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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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Pengembangan Gim Simulasi Jalur Evakuasi Bencana Kebakaran di Kampus Menggunakan Metode ADDIE Julius Bata; Laura Imanuelle Defira
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1459

Abstract

Fire disasters frequently occur, resulting in both material and human losses. One of the places at risk of a fire disaster is the campus building. The campus is the center for academic activities involving faculty, students, staff, and visitors. This situation makes the campus a densely populated area susceptible to human casualties in a fire. In such emergencies, knowledge of evacuation routes is crucial for human safety. However, many academic members, especially students, need more information about evacuation routes. This research aims to develop a simulation game for socializing evacuation routes within the campus III building of Universitas Katolik Indonesia Atma Jaya BSD. We employ The ADDIE (Analysis-Design-Development-Implement-Evaluation) method to develop the game. The analysis stage is carried out by analyzing information about evacuation routes. Based on the results of the analysis, the design stage was carried out to design the game flow and quest in the game. After that, development, which consists of asset and game development, is carried out. The game assets, including a three-dimensional model of the building and attributes, are created using Blender. These assets are then integrated with the game logic using the Unity game engine. Evaluation is conducted by safety experts at Unika Atma Jaya and through black-box testing. The black-box testing results indicate that all game functions perform well. Experts opine that the game application can serve as a medium for socializing evacuation routes. Future research will focus on user testing by students.
Penerapan Metode K-Means Clustering Untuk Seleksi Atlet Taekwondo Porprov Maulina Tria Audina Gultom; Raissa Amanda Putri
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1462

Abstract

With the increase in the number of data on taekwondo athletes in North Sumatra Koni, of course the data will be different. In Koni North Sumatra, the selection process for taekwondo athletes still uses Microsoft Excel. The selection process using Microsoft Excel is still not appropriate because of the risk of errors in data input and it takes a long time to compare previous data with the resulting data. The purpose of writing this final assignment is to apply the K-Means Clustering method for selection data for taekwondo athletes who took part in the Porprov event into several clusters. Therefore, the author is interested in taking the topic of applying the K-Means Clustering method for the selection of Porprov taekwondo athletes at Koni North Sumatra. Based on the Elbow Method, it can be seen that the optimal number of clusters for the K-Means method is 3 Clusters. Cluster 0 feasible category with the least number of athletes totaling 213 athletes. Cluster 1 category is not feasible which amounted to 57 athletes. Cluster 2 category is very feasible with the highest number of athletes totaling 216 athletes.  This is because the number of clusters is 3 which consists of not feasible, feasible and very feasible. In accordance with the results of this research, namely by applying the K-Means Clustering method for Selection of Provincial Taekwondo Athletes in Koni North Sumatra, it was successfully implemented. The conclusion that can be drawn from this research is that using the K-Means Clustering method for selecting provincial taekwondo athletes succeeded in producing three groups (clusters) based on the characteristics contained in the data. The results of this research can also be used as a basis for developing applications as well as various research carried out in the future by making comparisons in the use of the K-Means Clustering method in an effort to group athlete data contained in KONI SUMUT
Analisis User Experience Aplikasi Disney+ Hotstar dengan Menggunakan Metode User Experience Questionnaire (UEQ) Danar Feriano; Nabila Rizky Oktadini; Allsela Meiriza; Putri Eka Sevtiyuni; Pacu Putra
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1470

Abstract

With the advancement of the times, people have started using apps to fulfill their daily needs, such as reading news, shopping, and watching movies. Disney+ hotstar is a video streaming platform that provides various types of movies. There are 107 people who have used the disney+ hotstar application throughout Indonesia as the subject of this research. The problem identified is why users prefer Netflix to watch videos compared to using the disney+ hotstar app. The purpose of the study was to analyze the user experience while using the disney+ hotstar app using the UEQ method and also to provide recommendations on what can be improved to enhance the user experience. After that, the UEQ tool was used to analyze the information that had been collected. The results show that the attractiveness aspect has a value of 1.72 which is a good value, perspicuity has a value of 1.67, which is an above average value, efficiency has a value of 1.49, which is an above average value; dependability has a value of 1.34, which is an above average value, stimulation has a value of 1.43, which is a good value and novelty has a value of 1.05, which is an above average value.
Analisis Sentimen Tanggapan Masyarakat Terhadap Kenaikan Biaya Haji Tahun 2023 Menggunakan Metode K- Nearest Neighbor (KNN) Hafsyah; Elin Haerani; Novriyanto; Fadhilah Syafria
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1471

