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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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Klasifikasi Sentimen SVM Dengan Dataset yang Kecil Pada Kasus Kaesang Sebagai Ketua Umum PSI El Saputra, Yoga; Agustian, Surya; Yusra, Yusra; Ramadhani, Siti
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1944

Abstract

Social media has become the main platform for the public to express views and opinions on various events, including the appointment of Kaesang Pangarep as General Chair of the Indonesian Solidarity Party (PSI). This research aims to classify public sentiment towards the appointment using the Support Vector Machine (SVM) method with the Term Frequency-Inverse Document Frequency (TF-IDF) approach. Data was collected from Twitter using the keyword "Kaesang PSI" as well as external data on topics related to Covid-19. In the kaeasang data, 300 data were taken with each label (positive, neutral, negative) to get 100 tweets and added external data of 900 data with each label (positive, neutral, negative) to get 300 tweets. After the text preprocessing process which includes case folding, stopword removal, and stemming. The model was tested using a confusion matrix to evaluate performance based on accuracy, precision, recall and F1 Score metrics. The results show that the SVM model with TF-IDF has an F1 Score of 0.53, accuracy of 0.62, precision of 0.52, and recall of 0.57. Adding external data related to Covid-19 to the TF-IDF feature has been proven to significantly improve model performance. In conclusion, the SVM method with TF-IDF is effective in analyzing sentiment on social media even with small datasets.
Sentiment and Toxicity Score Evaluation of DJI Avata Product Reviews Using Cross-Industry Standard Process for Data Mining Singgalen, Yerik Afrianto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1946

Abstract

This research employs the CRISP-DM framework to analyze consumer sentiment and preferences regarding DJI Avata drone products, aiming to provide data-driven strategic recommendations for marketing and product development. By systematically exploring business objectives, preparing and cleaning data, and modeling sentiment, the study reveals high consumer engagement and predominantly positive sentiment (51.91% positive, 31.16% neutral, 16.93% negative) towards the DJI Avata. The Support Vector Machine (SVM) algorithm demonstrated superior performance in sentiment classification, achieving an accuracy of 74.69%, with an AUC of 0.839, precision of 77.57%, recall of 69.68%, and F-measure of 73.23%. A comparative analysis between the VADER and TextBlob models, showing a moderate agreement (Cohen’s kappa statistic = 0.413) on 64.84% of the posts, highlighted the value of using multiple sentiment analysis tools. Furthermore, toxicity scores calculated via the Perspective API identified critical areas for improvement in user engagement. Subsequently, the toxicity results reveal the following scores: Toxicity with an average of 0.09461 and a peak of 0.90451, Severe Toxicity with an average of 0.00817 and a peak of 0.45895, Identity Attack with an average of 0.01139 and a peak of 0.58743, Insult with an average of 0.04543 and a peak of 0.70658, Profanity with an average of 0.06133 and a peak of 0.89080, and Threat with an average of 0.02063 and a peak of 0.69437. These detailed metrics provide a comprehensive understanding of the dataset's different dimensions and intensities of negative sentiments. The significant variation between average and peak values indicates the presence of highly negative interactions, which necessitates targeted intervention. Consequently, these findings inform the development of specific strategies to mitigate toxicity and enhance the overall user experience in digital communities. These insights informed strategic recommendations to enhance digital marketing efforts and product features, underscoring the CRISP-DM framework's efficacy in guiding comprehensive consumer sentiment analysis and fostering informed decision-making in the aerial photography and videography market.
Understanding Digital Engagement through Sentiment Analysis of Tourism Destination through Travel Vlog Reviews Singgalen, Yerik Afrianto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1947

Abstract

This research employs the CRISP-DM framework to analyze digital engagement through travel vlog content, explicitly focusing on vlogs about Gili Trawangan. The study systematically follows the CRISP-DM phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Utilizing the VADER sentiment analysis model and the SVM algorithm with SMOTE, the research achieves a high level of accuracy in sentiment classification, with the SVM model demonstrating an accuracy of 88.57% +/- 5.11% and a precision of 90.95% +/- 5.09%. Analysis of 442 cleaned and labeled data points reveals a strong dominance of positive sentiments, with 62.61% in the first video and 84.25% in the second video. These findings underscore the effectiveness of travel vlogs in engaging viewers and generating positive interactions as powerful tools for tourism marketing. The study concludes that the CRISP-DM framework is highly effective in facilitating comprehensive sentiment analysis and enhancing strategic tourism marketing initiatives.
Analisis Quality of Service (QoS) Jaringan Internet untuk Optimalisasi Bandwith Imam Ghozali, Muhammad; Alif Catur Murti; Syafiul Muzid
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1948

