JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan reviewer.
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<![CDATA[Evaluasi Peggunaan Aplikasi Peduli Lindungi Pada Kalangan Masyarakat Umum Menggunakan Metode Pieces ]]>
<![CDATA[Ramadani, Indha Suci]]>;
<![CDATA[Utama Jaya, Joy Nashar]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4131
<![CDATA[COVID-19 Pandemic makes all Government in the world making somekind of some safety measures into increasing the health safety of it citizen. Efforts have been made to reduce the spread. Indonesian government came up with the "PeduliLindungi" application to protect people in their daily life. This study seeks to determine the level of satisfaction of "PeduliLindung" users using PIECES methode. This type of research is based on primary data which is directly given to respondents using a questionnaire. The main respondents are users who have used (PeduliLindungi). The respondent's questionnaire reached 69 samples and used the Slovin formula with an error tolerance of 5% so that only 59 samples were taken. These results show that efficiency has a significant effect on application users with P-Values "‹"‹< 0.05 and T-Statistics > 1.99 while the other five are still not significant because P-Values "‹"‹> 0.05 and T-Statistics < 1.99. The final number of T-Statistics in Efficiency domain is 4.740 which is bigger >1.99 which means that "PeduliLindungi" Application is efficient into helping the public or government tracking and reducing the COVID-19 Pandemic in spreading much further.]]>
<![CDATA[Optimization of K-Nearest Neighbors Algorithm with Cross Validation Techniques for Diabetes Prediction with Streamlit ]]>
<![CDATA[Prasetyo, Aditya Budi]]>;
<![CDATA[Laksana, Tri Ginanjar]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4182
<![CDATA[The problem that occurs in the application of K-Nearest Neighbors as a classification algorithm is the frequent occurrence of overfitting in data processing. This can be overcome by using cross-validation techniques in evaluating the algorithm model and minimizing overfitting. Then the performance of diabetes prediction accuracy is unknown using the K-Nearest Neighbors algorithm with cross-validation technique. The data used comes from the National Institute of Digestive and Kidney Diabetes in 2021. The case study in this study is to find out the initial screening for diabetes is supported by the results of algorithm accuracy and real time application of streamlit-based users. The purpose of this study was to optimize the accuracy results with a cross validation technique supported by the k-nearest neighbors algorithm in the study of diabetes data. The method used is the k-nearest neighbors algorithm which is supported by cross validation technique for optimal accuracy results. Then the application of a streamlit-based interactive web application for testing the accuracy results used by the user to see the probability that the user has diabetes. The results showed that the optimization of the Cross Validation technique supported by the KNearest Neighbors algorithm model worked well. The results of the confusion matrix using the cross validation technique are more accurate in terms of the advantages of using the cross-validation technique itself. So that the classification report which has a value of 95% is more accurate than the accuracy which is worth 92% because of the use of cross-validation techniques that can minimize overfitting in addition to considerations of the accuracy value and the implementation of streamlit-based interactive web applications for user testing is going well.]]>
<![CDATA[Pencarian Pola Pemakaian Obat Menggunakan Algoritma FP-Growth ]]>
<![CDATA[Salsabila, Nikita]]>;
<![CDATA[Sulistiyowati, Nina]]>;
<![CDATA[Padilah, Tesa Nur]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4187
<![CDATA[Obat'merupakan sebuah bahan yang digunakan'untuk mendiagnosis sebuah penyakit yang dapat digunakan untuk pencegahan atau pengobatan penyakit pada manusia atau hewan. Dalam penggunaannya, proses perencanaan stok obat di klinik atau rumah sakit merupakan hal penting yang harus diperhatikan karena apabila stok obat tidak sesuai maka akan menimbulkan masalah dalam ketersediaan stok obat. Pada penelitian ini terjadi permasalahan pada stok obat pada sebuah klinik yang berlokasi di Kabupaten Brebes yang mana terjadi kelebihan stok obat yang mengakibatkan jumlah data stok obat tidak sesuai dengan stok obat yang tersedia. Oleh sebab itu proses data mining dengan bantuan metodologi Knowledge Discovery in Databases (KDD) digunakan untuk membantu dalam pengelolaan stok obat pada klinik tersebut. Adapun tahapan KDD diantaranya, data selection, data pre-processing, data transformation, data mining, dan interpretation/evaluation. Pengujian dilakukan dengan menggunakan aplikasi Rapid Miner. Penerapan metode asosiasi pada data mining mampu menghasilkan suatu aturan asosiasi baru dari masing"“masing item. Berdasarkan analisis yang dilakukan dengan algoritme FP-Growth, ditetapkan nilai support sebesar 75 frekuensi atau 23% dan nilai confidence sebesar 75%. Hasil penelitian menghasilkan 6 aturan asosiasi dengan kombinasi item terbesar hingga 3 item. Evaluasi pengujian yang didapat dari nilai Lift Ratio mendapat nilai rata-rata sebesar 1.267.]]>
