MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer最新文献

Intelligent System for Internet of Things-Based Building Fire Safety with Naive Bayes Algorithm 采用 Naive Bayes 算法的基于物联网的建筑消防安全智能系统

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-30 DOI: 10.30812/matrik.v23i1.3581

Ni Gusti Ayu Dasriani, Sirojul Hadi, Moch Syahrir

{"title":"Intelligent System for Internet of Things-Based Building Fire Safety with Naive Bayes Algorithm","authors":"Ni Gusti Ayu Dasriani, Sirojul Hadi, Moch Syahrir","doi":"10.30812/matrik.v23i1.3581","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3581","url":null,"abstract":"Population growth is increasing every year. Population growth causes an increase in population density in a country. The largest population density is in urban areas. Fires in a city with a high population density will potentially cause greater damage. Material and non-material losses due to fire can be caused by not functioning maximally early warning systems, especially fire detection. In addition, other factors, such as system errors in detecting fires, can potentially cause fires. This research aims to build an intelligent system that can minimize building fire detection errors to reduce user material losses. The intelligent system can classify fire potential into four classifications, namely ”very dangerous,” ”dangerous,” ”alert,” and ”safe.” The method used in this research is Research and Development (R&D) with artificial intelligence using the Na¨ıve Bayes method, which has been integrated with the Internet of Things (IoT). This research shows that the Na¨ıve Bayes algorithm can be used to classify fire potential, proven by the overall system testing accuracy of 93.33% with an error of 6.77%.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139201982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detecting Disaster Trending Topics on Indonesian Tweets Using BNgram 利用 BNgram 检测印尼推文中的灾难热门话题

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-30 DOI: 10.30812/matrik.v23i1.3308

Indra Indra, Nur Aliza

{"title":"Detecting Disaster Trending Topics on Indonesian Tweets Using BNgram","authors":"Indra Indra, Nur Aliza","doi":"10.30812/matrik.v23i1.3308","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3308","url":null,"abstract":"People on social media share information about natural disasters happening around them, such as the details about the situation and where the disasters are occurring. This information is valuable for understanding real-time events, but it can be challenging to use because social media posts often have an informal style with slang words. This research aimed to detect trending topics as a way to monitor and summarize disaster-related data originating from social media, especially Twitter, into valuable information. The research method used was BNgram. The selection of BNgram for detecting trending topics was based on its proven ability to recall topics well, as shown in previous research. Some stages in detection were data preprocessing, named entity recognition, calculation using DF-IDF, andhierarchical clustering. The resulting trending topics were compared with the topics obtained using the Document pivot method as the basic method. This research showed that BNgram performs better in detecting trending natural disaster-based topics compared to the Document pivot. Overall, BNgram had a higher topic recall score, and its keyword precision and keyword recall values were slightly better. In conclusion, recognizing the significance of social media in disaster-related information can increase disaster response strategies and situational awareness. Based on the comparison, BNgram was proven to be a more effective method for extracting important information from social media during natural disasters.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"1232 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139202915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementation of Port Knocking with Telegram Notifications to Protect Against Scanner Vulnerabilities 利用电报通知实施端口锁定，防范扫描仪漏洞

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-30 DOI: 10.30812/matrik.v23i1.3459

Husain Husain, I. P. Hariyadi, Kurniadin Abd. Latif, Galih Tri Aditya

{"title":"Implementation of Port Knocking with Telegram Notifications to Protect Against Scanner Vulnerabilities","authors":"Husain Husain, I. P. Hariyadi, Kurniadin Abd. Latif, Galih Tri Aditya","doi":"10.30812/matrik.v23i1.3459","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3459","url":null,"abstract":"The opening of the service port on the Mikrotik router provides an opening for hackers to enter the Mikrotik service to access the router illegally. This research aimed to close certain ports that are gaps for hackers and uses port knocking and telegram bots. The Telegram bot was used as a message notification to managers in real-time to provide information that occurs when the vulnerability scanning process is carried out to find and map weaknesses in the network system. Searching for weaknesses also includes looking for open router service ports such as ports 22, 23, 80, and 8291. This research used the Network Development Life Cycle method, which started from analysis design and prototype simulation to implementation. The research results after testing were able to secure local network service ports against vulnerability scanners on routers using the port knocking method, and testing attack schemes carried out from each scheme could run well on the router’s local network and obtain notifications via telegram bots in real time to administrators. This research contributes to administrators’ ability to secure networks so irresponsible people do not easily infiltrate them.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139200241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electronic Tourism Using Decision Support Systems to Optimize the Trips 利用决策支持系统优化旅行的电子旅游业