Abstract

The rapid growth in internet use in recent years has placed significant demands on the quality of network services. Technological developments and increasingly complex communication needs make it important to improve the Quality of Service (QoS) of internet networks. Optimal Quality of Service is critical to supporting critical applications such as video conferencing, streaming, and other real-time applications. Obstacles such as high latency, low Throughput, and lack of prioritization in traffic management can hinder the user experience and reduce the effectiveness of the service. Carrying out QoS optimization not only ensures that critical services get the right priority, but can also increase the overall efficiency of using network resources. The involvement of this prioritization scheme in the network infrastructure provides a holistic solution, combining a deep understanding of latency, Throughput and priority requirements. All of this is done in an effort to optimize QoS so that users can get a good experience in using internet access.
Sistem Pendukung Keputusan Dalam Rekomendasi Kelayakan Nasabah Penerima Kredit Menerapkan Metode Multi Object Optimization on the Basis of Ratio Analysis (MOORA) Aprilia Cahyani, Regyn; Lingga Wijaya, Harma Oktavia; Hakim, Lukman
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1949

Abstract

The process of applying for credit (loan funds) by customers is one of the many forms of service at the bank. To approve a credit application, the bank, especially the credit manager, must carry out a complex assessment in accordance with the standard requirements that apply in the bank, this is because to minimize the risk of bad credit because the customer cannot make installment payments in the future. Due to the complexity of considerations in determining the eligibility of customers applying for credit, limited employees (labor) and also the assessment process that is still carried out manually so that it takes a long time, so to overcome these problems, a system is needed that can provide recommendations for customer decisions that are worthy of acceptance in applying for credit.  By using one of the methods in the decision support system, it is hoped that the credit application process can run faster. One of the methods in SPK is the Multi Object Optimization on the Basis of Ratio Analysis (MOORA) Method. The criteria used in this assessment process include collateral, income, completeness of files, financial statements and mandatory net data from loans. Based on the results of the calculation according to the predetermined criteria, the highest score is obtained on behalf of the name with a value of 0.4591 0.59 and the lowest is held by Rahma with a value of 0.2172
Understanding Tourism Destination through Music: Digital Engagement Discourse Based on Sentiment Analysis Approach Singgalen, Yerik Afrianto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1950

Abstract

This research investigates the effectiveness of music-video content as a tool for tourism destination marketing, employing the CRISP-DM framework to approach data collection, analysis, and interpretation systematically. Focusing on the music video "Welcome to Sumba Island" by Marapu Reggae Official, the study analyzes public sentiment and toxicity scores to gauge audience engagement. The findings reveal a predominance of positive sentiments and minimal toxicity, with scores such as 0.02117 for general toxicity and 0.00189 for severe toxicity, indicating a respectful and appreciative audience. The Decision Tree (DT) algorithm, enhanced by the SMOTE operator, demonstrated superior performance in sentiment classification, achieving an accuracy of 95.50% and an AUC of 0.979. While the study's focus on a single music genre and location limits generalizability, it highlights the potential of music videos in tourism marketing. Future research should expand to diverse music genres and destinations and integrate mixed-method approaches for deeper insights. The CRISP-DM framework's effectiveness in this study underscores its value in guiding sentiment analysis and developing impactful tourism marketing strategies
Sistem Pendukung Keputusan Menentukan Sales Terbaik Menerapkan Metode Simple Additive Weighting Rasni Alex; Muh. Jamil
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 5 No. 1 (2024): Agustus 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v5i1.1951

Abstract

In this research, the author uses the SAW (Simple Additive Weighting) Method to determine the best salesperson at company. The SAW method is considered appropriate because it performs a weighted sum of the performance ratings for each alternative on all attributes. This research involves structured steps, starting with determining criteria, alternatives and weights that are relevant to the company context. The next process involves matrix preparation, normalization, and preference calculation. First of all, significant criteria for assessing sales performance have been determined. The sales alternatives to be evaluated have also been identified, and the weight given to each criterion is according to its importance in the company context. Then, a matrix containing sales performance data is created for the next calculation process. Each value in the matrix is normalized so that it can be compared fairly. After the normalization process is complete, the next step is to calculate preferences for each sales alternative. This involves multiplying each normalized value by the appropriate weight, then adding them to get a total preference value for each alternative. From these results, the best alternative is determined through a ranking process. The research results show that the 6th alternative, represented by Rahman Rianto, has the highest score with 0.879, making it the best seller. These recommendations are based on detailed analysis using the SAW Method, which provides valuable insight for company management in making decisions regarding the assessment and development of their sales performance. Thus, this research not only provides an understanding of the best sales performance, but also provides a strong foundation for sustainable decision making in the context of this company.
Penerapan Metode Single Moving Average Untuk Peramalan Penjualan Potel Ketela Wahyuni, Tri; Primadewi, Ardhin; Ully Artha, Emilya
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1953

