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.
Articles
695 Documents
<![CDATA[Pengembangan Sistem Informasi Pendaftaran Praktek Kerja Lapangan (PKL) dengan Konsep Hierarchical Model View Controller (HMVC) ]]>
<![CDATA[Suci Nurfauziah]]>;
<![CDATA[Tri Ramadani Arjo]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 5 No 1 (2021): July 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i1.2665
<![CDATA[Registration for Praktek Kerja Lapangan (PKL) in the Administration Business department has not been maximized. Some of the problems that occur include student registration which is still semi-manual so that it prolongs the registration process, one company only have three students for each Study Program so that students have to fight, this makes it difficult for the admin, manual PKL registration makes students have to queue in the administration room. The development of an information system with the HMVC pattern is able to make easier for programmers. Programmer can divide the system into more specific modules so that the execution of applications is more flexible. This research purpose to develop a registration information system for Praktek Kerja Lapangan (PKL) by applying the HMVC (Hierarchical Model View Controller) concept. The test results of the three experts show that all features of the PKL registration information system are running and functioning properly. And then, stress testing with Jmeter also showed satisfactory results, using 42 users / samples the average response time was less than 5 seconds and there were no errors.]]>
<![CDATA[Sistem Pendataan Barang Milik Negara dengan Secured QR Code dan REST API ]]>
<![CDATA[Maidel Fani]]>;
<![CDATA[Nelmiawati Nelmiawati]]>;
<![CDATA[Ahmad Hamim Thohari]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 5 No 1 (2021): July 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i1.2897
<![CDATA[Barang Milik Negara (BMN) adalah semua barang yang dibeli atau diperoleh atas beban Anggaran Pendapatan dan Belanja Negara (APBN) atau berasal dari perolehan lainnya yang sah. Politeknik Negeri Batam sebagai institusi pemerintah, wajib mengelola, memanfaatkan dan merawat BMN dengan baik agar didapat manfaat yang maksimal dari barang tersebut. Pemanfaatan teknologi mutlak diperlukan dalam rangka meningkatkan tata kelola dalam mengelola barang milik negara. Saat ini pengelolaan barang milik negara dilakukan dengan memberikan label yang berisi nomor pada setiap barang. Kendala yang muncul antara lain dalam proses pendataan, pelacakan dan pengelolaan barang milik negara, karena label tersebut dapat rusak, pudar dan terlepas. Penelitian ini mengusulkan aplikasi mobile dengan QR Code scanner untuk mengakses dan memeriksa data BMN dengan tepat. Aplikasi dilengkapi dengan secure QR Code generator dan REST API sebagai penyedia data BMN.]]>
<![CDATA[Perbandingan Performa Teknik Sampling Data untuk Klasifikasi Pasien Terinfeksi Covid-19 Menggunakan Rontgen Dada ]]>
<![CDATA[Akhmad Rezki Purnajaya]]>;
<![CDATA[Fuad Dwi Hanggara]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 5 No 1 (2021): July 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i1.3010
<![CDATA[The COVID-19 virus became a virus that was deadly and shocked the world. One of the consequences caused by the COVID-19 virus is a respiratory infection. The solution put forward for this problem is with a prediction of the COVID-19 virus infection. This prediction was made based on the classification of chest X-ray data. One challenging issue in this field is the imbalance on the amount of data between infected chest X-rays and uninfected chest X-rays. The result of imbalanced data is data classification that ignores classes with fewer data. To overcome this problem, the data sampling technique becomes a mechanism to make the data balanced. For this reason, several data sampling techniques will be evaluated in this study. Data sampling techniques include Random Undersampling (RUS), Random Oversampling (ROS), Combination of Over-Undersampling (COUS), Synthetic Minority Over-sampling Technique (SMOTE), and Tomek Link (T-Link). This study also uses the Support Vector Machines (SVM) data classification, because it has high accuracy. Furthermore, the evaluation is carried out by selecting the highest accuracy and Area Under Curve (AUC). The best sampling technique found was SMOTE with an accuracy value of 99% and an AUC value of 99.32%. The SMOTE technique is the best data sampling technique for the classification of COVID-19 chest x-ray data.]]>