Abstract

The Indonesian government implemented a policy of increasing the cost of Hajj in 2023, but the policy has attracted many positive and negative comments among the public. Public comments are taken from the social media network Twitter, because it contains a lot of information so that it attracts the interest of most people. With the increase in Hajj costs in 2023, it is necessary to conduct sentiment analysis. This study uses  the K-Neearest Neighbor method  because it is easy to apply and the data used are divided into two classes, positive and negative. The results of research on the application of  the K-Nearest Neighbor method in  sentiment analysis of the increase in Hajj costs in 2023 using 3,000 data taken from Twitter comments. The tweet data  used, there were 1866 positive comments and 415 negative comments and the total net data of 2281, judging from the amount of positive data compared to negative  data, obtained an accuracy value of 81.17% in 70:30 data sharing, 79.87% in 80:20 data sharing, 77.73% in 90:10 data sharing. Meanwhile, the highest accuracy value was 81.17% with  82.48% precision, 97.67% recall, F1- Score 89.43%.  In this study, there were more positive responses, this proves that the increase in Hajj costs in 2023 using  the K-Nearest Neighbor (KNN)  method can be accepted by the community
Pengukuran Tingkat Layanan Helpdesk Menggunakan COBIT 5 Febby Kurniawan; Novriyanto; Elin Haerani; Lola Oktavia
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1474

Abstract

The Riau Provincial Information and Statistics Communication Service is a government agency tasked with formulating policies, conducting evaluations and reporting in the field of information and communication technology in various sectors of society. The Riau Provincial Information and Statistics Communication Agency has one of the services, namely a helpdesk to assist in handling problems related to the use of information technology. The helpdesk is one of the most important parts in the Riau Provincial Information and Statistics Communication Service because it is a liaison for each Regional Apparatus Organization (OPD), but the helpdesk at the Riau Provincial Information and Statistics Communication Service (Diskominfotik) does not yet have a benchmark that can be used to evaluate the performance of the helpdesk system. The purpose of this study is to determine the level or level of helpdesk services in optimizing information technology using the COBIT 5 framework and focusing on DSS03 Domain. This research was conducted by interviewing 8 respondents who were involved in the helpdesk and had 27 questions on the DSS03 domain. This research obtained the results of measuring the level of helpdesk service capability in Diskominfotik Riau Province  is at level 4, namely Predictable  Process where diskominfotik has run IT processes in accordance with established SOPs but needs to make continuous improvements in order to reach the target level to be achieved, which is at level 5 Optimizing Process
MobileNet untuk Identifikasi Skala Kerapatan dan Transparansi Tajuk Pohon Daun Lebar Fanirizki Sofiyana; Rico Andrian; Rahmat Safe'i
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1476

Abstract

Forest health is an essential aspect of maintaining global environmental balance. One method for measuring forest health is Forest Health Monitoring (FHM), which includes measuring crown condition (crown density and foliage transparency). The measurement of crown density and foliage transparency is currently conducted by forest health experts by comparing the intensity of sunlight under the trees with values on a scale card (magic card) and then recording it. This is less effective because it relies on direct observation and can only be done by experts.Deep learning technology, especially Convolutional Neural Networks (CNN) such as MobileNet, can be used to make these measurements easier. This research aims to identify the scale of crown density and foliage transparency of broadleaf tree. This dataset used consist of four broadlieaf tree types: cacao (Theobroma cacao), durian (Durio zibethinus), rubber (Havea brasiliensis), and candlenut (Aleurites moluccana) with 5,000 images per tree type. The data preprocessing is carried out by data augmentation to prepare the dataset. The dataset is divided into three parts, 70% training data, 10% validation data, and 20% test data. Experimental results show that the MobileNet model can measure crown density and foliage transparency with accuracy during training and validation for Theobroma cacao (94.20%), Durio zibethinus (83.60%), Havea brasiliensis (97.80%), and Aleurites moluccana (99.20%). Accuracy in the testing process on Theobroma cacao (94.20%), Durio zibethinus (87.50%), Havea brasiliensis (97.90%), and Aleurites moluccana (98.70%). These results show that the MobileNet model is able to identify scales of crown density and foliage transparency using the Forest Health Monitoring (FHM) method for broadleaf trees with very good performance. Therefore, this research with MobileNet shows the potential for using deep learning technology in monitoring forest health more effectively and efficiently.These results show the potential for using deep learning technology in monitoring forest health more effectively and efficiently.
Implementasi Metode Waterfall Pada Sistem Informasi Pencarian Lowongan Kerja Berbasis Web Praja Sendi Wardanu; Joko Aryanto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1478