Abstract

The Sajen Chips home industry is one of the MSMEs providing various processed chips made from cassava in the Trenten Village area. So far, it has been difficult to predict future product sales. Forecasting sales of cassava potel chips in the Kripik Sajen home industry is needed to make decisions about supplying cassava stock so that it can reduce stock excesses and shortages that often occur. This research uses the Single Moving Average (SMA) method to forecast cassava chips sales in the Kripik Sajen home industry. This research uses a sample of sales reports in October 2022 - October 2023 with movement values ??of 1, 2, 3, 4, 5, 6, 7, and 8 which will be used as calculation data for the Single Moving Average (SMA) method. Calculation of error from forecasting results uses the Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE) methods. So the final results can be obtained after calculating SMA forecasting and calculating MAD and MAPE errors. This research aims to determine the prediction of sales of cassava products by using the movement period and the SMA method. The forecasting results that have been carried out have good accuracy (small error rate) obtained in period 7, namely 108.57 kg of cassava potel sales in November 2023, which have a MAD accuracy of 8.69% and MAPE of 7.98%. These results show that the 7 is the best sales prediction for the Sajen Chips home industry.
Penerapan Metode Backpropagation Neural Network untuk Klasifikasi Penyakit Stroke Azhima, Mohd; Afrianty, Iis; Budianita, Elvia; Gusti, Siska Kurnia
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1956

Abstract

Stroke is a non-communicable disease that can occur suddenly due to local or global disruption of brain function. The early symptoms of stroke are often difficult to recognize, causing many sufferers not to realize or feel the signs, so the death rate is quite high. This research aims to determine the ability of the Backpropagation Neural Network (BPNN) method in classifying stroke. The dataset used consists of 4891 medical records with stroke and non-stroke classes which include ten relevant variables (gender, age, hypertension, history of heart disease, BMI, blood sugar levels, and so on). This research runs three scenarios with the BPNN architecture model [19:25:1], [19:29:1], and [19:35:1] using a certain combination of variables, namely the comparison of training and testing data (90:10, 80 :20, 70:30), and learning rate 0.1; 0.01; 0.001. Test results with the highest average accuracy level of 96.14% were achieved with an architectural model of [19:29:1], a learning rate of 0.001, and a training and testing data distribution of 80:20. Based on testing, it can be concluded that BPNN is considered capable of classifying stroke
Perancangan dan Implementasi UI/UX Website Edukasi Kesehatan Balita Menggunakan Metode Design Thinking Mufadhal Faraz Addhifa; Nur Adi, Taufik; Lailatuth Thohiroh, Elvira
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 5 No. 1 (2024): Agustus 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v5i1.1961

Abstract

This research examines the design and implementation of user interface (UI) and user experience (UX) on a toddler health education website using a design thinking approach. The main problem studied is the low accessibility and interactivity of toddler health information available online, which leads to a lack of parental understanding of the nutritional needs of toddlers. This research aims to design an intuitive UI and satisfying UX to increase parents' participation and understanding of toddler health information. The research method consists of three main stages: problem identification, design, and implementation, which include data collection through literature review, online survey, and in-depth interviews. The design process followed the design thinking methodology with empirical steps: empathize, define, ideate, prototype, and test. Data obtained from surveys and interviews were used to inform the creation of an initial prototype, which was then tested to obtain user feedback. Evaluation was conducted using usability testing and System Usability Scale (SUS) methods, resulting in an average score of 83.5, indicating an excellent level of user acceptability of the developed design. The findings of this research indicate that the simplified, easy-to-use, and interactive UI/UX design successfully addresses the challenges of accessing under-five health information. The resulting website, known as "Pelita", provides valid and reliable health information content, as well as additional features such as nutrition guidance, health service locations, and consultation services. This research not only resulted in an innovative and relevant design, but also increased parents' understanding and active participation in maintaining the health of their toddlers.

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