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-29 DOI: 10.30812/matrik.v23i1.3331

Dedi Setiadi, Y. Mukti

{"title":"Electronic Tourism Using Decision Support Systems to Optimize the Trips","authors":"Dedi Setiadi, Y. Mukti","doi":"10.30812/matrik.v23i1.3331","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3331","url":null,"abstract":"Pagar Alam is a tourist destination city in the province of South Sumatra, which has many very diverse tourist destinations. The problem is that there is still a lack of information about tourism that tourists can access. This research aimed to build electronic tourism to make it easier for tourists to get the best information and recommendations about tourism in the city of Pagar Alam, which can be accessed anytime and anywhere, as well as improve tourist experience in planning their tourist trips because this electronic tourism platform includes decision making support system, which helps tourists manage their tours according to their needs and abilities. The research method used was analysis by collecting data by observing tourist attractions, calculating predictions using the simple additive weighting method, and from the results of testing with several alternatives, it can be concluded that electronic tourism meets the criteria chosen by tourists after being carried out. The calculation produced the highest preference value for tourist attractions, namely Tugu Rimau, with a value of 13.25. The highest preference value for hotels is Villa Gunung Gare Pagar Alam, with a score of 8.91, and the highest preference score for eating places is Warung Ridwan, with a score of 13.25. The next stage was system design using data flow diagrams, and the final stage was implementation by building electronic tourism using the CodeIgniter framework.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139212857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Employee Presence and Payroll Information System Using Quick Response Code and Geolocation 使用快速反应代码和地理定位的员工在职和薪资信息系统

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-23 DOI: 10.30812/matrik.v23i1.3093

Ahmad Homaidi, Lukman Fakih Lidimilah, Jarot Dwi Prasetyo, Nur Azizah

{"title":"Employee Presence and Payroll Information System Using Quick Response Code and Geolocation","authors":"Ahmad Homaidi, Lukman Fakih Lidimilah, Jarot Dwi Prasetyo, Nur Azizah","doi":"10.30812/matrik.v23i1.3093","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3093","url":null,"abstract":"The presence in the institution still uses the conventional method of affixing a signature on the attendance sheet. Presences that have been carried out so far are felt to be less effective and efficient because sometimes attendance is filled towards the end of the month, which causes the validity of attendance data to be questioned. Even errors are often found in the recording, which causes the nominal to be inappropriate and must be revised. This research aimed to design an information system using the Quick Response Code to increase the effectiveness of employee attendance and payroll, supported by geolocation, to make it more efficient. The method used in this research was the waterfall method, using the stages of communication, planning, modeling, construction, and deployment. This research produced an information system that could make it easier for employees to attend, speed up determining employee salaries and filing financial disbursements, and increase employee presence and salary validity. The test results showed that 90% said they were satisfied with the performance of the system being built.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"27 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139244811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing Inventory with Frequent Pattern Growth Algorithm for Small and Medium Enterprises 利用频繁模式增长算法优化中小企业库存

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-23 DOI: 10.30812/matrik.v23i1.3363