<![CDATA[Klasifikasi Penyakit Hipertensi dan Diabetes Berbasis Web Pada Klinik Pratama Rumkitban 01.08.03 Batam ]]>
<![CDATA[Mira Chandra Kirana]]>;
<![CDATA[Michel K]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 5 No 1 (2021): July 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i1.3034
<![CDATA[The management of outpatient medical records at the Rumkitban Primary Clinic 01.08.03 Batam is still manual and causes many limitations and problems. This problem resulted in the inability of the clinic to run the Chronic Disease Treatment Program (PROLANIS) organized by BPJS-Health. The purpose of the study is to facilitate data processing and then from that data it can be used to classify hypertension and diabetes then the results of the classification are displayed in graphical form. This study discusses 2 diseases, namely hypertension and diabetes. The system uses the C45 Tree Decision Algorithm for automatic data processing. The attributes used are glucose, diastolic, systolic, insulin, and age to support the decision-making system. The system can make a decision whether the patient has hypertension, diabetes or not. The results of this study are the accuracy of classification accuracy in the system for hypertension shows 16.667% accuracy and 83.333% accuracy is not correct, then the calculation of diabetes classification accuracy shows 96.667% accuracy, and 3.333% accuracy is incorrect. This system is integrated with Mysql database to store the results.]]>
<![CDATA[Metode Naive Bayes dan SMART untuk Menentukan Perkembangan dan Status Balita ]]>
<![CDATA[Dewi, Qomariah Kumala]]>;
<![CDATA[Al Amin, Imam Husni]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol. 5 No. 1 (2021): July 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i1.3105
<![CDATA[Integrated Service Post (Posyandu) is a forum used for health services carried out from and for the community under the guidance of health workers. Currently, toddlers need to be given more attention to monitor their growth and development. The number of children under five who are monitored by posyandu cadres and puskesmas officers will certainly take a lot of time and require maximum accuracy in classifying the status of each toddler. The purpose of the design of this decision support system is to assist posyandu cadres in determining the developmental decisions of active and inactive toddlers. This research is very important to assist posyandu cadres in providing proper analysis of the developmental status of each toddler. The results of this study are an application that can be used to determine the criteria for growth and development of toddlers using the Naive Bayes and SMART methods so that they can help posyandu cadres in determining the development of toddler status.]]>
<![CDATA[Algoritma Triple Exponential Smoothing Untuk Prediksi Trend Turis Pariwisata Jatim Park Batu Saat Pandemi Covid-19 ]]>
<![CDATA[Safor Madianto]]>;
<![CDATA[Ema Utami]]>;
<![CDATA[Anggit Dwi Hartanto]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 5 No 1 (2021): July 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i1.3139
