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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JISKa (Jurnal Informatika Sunan Kalijaga) Journal of Soft Computing Exploration Journal of Student Research Exploration Journal of Information System Exploration and Research
Pertiwi, Dwika Ananda Agustina
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Library & Information Science

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The Effect of Digitalization on Business Performance in the MSME Industry Context Umar, Fadhil; Septian, M. Rivaldi Ali; Pertiwi, Dwika Ananda Agustina
Journal of Information System Exploration and Research Vol. 2 No. 1 (2024): January 2024
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v2i1.199

Abstract

The current digital era is increasingly developing in the use of new technology that creates value for companies and offers benefits. Digitalization is useful for increasing competitive advantage to improve business performance. The purpose of this study is to find out whether digitalization affects business performance and to find out whether competitive advantage can mediate digitalization on business performance. The sample of this research is 115 SMEs in Semarang. data were analyzed using the SEM approach with the smartPLS tool. The results of the study show that the digitalization variable has an influence on business performance, furthermore, competitive advantage also has a positive and significant effect on business performance. The results of the indirect effect test also show that competitive advantage can mediate the relationship between digitalization and business performance. The better the implementation of digitalization, the higher the competitive advantage MSMEs, consequently leading to an increase the business performance.
Breast Cancer Diagnosis Utilizing Artificial Neural Network (ANN) Algorithm for Integrating Multi-Omics Data and Clinical Features Rofik, Rofik; Artiyani, Fani; Pertiwi, Dwika Ananda Agustina
Journal of Information System Exploration and Research Vol. 2 No. 2 (2024): July 2024
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v2i2.249

Abstract

Breast cancer is one of the most common diseases affecting women worldwide, with a significant impact on patient's health and quality of life. Despite advances in medical technology and research, breast cancer diagnosis remains a challenge due to its complexity involving various biological and clinical factors. Several previous studies have focused on detecting this disease with optimal accuracy, but the selection of appropriate algorithms and methods is key to achieving this goal. This study aims to improve the accuracy of breast cancer diagnosis by using the ANN algorithm and data balancing method, SMOTE. This research uses Multi-Omic data and Clinical Features obtained in general from Kaggle. The research process is carried out in several stages, namely Data Collection, Preprocessing, Oversampling, Modeling, and Evaluation. This research successfully obtained an increase in accuracy, which was able to achieve an accuracy of 99.30%.  This research shows that early detection of breast cancer with ANN algorithm and data balancing using SMOTE can improve accuracy performance in early detection of breast cancer. Given the use of data in this study is not too large, it is recommended for further research to use a larger dataset to validate the strength of the model that has been built on more varied data.
Sentiment based-emotion classification using bidirectional long short term-memory (Bi-LSTM) Utami, Putri; Ningsih, Maylinna Rahayu; Pertiwi, Dwika Ananda Agustina; Unjung, Jumanto
Journal of Soft Computing Exploration Vol. 5 No. 3 (2024): September 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i3.461

Abstract

Social media is now an important platform for sharing information, expressing opinions, and daily feelings or emotions. The expression of emotions such as anger, sadness, fear, happiness, disappointment, and so on social networks can be further analyzed either for business purposes or just analyzing the habits of a community or someone's posts.  However, analyzing manually will be a time-consuming process, and the use of conventional methods can affect the results of less accurate accuracy. This research aims to improve the accuracy of recognizing emotions in text by using the Bidirectional Long Short Term Memory (Bi-LSTM) method, which is a subset of RNNs that tend to be more stable during training and show better performance on various NLP and other processing tasks. The method used includes several stages, namely preprocessing, tokenization, sequence padding, and modeling. The results of this study show that the Bi-LSTM model is capable of predicting emotions in text with an accuracy of 94.45% because it excels in handling the temporal context and can avoid vanishing gradients.
Analysis of k-means clustering algorithm in advanced country clustering using rapid miner Prabaswara, Ireneus; Pertiwi, Dwika Ananda Agustina; Jumanto, Jumanto
Journal of Student Research Exploration Vol. 2 No. 2: July 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v2i2.337