Imam Riadi, Herman Herman, Fitriah Fitriah, S. Suprihatin

{"title":"Optimizing Inventory with Frequent Pattern Growth Algorithm for Small and Medium Enterprises","authors":"Imam Riadi, Herman Herman, Fitriah Fitriah, S. Suprihatin","doi":"10.30812/matrik.v23i1.3363","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3363","url":null,"abstract":"The success of a business heavily relies on its ability to compete and adapt to the ever-changing market dynamics, especially in the fiercely competitive retail sector. Amidst intensifying competition, retail business owners must strategically manage product placement and inventory to enhance customer service and meet consumer demand, considering the challenges of finding items. Poor inventory management often results in stock shortages or excess. To address this, adopting suitable inventory management techniques is crucial, including techniques from data mining, such as association rule mining. This research employed the FP-Growth algorithm to identify patterns in product placement and purchases, utilizing a dataset from clothing store sales. Analyzing 140 transactions revealed 24 association rules, comprising rules with 2-itemsets and frequently appearing 3-itemset rules. The highest support value in the final association rules with 2-itemsets was 10% with a confidence level of 56%, and the highest support value in the 3-itemsets was 67% with the same confidence level. Additionally, three rules had a confidence level of 100%. Thus, the association rules generated by the FP-Growth frequent itemset algorithm can serve as valuable decision support for sales of goods in small and medium-sized retail businesses.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"36 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139243066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of Distance Measurements Based on k-Numbers and Its Influence to Clustering 基于 k 数的距离测量及其对聚类的影响比较

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-20 DOI: 10.30812/matrik.v23i1.3078

Deny Jollyta, Prihandoko Prihandoko, Dadang Priyanto, Alyauma Hajjah, Yulvia Nora Marlim

{"title":"Comparison of Distance Measurements Based on k-Numbers and Its Influence to Clustering","authors":"Deny Jollyta, Prihandoko Prihandoko, Dadang Priyanto, Alyauma Hajjah, Yulvia Nora Marlim","doi":"10.30812/matrik.v23i1.3078","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3078","url":null,"abstract":"Heuristic data requires appropriate clustering methods to avoid casting doubt on the information generated by the grouping process. Determining an optimal cluster choice from the results of grouping is still challenging. This study aimed to analyze the four numerical measurement formulas in light of the data patterns from categorical that are now accessible to give users of heuristic data recommendations for how to derive knowledge or information from the best clusters. The method used was clustering with four measurements: Euclidean, Canberra, Manhattan, and Dynamic Time Warping and Elbow approach for optimizing. The Elbow with Sum Square Error (SSE) is employed to calculate the optimal cluster. The number of test clusters ranges from k = 2 to k = 10. Student data from social media was used in testing to help students achieve higher GPAs. 300 completed questionnaires that were circulated and used to collect the data. The result of this study showed that the Manhattan Distance is the best numerical measurement with the largest SSE of 45.359 and optimal clustering at k = 5. The optimal cluster Manhattan generated was made up of students with GPAs above 3.00 and websites/ vlogs used as learning tools by the mathematics and computer department. Each cluster’s ability to create information can be impacted by the proximity of qualities caused by variations in the number of clusters.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139256000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Single elimination tournament design using dynamic programming algorithm 使用动态编程算法设计单败淘汰赛

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-20 DOI: 10.30812/matrik.v23i1.3290

Yusri Ikhwani, As`ary Ramadhan, Muhammad Bahit, Taufik Hidayat Faesal

{"title":"Single elimination tournament design using dynamic programming algorithm","authors":"Yusri Ikhwani, As`ary Ramadhan, Muhammad Bahit, Taufik Hidayat Faesal","doi":"10.30812/matrik.v23i1.3290","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3290","url":null,"abstract":"Finding the best single-elimination tournament design is important in scientific inquiry because it can have major financial implications for event organizers and participants. This research aims to create an optimal single-elimination tournament design using binary tree modeling with dummy techniques. Dynamic programming algorithms have been used to compute optimal single-elimination designs to overcome this effectively. This research method uses various implementations of sub-optimal algorithms and then compares their performance in terms of runtime and optimality as a solution to measure the comparison of sub-algorithms. This research shows that the difference in relative costs produced by various sub-algorithms with the same input is quite low. This is expected because quotes are generated as integer values from a small interval 1, ≤ 9, whereas costs tend to reach much higher values. From the comparison of these sub-algorithms, the best results among the sub-optimal algorithms were obtained in the Sub Optimal algorithm 3. We present the experimental findings achieved using the Python implementation of the suggested algorithm, with a focus on the best single-elimination tournament design solution.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"4 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139256303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Application of Numerical Measure Variations in K-Means Clustering for Grouping Data 在 K-Means 聚类中应用数值度量变量对数据进行分组

