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INDONESIA
JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Published by Politeknik Negeri Batam
ISSN : -     EISSN : 25486861     DOI : 10.3087
Core Subject : Science,
Computer Science & IT
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.
Arjuna Subject : -
Articles 695 Documents
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Pencarian Pola Pemakaian Obat Menggunakan Algoritma FP-Growth Salsabila, Nikita; Sulistiyowati, Nina; Padilah, Tesa Nur
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4187

Abstract

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.
Pemetaan UMKM dalam Upaya Pengentasan Kemiskinan dan Penyerapan Tenaga Kerja Menggunakan Algoritma K-Means Kurniadewi, Herwinda; Hakim, Rijal Abdul; Jajuli, Mohamad; Jaman, Jajam Haerul
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4227

Abstract

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.
Analisis Sentimen Twitter Terhadap Opini Publik Atas Isu Pencalonan Puan Maharani dalam PILPRES 2024 Vonega, Defangga Aby; Fadila, Aminudin; Kurniawan, Dwi Ely
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4300

Abstract

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.
Optimization of the Decision Tree Method using Pruning on Liver Disease Classification Wardhani, Anindya Khrisna; Nugraha, Ega; Ulfiana, Qonita
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4350

Abstract

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.
Data Mining Untuk Estimasi Sidang Perkara Narkotika Menggunakan Metode Regresi Linier Berganda Khairina, Dyna Marisa; Shapanara, Rhenaldi Octa; Maharani, Septya; Hatta, Heliza Rahmania
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4401

Abstract

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.
Pembagian Task Karyawan Berdasarkan Riwayat Kerja dengan Metode Naive Bayes Nashihah, Mustafidatun; Aminah, Siti; Maulidi, Rakhmad
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4602

Abstract

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%.
Analisis Faktor-Faktor yang Mempengaruhi Harga Saham pada Perusahaan Sub Sektor Kosmetik dan Barang Keperluan Rumah Tangga dengan Python Yuliantoro, Heri Ribut; Nurmalasari, Dini
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4606

Abstract

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.
Digital Marketing Strategy on Fashion Industry among Z Generation in Batam City Susanti, Tri; Siahaan, Mangapul
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4615

Abstract

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.
Analisis Fitur HRV pNN50 pada Sinyal Psikofisiologis Marah Manusia Rumpa, Lantana Dioren; Panggalo, Iindarda S.
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4617

Abstract

Affective Computing dan Affective medicine dapat menjadi bidang yang menggabungkan teknik komputasi, ilmu kesehatan dan psikologi. Bidang ini dikembangkan untuk mempelajari dan mengkomputasi psikologi manusia dengan menggunakan metode matematika. Dalam paper ini, kami meneliti sinyal psikofisiologis Marah Manusia dengan menggunakan fitur pNN50 Heart Rate Variability. Dalam penelitian ini kami menggunakan sensor EKG untuk merekan reaksi jantung manusia terhadap stimuli video marah yang dipertunjukkan ke mereka. Sinyal tersebut akan dianalisis dengan menggunakan aplikasi kubiosHRV untuk mendapat nilai pNN50 dari masing-masing partisipan. Hasil penelitina ini menunjukkan bahwa ada perbedaan nilai pNN50 sebelum dan sesudah mendapatkan Stimuli Video. Hal ini menunjukkan bahwa pNN50 dapat digunakan sebagai fitur untuk membedakan sinyal jantung manusia pada saat marah dan normal.
Deteksi Tangan Otomatis Pada Video Percakapan Bahasa Isyarat Indonesia Menggunakan Metode YOLO Dan CNN Arifah, Indah Inayatul; Fajri, Fathorazi Nur; Pratamasunu, Gulpi Qorik Oktagalu
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4694

Abstract

Bahasa merupakan alat atau wahana untuk menyampaikan antar manusia satu dengan yang lainnya. Bagaimanapun, tidak setiap orang dapat menggunakan bahasa verbal dengan sempurna. Seperti orang yang tuli dan bisu, mereka tidak bisa menyampaikan apa yang ingin di sampaikan dengan baik. Tuli atau tunarungu adalah kekurangan kemampuan mendengar dari satu atau dua telinga. Dalam berkomunikasi tunarungu cenderung menggunakan bahasa isyarat. Salah satu bahasa isyarat yang sering digunakan ialah berupa angka, satu, dua, tiga, empat, dan lima. Dalam penelitian ini di gunakan metode You Only Look Once (YOLO) dan Convolutional Neural Network (CNN) untuk membantu sistem agar bisa membaca setiap gerakan yang dilakukan oleh tangan dan menghasilkan output berupa teks seperti tangan berisyarat satu bertuliskan satu atau tangan berisyarat dua bertuliskan dua dan seterusnya. Adapun tahapan yang dilakukan pada penelitian ini yaitu pengumpulan data , pengolahan gambar atau proses pre-processing data dalam pengimplementasian YOLO dan CNN. Setelah itu dilakukan uji coba dengan menggunakan Gambar dan video dari data BISINDO. Untuk hasil uji coba yang telah dilakukan menghasilkan akurasi sebesar 89 %.

Page 13 of 70 | Total Record : 695

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