<![CDATA[Pemetaan UMKM dalam Upaya Pengentasan Kemiskinan dan Penyerapan Tenaga Kerja Menggunakan Algoritma K-Means ]]>
<![CDATA[Kurniadewi, Herwinda]]>;
<![CDATA[Hakim, Rijal Abdul]]>;
<![CDATA[Jajuli, Mohamad]]>;
<![CDATA[Jaman, Jajam Haerul]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4227
<![CDATA[Covid pandemic created an economic crisis. Increase the poverty rate by double digits in one year in Indonesia. Covid pandemic has also had an impact on Indonesia's employment conditions, such as finding it difficult to find work. Absorption of labor has a close correlation with poverty. The workforce has a significant influence on the poverty level. One of the regencies in West Java which has a high poverty rate and job seekers is increasing compared to the previous year, Purwakarta Regency. Poverty alleviation by developing MSMEs has good potential. The development of MSMEs will be able to absorb more workers and increase people's income so that it can encourage the rate of economic growth. In this study using the CRISP-DM methodology. In this study, MSMEs in Purwakarta Regency were grouped based on location, number of MSMEs, number of poor people and number of job seekers by using the k-means algorithm and mapping using python. The results of the grouping obtained 3 clusters, namely clusters as many as 6 districts, clusters as many as 8 districts and clusters as many as 3 districts. To determine the performance of the model, an evaluation of the silhouette coefficient which obtained a value of 0.45.]]>
<![CDATA[Analisis Sentimen Twitter Terhadap Opini Publik Atas Isu Pencalonan Puan Maharani dalam PILPRES 2024 ]]>
<![CDATA[Vonega, Defangga Aby]]>;
<![CDATA[Fadila, Aminudin]]>;
<![CDATA[Kurniawan, Dwi Ely]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4300
<![CDATA[Twitter can be seen as a platform for candidates and users to gain substantial reach to show their views on who the president will be elected to in 2024. The aim of this study is to explore contrasting information over time regarding whether Puan Maharani can be one of the candidates. The best according to the Indonesian people. In this study, sentiment analysis was carried out using the text mining method and several libraries such as TextBlob, VaderSentiment, and SentiWordNet to retrieve and classify the polarity of opinions from data that had been crawled. In the dataset generated with the keyword "Puan Maharani" The average negative sentiment is only 0.1%, neutral sentiment is 97.25, and positive sentiment is 2.55%. It can be concluded that Twitter users tend to be neither aggressive nor defensive in discussing issues leading to the candidacy of Puan Maharani in the upcoming 2024 Indonesian presidential election.]]>
<![CDATA[Optimization of the Decision Tree Method using Pruning on Liver Disease Classification ]]>
<![CDATA[Wardhani, Anindya Khrisna]]>;
<![CDATA[Nugraha, Ega]]>;
<![CDATA[Ulfiana, Qonita]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4350
<![CDATA[The amount of data about liver disease can be used to become information that can be extracted using the decision tree data mining method. However, there is a weakness in the decision tree method, namely over-fitting the resulting tree can produce a good model in training data but normally cannot produce a good tree model when applied to unseen data. Based on experiments conducted using datasets taken from The UCI Machine Learning Repository database is the ILPD dataset which contains 583 clinical data with 10 attributes with a target output of 416 positive liver and 167 negative liver. The results show that the decision tree algorithm using pruning and without pruning has been tested showing an increase in accuracy. The results of the decision tree performance without pruning generated in the confusion matrix for the accuracy measure, which is 73.58 %. While the results of the system performance using the pruning method have an accuracy of 73.76%. Although the accuracy value is slightly adrift, it can prove that the decision tree method using the pruning method has much better accuracy. In addition, the models and rules generated by the decision tree can be used as the basis for developing a prototype application for liver disease classification.]]>
<![CDATA[Data Mining Untuk Estimasi Sidang Perkara Narkotika Menggunakan Metode Regresi Linier Berganda ]]>
<![CDATA[Khairina, Dyna Marisa]]>;
<![CDATA[Shapanara, Rhenaldi Octa]]>;
<![CDATA[Maharani, Septya]]>;
<![CDATA[Hatta, Heliza Rahmania]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4401