Abstract

In the era of globalization, the understanding of developed countries is no longer limited to the level of per capita income alone. As part of the analysis of developed countries based on aspects of government revenue, income balance, national savings, and domestic output based on sales. This research aims to cluster and to find out how these economic indicators are interrelated and affect the status of a country as a developed country. The K-means algorithm is used to identify patterns of countries with similar economic characteristics. From the research conducted, there are 4 clusters generated based on the characteristics of developed countries.
Optimized Support Vector Machine with Particle Swarm Optimization to Improve the Accuracy Amazon Sentiment Analysis Classification Ningsih, Maylinna Rahayu; Unjung, Jumanto; Pertiwi, Dwika Ananda Agustina; Prasetiyo, Budi; Muslim, Much Aziz
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 1, February 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i1.1888

Abstract

Text mining is a valuable technique that empowers users to gain a deeper understanding of existing textual data, ultimately allowing them to make more informed decisions. One important application of text mining is in the field of sentiment analysis, which has gained significant traction among companies aiming to understand how customers perceive their products and services. In response to this growing need, various research efforts have been made to improve the accuracy of sentiment analysis classification models. The purpose of this article is to discuss a specific approach using the Support Vector Machine (SVM) algorithm, which is often used in machine learning for text classification tasks and then combined with the application of Particle Swarm Optimization (PSO), which optimizes the SVM model parameters to achieve the best classification results. This dynamic combination not only improves accuracy but also enhances the model's ability to efficiently handle large amounts of text data to achieve better results. The research findings highlight the effectiveness of this approach. The application of the SVM algorithm with PSO resulted in an outstanding accuracy performance of 94.92%. The substantial increase in accuracy compared to previous studies shows the promising potential of this methodology. This proves that the SVM algorithm model approach with Particle Swarm Optimization provides good performance.
Improved logistics service quality for goods quality delivery services of companies using analytical hierarchy process Riliandini, Popy; Dianti, Erika Noor; Hidayah, Sayidah Rohmatul; Pertiwi, Dwika Ananda Agustina
Journal of Soft Computing Exploration Vol. 2 No. 1 (2021): March 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i1.21

Abstract

Logistics plays a role in the smooth transaction between companies because it is a facilitator of buying and selling goods and services to fulfill the supply orders of consumer companies. This study aims to analyze how the impact of improved Logistic Service Quality (LSQ) for quality of goods delivery services by using LSQ dimensions from previous research. Sample data is obtained through the dissemination of questionnaires which are then processed quantitatively with convergent validity and reliability tests. Data processing with a sample count of 61 respondents. The results of this study show that there is the main dimension of logistic service quality in improving the quality of service, namely ordering condition, time, and information quality. Each comparison factor is tested for consistency using the Analytical Hierarchy Process (AHP), each of the main criteria has a consistency value of less than 0.1 so that the main criteria tested have a consistent comparison matrix and can be the basis of decision making for companies in choosing alternative criteria priorities.
Simulations of text encryption and decryption by applying vertical bit rotation algorithm Pertiwi, Dwika Ananda Agustina; Djuniadi, Djuniadi
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.44

Abstract

Cryptography is the study of hiding text and numbers in the form of codes. Vertical Bit Rotation (VBR) is one of the most widely implemented cryptographic algorithms as a one-way hash function that simplifies the encryption process with a high degree of difficulty in decryption. The purpose of this study is to apply VBR hash algorithm modeling to binary value characters with bit rotation keys 10, 11, 7, 3, 2, 7, 5, and 4. Thus, generating a passcode. The results of the encryption simulation show the code in the form of letters and characters, then the result of the decryption with the opposite rotation to the encryption process returns the value from ciphertext to plaintext based on ASCII characters. Cryptographic algorithms are applied to avoid cryptanalytic experiments in opening encryption codes.
Improvement business process model and notation on the drink distribution industries using six core element Khoirunnisa, Oktaria; Pertiwi, Dwika Ananda Agustina; Dianti, Erika Noor; Fattah, Ahmad Maulana Malik; Budiman, Kholiq
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.46

