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INDONESIA
KLIK: Kajian Ilmiah Informatika dan Komputer
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : -     EISSN : 27233898     DOI : -
Core Subject : Science,
Computer Science & IT
Topik utama yang diterbitkan mencakup: 1. Teknik Informatika 2. Sistem Informasi 3. Sistem Pendukung Keputusan 4. Sistem Pakar 5. Kecerdasan Buatan 6. Manajemen Informasi 7. Data Mining 8. Big Data 9. Jaringan Komputer 10. Dan lain-lain (topik lainnya yang berhubungan dengan Teknologi Informati dan komputer)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 561 Documents
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Perancangan UI/UX Aplikasi Crowdfunding Syariah Untuk UMKM Menggunakan Metode User-Centered Design Thea Anugrah Felicia; Rahmat Fauzi; Faishal Mufied Al Anshary
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.1084

Abstract

The Indonesian economy is influenced by Micro, Small, and Medium Enterprises (MSMEs). Even though MSMEs are an important part of the Indonesian economy, they still need help developing their business, including capital problems. Of the total MSMEs, 17.5% can only get capital loans through banks, and 82.5% access capital from non-banks. Another problem MSMEs face is that their income still needs to be improved. Hence, they sometimes need help to make interest payments or repay the principal on loans. In addition, MSME actors need more assets for collateral when they want to make loans. Thus, it is necessary to develop a website-based crowdfunding application that can provide easy access to funding so that MSME actors can easily obtain capital and help develop the Islamic finance industry. The design of this website uses the user-centered design method. It has been tested with three iterations using maze tools with the first parameter value, namely the Usability Score (MAUS) with a value of 68, and the second parameter, namely the System Usability Scale (SUS) with a value of 67.67 with a Marginal acceptability range. In the second iteration, the Maze Usability Score (MAUS) is 79, and the System Usability Scale (SUS) is 74.25 with the Acceptability range Acceptable. Then, in the last iteration, the Maze Usability Score (MAUS) was 84, and the System Usability Scale (SUS) was 80.25 with the Acceptability range Acceptable. So with the results of these three iterations, the Tasha Sharia Crowdfunding website can meet user needs
Audit Sistem Informasi Aplikasi Fingerprint Menggunakan Cobit 5 Diaul Munir; Eva Zuraidah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 2 (2023): Oktober 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i2.1086

Abstract

The existence of information technology is able to support organizations in providing accurate, relevant, fast information. By harmonizing organizational goals, organizational information systems/information technology can speed up the process of achieving organizational goals, but of course supervision and maintenance are needed so that the organization's IS/IT runs well. Information technology audit is a form of operational audit, but information technology audit whose main objective is to improve IT governance, operational audit of information resource management, effectiveness, efficiency, economics of the information system functional unit. Based on the identification of the problems that have been described, this research will discuss the calculation of the capability level in the fingerprint attendance application in the Honda Pandawa Lima Sejati work environment. :DSS 01(manage operations ), DSS03 (manage problem) The results of research on auditing information systems for fingerprint attendance applications using the COBIT 5 domain DSS 01 and DSS 03 framework, it can be concluded that auditing information systems Fingerprint at Pandawa Lima Dealers Using COBIT 5 has almost reached the expected target level, the results of data processing of the distribution of questionnaires into data obtained and the rating to level F has fulfilled, the scale of rounding off the capability model condition index is at level 4 of the company
Searching and Comparing Isim Ma’rifat with Diacritic Removal in the Quran and Sahih Muslim Hadiths Ryan Fahreza Maliki; Eko Darwiyanto; Moch. Arif Bijaksana
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.1090

Abstract

This research aims to address the scarcity of comprehensive websites providing detailed lists of Isim Ma’rifat in the Quran and Sahih Muslim Hadith. The absence of a comprehensive resource hinders the ability to study and compare Isim Ma’rifat between these significant Islamic texts. To overcome this issue, the study develops a natural language processing approach utilizing an integrated Java tokenizer program with a MySQL database containing the Sahih Muslim Hadith and Quranic texts. The program identifies the occurrence of the alif lam prefix, followed by diacritic removal to facilitate accurate verse comparison between the two texts. The research focuses on identifying alif lam prefixed Isim Ma’rifat exclusively present in the Quran, exclusive to Sahih Muslim Hadith, and similarities between them. The analysis yields a comprehensive understanding of the distinctions and similarities of alif lam prefixed Isim Ma’rifat between the Quran and Sahih Muslim. These findings provide valuable input for the Al-Quran project, contributing to the development of comprehensive and accessible resources for Islamic studies. It is expected that this research will enhance the understanding of Isim Ma’rifat in the religious and linguistic context, offering a significant contribution to the field of natural language processing especially in the Arabic language.
Perancangan UI/UX Fitur Customer Relationship Management (CRM) Pada Aplikasi ABC Reload Menggunakan Metode Design Thinking Herman Kurniawan Gulo; Irsan Jaelani; Mochzen Gito Resmi
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.1096