<![CDATA[Narcotics cause unrest in the community because it has a very bad impact on society. The number of reports of narcotics cases has an impact on the number of executions in the trial of these cases. From the number of trial executions, it is necessary to follow up efforts to anticipate the handling of narcotics cases by knowing in advance the trend/pattern of increasing/decreasing narcotics cases as supporting information in efforts to handle these cases. The purpose of the research is to help speed up the process of calculating and managing the information contained in the data into new knowledge so that an estimate of the trial of narcotics cases is produced based on information on the pattern/trend of increasing/decreasing narcotics. The case uses multiple linear regression which is then tested for the coefficient of determination and the simultaneous significant test. The case data used is a time series from January 2021 to December 2021. The resulting regression model is Y = 39.777 "“ 0.035 X1 "“ 0.065 X2. The calculation of the regression results shows that the estimation of the implementation of the number of stages of narcotics cases with stage I and stage II variables has a negative effect on the implementation of narcotics cases based on the results of hypothesis testing conducted.]]>
<![CDATA[Pembagian Task Karyawan Berdasarkan Riwayat Kerja dengan Metode Naive Bayes ]]>
<![CDATA[Nashihah, Mustafidatun]]>;
<![CDATA[Aminah, Siti]]>;
<![CDATA[Maulidi, Rakhmad]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4602
<![CDATA[Accuracy and suitability in the division of employee tasks have an important role in the division of employee tasks, in order to obtain a list of criteria that are in accordance with the abilities of employees in one division. PT. Assist Software Indonesia Pratama is currently still in manual division of tasks, namely by sorting out tasks based on features, applications, divisions, and employees who usually do the work. So that it takes a long time in the process of dividing employee tasks, one of the factors is HRD must sort out tasks based on features, applications in order to determine the division and employees who work on the task. The purpose of the research is to facilitate the division of tasks to employees in order to get a list of criteria that are in accordance with the abilities of employees in one division using the Naive Bayes method. So we need a system that can help HRD in distributing employee tasks in accordance with the division and employee capabilities. In this task distribution system using the Multinomial Naïve Bayes Classifier method as a determinant of employee task distribution. The division of employee tasks is based on the tasks that have been done by the previous employee, so that the system can perform the appropriate task division. The system can see the similarities between tasks using the Multinomial Naïve Bayes method as a consideration for determining the divisions and employees who work with the percentage accuracy of 92.5% and 82.5%.]]>
<![CDATA[Analisis Faktor-Faktor yang Mempengaruhi Harga Saham pada Perusahaan Sub Sektor Kosmetik dan Barang Keperluan Rumah Tangga dengan Python ]]>
<![CDATA[Yuliantoro, Heri Ribut]]>;
<![CDATA[Nurmalasari, Dini]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4606
<![CDATA[This study aims to determine the relationship between stock prices of companies listed on the Stock Exchange in the Household Goods and Cosmetics sub-sector with several independent variables, namely quick ratio, current ratio, net profit margin, and return on assets. The analysis carried out is multiple regression analysis, conventional hypothesis testing, and descriptive analysis. The results of this study indicate that the current ratio and return on assets have a large influence on stock prices on the IDX, quick ratios and net profit margins have no significant effect. Return on assets, net profit margin, quick ratio, and current ratio all together have a big influence on stock prices. The results of the analysis of this study can be concluded that stock prices are positively influenced by the variables quick ratio, current ratio, net profit margin, and return on assets of 49.4%, and the remaining 50.6% is influenced by other factors.]]>
<![CDATA[Digital Marketing Strategy on Fashion Industry among Z Generation in Batam City ]]>
<![CDATA[Susanti, Tri]]>;
<![CDATA[Siahaan, Mangapul]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v6i2.4615
<![CDATA[The Internet has become a part of society in almost all areas of business. The popularity of the internet causes increase in the needs of the community, especially generation z which has a major influence on daily life. Information that is spread through social networks is a solution to the needs of generation z. They can make purchases online by utilizing digital media and available information. This study was conducted to determine the effect of digital marketing on online purchase intention of generation z in Batam City in the fashion industry through brand equity and consumer perceived value. This study uses an explanatory sequential mixed method that combines both quantitative and qualitative methods. Data collection on the quantitative method was carried out by distributing questionnaires to 404 respondents and analyzed by using the Structural Equation Modeling (SEM) using SPSS Statistics 25 and SPSS AMOS 22. The qualitative method was carried out by interviewing 20 sources and analyzed by classifying the data used to support quantitative results. This study shows that digital marketing does not have a positive effect on online purchase intentions, digital marketing does not have a positive effect on online purchase intentions through brand equity as a mediator, and digital marketing has a positive effect on online purchase intentions through consumer perceived value as a mediator.]]>