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-20 DOI: 10.30812/matrik.v23i1.3269

Relita Buaton, Solikhun Solikhun

{"title":"The Application of Numerical Measure Variations in K-Means Clustering for Grouping Data","authors":"Relita Buaton, Solikhun Solikhun","doi":"10.30812/matrik.v23i1.3269","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3269","url":null,"abstract":"The K-Means Clustering algorithm is commonly used by researchers in grouping data. The main problem in this study was that it has yet to be discovered how optimal the grouping with variations in distance calculations is in K-Means Clustering. The purpose of this research was to compare distance calculation methods with K-Means such as Euclidean Distance, Canberra Distance, Chebychev Distance, Cosine Similarity, Dynamic TimeWarping Distance, Jaccard Similarity, and Manhattan Distance to find out how optimal the distance calculation is in the K-Means method. The best distancecalculation was determined from the smallest Davies Bouldin Index value. This research aimed to find optimal clusters using the K-Means Clustering algorithm with seven distance calculations based on types of numerical measures. This research method compared distance calculation methods in the K-Means algorithm, such as Euclidean Distance, Canberra Distance, Chebychev Distance, Cosine Smilirity, Dynamic Time Warping Distance, Jaccard Smilirity and Manhattan Distance to find out how optimal the distance calculation is in the K-Means method. Determining the best distance calculation can be seen from the smallest Davies Bouldin Index value. The data used in this study was on cosmetic sales at Devi Cosmetics, consisting of cosmetics sales from January to April 2022 with 56 product items. The result of this study was a comparison of numerical measures in the K-Means Clustering algorithm. The optimal cluster was calculating the Euclidean distance with a total of 9 clusters with a DBI value of 0.224. In comparison, the best average DBI value was the calculation of the Euclidean Distance with an average DBI value of 0.265.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139255558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analyzing Sentiment with Self-Organizing Map and Long Short-Term Memory Algorithms 利用自组织映射和长短期记忆算法分析情感

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-11-20 DOI: 10.30812/matrik.v23i1.3332

F. Sinaga, Sio Jurnalis Pipin, Sunaryo Winardi, Karina Mannita Tarigan, Ananda Putra Brahmana

{"title":"Analyzing Sentiment with Self-Organizing Map and Long Short-Term Memory Algorithms","authors":"F. Sinaga, Sio Jurnalis Pipin, Sunaryo Winardi, Karina Mannita Tarigan, Ananda Putra Brahmana","doi":"10.30812/matrik.v23i1.3332","DOIUrl":"https://doi.org/10.30812/matrik.v23i1.3332","url":null,"abstract":"This research delves into the impact of Chat Generative Pre-trained Transformer, one of Open Artificial Intelligence Generative Pretrained Transformer models. This model underwent extensive training on a vast corpus of internet text to gain insights into the mechanics of human language and its role in forming phrases, sentences, and paragraphs. The urgency of this inquiry arises from Chat Generative Pre-trained Transformer emergence, which has stirred significant debate and captured widespread attention in both research and educational circles. Since its debut in November 2022, Chat Generative Pre-trained Transformer has demonstrated substantial potential across numerous domains. However, concerns voiced on Twitter have centered on potential negative consequences, such as increasedforgery and misinformation. Consequently, understanding public sentiment toward Chat Generative Pre-trained Transformer technology through sentiment analysis has become crucial. The research’s primary objective is to conduct Sentiment Analysis Classification of Chat Generative Pre-trained Transformer regarding public opinions on Twitter in Indonesia. This goal involves quantifying and categorizing public sentiment from Twitter’s vast data pool into three clusters: positive, negative, or neutral. In the data clustering stage, the Self-Organizing Map technique is used. After the text data has been weighted and clustered, the next step involves using the classification technique with LongShort-Term Memory to determine the public sentiment outcomes resulting from the presence of Chat Generative Pre-trained Transformer technology. Rigorous testing has demonstrated the robust performance of the model, with optimal parameters: relu activation function, som size of 5, num epoch som and num epoch lstm both at 128, yielding an impressive 95.07% accuracy rate.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139257829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0