Abstract

The ABC Reload app is a platform that connects customers with pulse recharge and bill payment services quickly and efficiently. In an era where customer interaction becomes successful, it is important for ABC Reload to strengthen relationships with customers through the implementation of Customer Relationship Management features (CRM). The design of the UI/UX user interface for the Customer Relationship Management (CRM) feature in the ABC Reload application has been done using the Design Thinking method. The study involved testing the feature with 30 respondents using the System Usability Scale method. (SUS). The design process of UI/UX features CRM on the ABC Reload application follows five main stages in the Design Thinking method, namely Empathize, Define, Ideate, Prototype and Test. Design Thinking methods are used to understand in depth the needs and preferences of users. Testing is done after UI/IX design is completed. The test results showed that the average value of the System Usability Scale (SUS) is 80,666, indicating that the design of UI/UX features CRM on the ABC Reload application received a positive response from users. It describes that the Design Thinking method applied in UI/UX design has succeeded in creating a more intuitive and user-satisfactory interface. Test results show that the Design Thinking method is able to meet the needs and wishes of the user well. The application of this method allows ABC Reload applications, especially for micro, small and medium-sized enterprises (MSMEs), to be more effective in managing customer relationships. Thus, the app can attract more customers and build a higher customer loyalty.
Analisis Penerimaan E-learning Madrasah Menggunakan Metode Technology Acceptance Model (TAM) Hellen Agustina
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.1097

Abstract

Along with the development of digital-based technology and the Covid-19 pandemic which required the school teaching and learning process to be carried out boldly, the Ministry of Religion of the Republic of Indonesia issued a Learning Management System (LMS) product called E-Learning Madrasah which was then applied to madrasah schools. Utilization of E-Learning Madrasah which is then used as digital-based learning (e-learning) at MAN 2 Tulungagung. The use of E-learning Madrasah to assist the teaching and learning process is both challenging and attractive, but in use of its use, there are several obstacles including difficulties for users to understand the features, lack of socialization of use, and ultimately impact on confusion in the operation of E-learning Madrasah. The purpose of this study is to carry out a factor analysis of the use of E-Learning Madrasah at MAN 2 Tulungagung with a quantitative approach, while the measurement model uses the Technology Acceptance Model (TAM) which involves perceived ease of use, perceived usefulness, attitude toward use, behavioral intention to use. The population in this study were students of class XI and XII MAN 2 Tulungagung, totaling 260 students, then processing the data using SmartPLS with the SEM-PLS analysis method. The sampling technique used in this research is probability sampling with proportional stratified random sampling. After conducting thorough data analysis, the research found that the variable's perceived ease of use and perceived usefulness are factors that must be strengthened in their use.
Implementasi Algoritma Naive Bayes dan Algoritma C4.5 dalam Klasifikasi Kelayakan Bantuan UMKM Aldy Novriandy; Winarsih
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.1099

Abstract

Indonesia's economic development has slowed down due to rising inflation. Entrepreneurs often face several problems in starting an entrepreneurial activity, including: capital, licensing, accounting guidelines, promotion, goods, pricing, human resources, advertising and other activities that often hinder the business process. Financial Management for MSME Empowerment is one of the business processes run by the Ministry of Finance in improving the performance of MSMEs through the provision of business capital. But in practice, there are obstacles in the process of testing the feasibility classification of the assistance activities carried out, because it still uses inefficient manual methods. In order for the testing to be more effective and practical, integrated website-based software is needed. To achieve this, this research was conducted with the aim of producing information related to the eligibility status of MSMEs in all regions of Indonesia that are eligible or not eligible to receive financial assistance from the government. In order for the MSME eligibility status information obtained to be useful for regional offices throughout Indonesia, the algorithms used in this research are the Naive Bayes algorithm and the C4.5 algorithm. The results showed that both algorithms can be applied well in determining the eligibility of MSME assistance. The accuracy of the C4.5 algorithm is 90% while the accuracy of the Naive Bayes method is 70%. The C4.5 algorithm performs slightly better than Naive Bayes in this classification setting. The accuracy findings in this study can be compared to previous research already conducted using the same algorithm or with similar data sets. This helps determine if this research methodology results in a higher accuracy rate than previous studies
Analisis Sentimen Terhadap Presidensi G20 2022 pada Media Sosial Twitter Menggunakan Metode Naïve Bayes I Gusti Agung Indrawan; Dewa Ayu Indah Cahya Dewi; Ida Ayu Putu Ananda Wisdantini
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.1104

