Faktor-Faktor Yang Mempengaruhi Penggunaan Electronic-Know Your Customer (e-KYC) Mr. Fitree Tahe; Maria Ulfah Siregar; Mohammad Farhan Qudratullah
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 3 (2021): September 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

There are many technological developments in banks, one of which is online transactions. To get these transactions, an account should be opened using the electronic know you customer (e-KYC) verification system at banks. This research wants to know the differences in the factors that influence behavioral intentions to use e-KYC at SCB (The Siam Commercial Bank) Thailand and Bank Mandiri Indonesia. This is a quantitative research using a survey. The researcher has prepared a questionnaire of 160 respondents: 80 for Bank Mandiri and 80 for SCB. The results indicate that the willingness of Bank Mandiri Indonesia’s respondents to use electronic identity verification services is influenced by smaller factors compared to SCB Thailand’s respondents. In total, all of the factors defined in this research is influenced the willingness.

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Muhammad Taufiq Nuruzzaman

Contact Email
m.taufiq@uin-suka.ac.id

Phone
+6287708181179

Journal Mail Official
jiska@uin-suka.ac.id

Editorial Address
Teknik Informatika, Fak. Sains dan Teknologi, UIN Sunan Kalijaga Jln. Marsda Adisucipto No 1 55281 Yogyakarta

Location
Kab. sleman,

Daerah istimewa yogyakarta

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Muhammad Taufiq Nuruzzaman

Contact Email m.taufiq@uin-suka.ac.id

Phone +6287708181179

Journal Mail Official jiska@uin-suka.ac.id

Editorial Address Teknik Informatika, Fak. Sains dan Teknologi, UIN Sunan Kalijaga Jln. Marsda Adisucipto No 1 55281 Yogyakarta

Location Kab. sleman, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Muhammad Taufiq Nuruzzaman

Contact Email
m.taufiq@uin-suka.ac.id

Phone
+6287708181179

Journal Mail Official
jiska@uin-suka.ac.id

Editorial Address
Teknik Informatika, Fak. Sains dan Teknologi, UIN Sunan Kalijaga Jln. Marsda Adisucipto No 1 55281 Yogyakarta

Location
Kab. sleman,

Daerah istimewa yogyakarta

INDONESIA