Abstract

In the world of work that continues to develop, access to job vacancy information has become a very important aspect for society. Rapid technological advances have presented new challenges in terms of access to job vacancy information. Many people experience difficulties in finding work, especially due to limited access and costs associated with print media such as newspapers, brochures and magazines which were previously the main source of employment information. This website aims to make it easier for job seekers to get access to various job vacancies online. To achieve this goal, the research uses quantitative research methodology, including literature studies to understand concepts and user needs, observations to observe current job search methods, interviews with potential job seekers to collect relevant data and questionnaires to obtain relevant data from applicants and applicants. public. Meanwhile, in creating the system, the System Development Life Cycle (SDLC) methodology with a waterfall model approach was used, and Unified Modeling Language (UML) was used as a tool to describe the resulting system. The reason for using the waterfall method for developing a website-based information system is to facilitate job seekers' access to job vacancy information. This approach provides a structured framework, enables planning from analysis to implementation, and emphasizes strong documentation to ensure a comprehensive understanding of user needs and an end result that meets expectations. The research results obtained showed that of the 25 respondents, the percentage level of acceptance by the public or applicants for the system being developed was the highest in the first statement, namely 40% agreed, the second was 36% neutral and the third was 40% agreed. Through this website-based information system, research concludes that the reduction in costs and time for people looking for work is very significant and effective. Positive impacts include the potential to reduce unemployment rates and increase inclusivity, provide wider job access opportunities, and create a better world of work
Pengembangan Persona Berbasis Survey Menggunakan Analisis Klaster Untuk Representasi Calon Tenaga Kerja Enjelina Tampubolon; Dedy Kurniawan; Pacu Putra; Rudi Sanjaya
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1480

Abstract

The phenomenon of difficulty finding work is one of the issues faced by the current generation, especially among young graduates. The Central Statistics Agency (BPS) released data regarding the number of unemployed in Indonesia in 2023, which reached 5.45%. This means that currently there are around seven million people who do not have permanent work. This condition is caused by a lack of readiness of prospective applicants in terms of skills, knowledge and information as well as high job competition. In this research, a survey was conducted on 200 respondents based on random sampling of active students and fresh graduates from various educational backgrounds. The survey data is used in developing personas to represent potential users using cluster analysis. Personas are a user-centered design approach in HCI that helps developers understand their motivations, needs, skills, and challenges. This approach is used when developers have limited knowledge about the individual behavior of target users. Thus, personas can be used to create basic user groups that represent broader needs and characteristics. Persona development also has the advantages of low development costs and fast and easy access. The final results of this research will present the development of two data-based personas from a total of eight clusters formed. Cluster one (n = 24) and cluster two (n = 84) were chosen as the author's guiding data in creating the main persona. The personas presented can be used in research and application development to increase awareness of end-user needs and demands
Evaluasi Proses Bisnis Pendaftaran Nikah Menggunakan Metode Business Process Improvement (BPI) di KUA Amanda Julia Dela Siska; Pacu Putra; Dinna Yunika Hardiyanti; Muhammad Ihsan Jambak
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1482

Abstract

The Indralaya District Religious Affairs Office is a government agency authorized to carry out some of the duties of the Ministry of Religious Affairs. Registration and recording of marriages is one of the duties of the Sub-district KUA. However, in carrying out its duties, there are several obstacles faced in the current flow of marriage registration, such as the length of the marriage registration process, and a complicated process due to the many documents that must be taken care of to various agencies. Therefore, it is necessary to conduct periodic evaluations to find potential problems that hinder the current business process and optimize the quality of services of the sub-district KUA. The current marriage registration flow and the recommended marriage registration flow will be modeled using a Business Process Model and Notation (BPMN) diagram. Then, each activity in the current marriage registration flow is evaluated using the Failure Mode and Effects Analysis (FMEA) approach. The results of the FMEA evaluation are used for business process improvement. Business process improvement is carried out using the Business Process Improvement (BPI) method. BPI is a method used to improve the quality of business processes to make them more effective and efficient without having to reconstruct ongoing business processes radically. After that, the design of business process recommendations will be proposed using tools from the third phase of BPI, namely streamlining. Furthermore, simulations will be carried out using Bizagi Modeler to test time, process validation, and resource analysis. The results obtained are an increase in process time from 28 days 2 hours 56 minutes 30 seconds to 10 days 9 hours 27 minutes 15 seconds or an increase of 62.80%.
Perbandingan Algoritma Naïve Bayes dan K-Nearest Neighbor Pada Imbalace Class Dataset Penyakit Diabetes Muhammad Rousydi Hunafa; Arief Hermawan
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1486

Abstract

Diabetes is a global health concern due to its significant impact on public health. Managing this disease is crucial to prevent serious complications. Technological advancements, particularly in machine learning models, have opened new avenues in diabetes identification. This study compares the performance of the Naive Bayes and K-Nearest Neighbor (KNN) classification algorithms on an imbalanced diabetes dataset. The primary aim is to evaluate these algorithms' performance in predicting diabetes while considering class imbalance. Classification methods were applied to previously collected datasets. The research findings demonstrate that Naive Bayes with the SMOTE technique exhibited the best performance with an accuracy of 71.66%, followed by Naive Bayes without SMOTE (76.03%), and KNN with SMOTE (80.47%). Although KNN without SMOTE showed the highest accuracy (83.02%), Naive Bayes with SMOTE showcased a better balance between accuracy, precision, and recall. The utilization of the SMOTE technique improved Naive Bayes' performance by enhancing precision and recall, indicating its capability to address class imbalance in the diabetes dataset. This study offers insights into selecting the best algorithms and effective techniques for handling class imbalance to predict diabetes on imbalanced datasets.

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