Abstract

Twitter is one of the social media as a suitable forum to express opinions from the community today. Many people express their opinions through posts on social media Twitter on issues that are trending topics. One of the trending topics in 2022 is the implementation of the G20 presidency held in Bali, Indonesia. This issue, can generate positive or negative opinions from the community. In the research, a sentiment analysis will be carried out on the implementation of G20 presidency activities in 2022 using Python Google Colab, RapidMiner Studio, and Orange Data Mining. In the initial data collection, there are 24,840 data that will go through the stages of text pre-processing, labeling, sharing, and data classification using the Naïve Bayes classification method. So that it obtained the results of the classification of positive sentiment 1,600 data (72.37%) and negative sentiment 611 data (27.63%). Based on the results of the sentiment classification, it can be concluded that the public supports the implementation of G20 activities in 2022 in Bali, Indonesia, seen from positive sentiment more than negative sentiment. The Naïve Bayes classification has a fairly good performance in classifying the topics studied, where an accuracy value of 88.01% is obtained.
Detection of Isim in Al-Qur'anic Verses using the Isim Marking Method and Creating Hyperlinks to Support the Quranpedia Website Project Muhamad Jibril; Eko Darwiyanto; Moch Arif Bijaksana
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.1106

Abstract

This research aims to detect isim words containing "???" (Alif Lam) in the verses of the Al-Qur'an using the isim marking method and creating hyperlinks to support the Quranpedia website project. The research follows the Agile methodology in project development. The findings reveal that approximately 12.97% of words in the Al-Qur'an contain "???" (Alif Lam). This information provides valuable insights into the frequency and distribution of isim words in the Al-Qur'an and reinforces support for the Quranpedia project.
Penerapan Algoritma K-Means Clustering Untuk Pengelompokan Data Pasien Rehabilitasi Narkoba Ega Yolanda; Suhardi
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.1107

Abstract

Drug abuse’s a serious problem leading to addiction and harmful effects. Rehabilitation aims to save drug addicts and help them lead a normal, physically, and mentally healthy life while improving skills and social relationships. The North Sumatra Province National Narcotics Agency’s responsible for drug prevention, eradication, and rehabilitation. There’re different rehabilitation programs for adolescents and adults, with a "parenting" program applied for adolescents. However, the manual and inefficient process of determining programs poses challenges. This research utilizes data mining with the K-Means clustering algorithm to efficiently categorize drug rehabilitation patient data. The clustering results in three patient clusters based on their characteristics, providing essential information for North Sumatra Province National Narcotics Agency to tailor rehabilitation programs to each group's needs. Through the data clustering process, drug user patterns can be identified based on their shared attributes. Consequently, The North Sumatra Province National Narcotics Agency can determine more effective and suitable programs for each cluster. The findings show that the parenting program is appropriate for Cluster two. The study concludes that using the K-Means clustering algorithm with Python and Jupyter Notebook tools yields optimal clustering results. This research serves as a foundation for application development, further investigations, and comparisons with other clustering algorithms in drug rehabilitation patient data grouping.
Sentiment Analysis of User Reviews of Mutual Fund Investment Applications on Google Playstore using Long Short Term Memory (LSTM) Algorithm Nurlaela; Teguh Iman Hermanto; Dede Irmayanti
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.1109

Abstract

Mutual fund investment is increasing, as evidenced by the increasing number of mutual fund application users on the Playstore platform in Indonesia. The Financial Services Authority (OJK) reported that the number of mutual funds in Indonesia until August 2022 reached 2,193 units. In this research, the data collection used is the data scrapping method on the Google Playstore website. The result of the scrapping data is an excel-formatted document of 3000 data which is then stored and processed using the Long Short Term Memory (LSTM) model. In order to facilitate the modeling stage later, the sentiment review data must go through a text preprocessing process. To improve the performance and performance of LSTM modeling more optimally, then in this study a choice of hyperparameters was made. The hyperparameters tested are Epoch, Batch Size and Layer LSTM. The highest accuracy value on the Ajaib dataset is 99.3% which is located at epoch 32 and batch size 50, the highest accuracy value on the Bareksa dataset is 95.1% which is located at epoch 32 and batch size 50, and the highest accuracy value on the Bibit dataset is 94.9% which is located at epoch and batch size 50. So that the highest accuracy value among the three datasets is obtained by the Ajaib dataset where the accuracy reaches 99.3%. From the test results of the three parameters, it proves that there is an increase in accuracy results that is good enough to reach the highest accuracy value of 0.9933.

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