Abstract

The development of distribution and market segmentation has become the company's background in improving business processes. The purpose of this research is to analyze the business processes of beverage companies using Business Process Management (BPM) modeling and improvised based on six core element management. In the analysis process, it is found that there is no stock forecasting system in forecasting sales stock that must be fulfilled. The results of the study show that the Business Process Management model is improved with the addition of a stock forecasting system, so that business processes become more controlled with the presence of a product stock inventory forecasting system in the company.
Augmented reality development using multimedia development life cycle (MDLC) method in learning media Solehatin, Solehatin; Aslamiyah, Sulaibatul; Pertiwi, Dwika Ananda Agustina; Santosa, Kevin
Journal of Soft Computing Exploration Vol. 4 No. 1 (2023): March 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i1.118

Abstract

Practical classroom learning in the multimedia department requires props, where props range from damage. To address this need, learning media are made by applying Augmented Reality. Learning media presents actual images without holding and seeing the objects in real terms so that there is no damage to the props. This research was conducted to create learning media for students of SMK Negeri 1 Banyuwangi majoring in multimedia as an Android-based teaching aid. Stages of research using the development method in the form of Multimedia Model Life Cycle (MDLC). The concept stage analyzes and applies the Augmented Reality (AR) method, the design stage performs application planning according to the needs of learning media. The data collection stage conducted interviews with teachers and students while the stages of making learning media used Blender, Unity and Visual Studio software. At the trial stage of the application by making a guidebook, it was carried out for students at SMK Negeri 1 Banyuwangi. For the stages of distributing learning media using the Likert scale method through distributing questionnaires. The results of the application trials and questionnaire distribution, the responses of students about learning media, the results show the interpretation of respondents by combining a value of 72.22%, which means students accept this learning media. The results of this research can create learning media for multimedia majors that can reduce the risk of damage to props and provide cool and fun learning media.
Application of the KNN method to check soil compatibility using a microcontroller for android-based banyuwangi citrus fruit plants Solehatin, Solehatin; Hadiq, Hadiq; Pertiwi, Dwika Ananda Agustina
Journal of Soft Computing Exploration Vol. 4 No. 3 (2023): September 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i3.197

Abstract

The city of Banyuwangi needs a touch of information technology in the agricultural sector, namely in the process of planting orange fruit, because orange fruit planting is carried out continuously to meet export needs. Citrus fruit planting is sometimes carried out without paying attention to the existing soil nutrient content, this condition can result in less than optimal harvest results. The research was carried out by creating a soil nutrient detection application with the aim of providing information to farmers about the soil nutrient content including nitrogen, calcium, phosphorus, pH and moisture resistance before planting citrus fruit. From the results of trials conducted by researchers with farmers based on various types of soil used as trial data, the information shows a match of 89.6%. The results of the research produced an Android-based soil nutrient checking application that farmers can use to check soil nutrients when planting citrus fruit. In conducting the research, the researcher created an application by applying the KNN method and utilizing a microcontroller to input the data. By combining methods and tools, microcontrollers can assist the implementation process so as to provide information in the form of soil suitability for planting citrus fruit based on the nutrient content of the soil being examined. The contribution made from the research results is the application of a KNN method which is used to check soil nutrients so that it can maximize the results of the detection carried out. Meanwhile, another contribution is the use of a tool in the form of a microcontroller which is used to automatically input data which can be obtained using the Bluetooth service in the soil nutrient check application.
Co-Authors Ahmad, Kamilah Ali, Muazam Annegrat, Ahmed Mohamed Artiyani, Fani Aslamiyah, Sulaibatul Budi Prasetiyo, Budi Budiman, Kholiq Darmawan, Aditya Yoga Dianti, Erika Noor Djuniadi Djuniadi Dullah, Ahmad Ubai Efrilianda, Devi Ajeng Fattah, Ahmad Maulana Malik Hadiq, Hadiq Hidayah, Sayidah Rohmatul Jumanto Jumanto, Jumanto Jumanto Unjung Khan, Atta Ullah Khoirunnisa, Oktaria Lestari, Apri Dwi Much Aziz Muslim Muhammad Yusuf Muzayanah, Rini Ningsih, Maylinna Rahayu Prabaswara, Ireneus Putri Utami, Putri Riliandini, Popy Rofik Rofik, Rofik Salahudin, Shahrul Nizam Santosa, Kevin Septian, M. Rivaldi Ali Solehatin, Solehatin Syahra, Syahra Audiyani Fitra Umar, Fadhil