<![CDATA[The level of tourism visits in 2021 both local and foreign to Indonesian tourism has decreased drastically. The COVID-19 pandemic is one of the causes of this loss. In the last 1 year, the level of tourism has dropped dramatically due to this pandemic. The impact on a country is an economic recession, Singapore is a country that is experiencing a severe recession of up to -40%, a country is a country that also depends, one of which is on tourism. Jatim Park Batu is a tourism learning park and family recreation area in Batu, East Java. Jatim Park is a well-known tourism object in East Java. The uncertainty of the number of tourists each month affects the operational management of Jatim Park in making every decision, both technical and strategic decisions. The researcher proposes to use the Triple Exponential Smoothing algorithm, the Holt Winters model, where this algorithm is classified as a prediction algorithm that can consider trend and seasonal factors. The method of measuring accuracy uses the MAPE (Mean Absolute Percetage Error) method. Tests were carried out by initiating the alpha beta gamma parameter 30 times and obtained an average of 9%.]]>
<![CDATA[Penerapan Algoritma Support Vector Machine (SVM) untuk Klasifikasi Berita Hoax Covid-19 ]]>
<![CDATA[Isnin Apriyatin Ropikoh]]>;
<![CDATA[Rijal Abdulhakim]]>;
<![CDATA[Ultach Enri]]>;
<![CDATA[Nina Sulistiyowati]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 5 No 1 (2021): July 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i1.3167
<![CDATA[Hoax merupakan informasi yang dibuat oleh orang tidak bertanggung jawab dengan tujuan membuat orang lain mempercayai sesuatu yang tidak benar. Berita hoax yang paling mudah beredar adalah hoax tentang kesehatan. Di Indonesia sendiri semenjak diberitakan masuknya virus Covid-19, berita hoax tentang hal itu terus meningkat berdasarkan data yang dirilis oleh Kominfo periode Januari-Agustus 2020. Agar terhindar dari berita hoax ialah dengan lebih teliti membaca judul berita pada situs yang terpercaya seperti Kompas. Karena itu penelitian ini akan mengembangkan dan menganalisis model klasifikasi berita hoax Covid-19 dengan menerapkan algoritma Support Vector Machine (SVM) dengan metodologi Knowledge Discovery in Databases (KDD). Studi kasus penelitian ini dibagi dalam 2 kategori yaitu berita hoax yang didapat dari situs Trunbackhoax & Hoax buster sedangkan berita bukan hoax diambil dari situs berita Kompas. Hasil penelitian menyatakan bahwa Algoritma Support Vector Machine (SVM) dengan kernel linear memiliki hasil prediksi yang bagus pada skenario 3 (80:20) karena model sanggup dalam mengklasifikasikan berita hoax dan bukan hoax Covid-19. Akurasi yang didapat pada skenario 3 juga memiliki nilai akurasi tertinggi sebesar 97,06%. Sedangkan pada kernel RBF memiliki akurasi terendah pada skenario 4 (90:10) yaitu 90.46% dan model kurang bagus dalam mengklasifikasikan berita hoax maupun bukan hoax Covid-19.]]>
<![CDATA[Penerapan Metode Regresi Linear Berganda untuk Prediksi Kerugian Negara Berdasarkan Kasus Tindak Pidana Korupsi ]]>
<![CDATA[Alfanda Novebrian Maharadja]]>;
<![CDATA[Iqbal Maulana]]>;
<![CDATA[Budi Arif Dermawan]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 5 No 1 (2021): July 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i1.3184
<![CDATA[Tindak pidana korupsi merupakan kegiatan yang dapat mengakibatkan kerugian keuangan negara atau perekonomian negara serta dapat menghambat pembangunan nasional. Semenjak penindakan kasus korupsi 2013-2020, pada tahun 2014 merupakan angka tertinggi dalam jumlah kasus, yaitu sebanyak 629 kasus, sedangkan pada tahun 2020 negara mengalami kerugian tertinggi sebesar Rp. 18,6 Triliun. Adanya permasalahan tersebut perlu dilakukan kebijakan yang tepat serta antisipasi dalam meminimalisir kerugian negara pada tahun selanjutnya. Oleh karena itu penelitian ini melakukan prediksi kerugian negara berdasarkan tindak pidana korupsi dengan menggunakan regresi linear berganda. Regresi linear berganda merupakan salah satu metode statistik yang digunakan untuk menelusuri pola hubungan antara variabel terikat dengan dua atau lebih variabel bebas. Pembelajaran regresi linear berganda dalam penelitian ini menghasilkan model regresi yang dimana menghasilkan nilai konstanta yaitu 284645.5891073216 serta nilai koefisien yaitu -139837.38007863 dan 363493.06049751. Kemudian penelitian ini melakukan pengukuran performa model regresi linear dengan kondisi pembagian data 80% untuk data training dan 20% untuk data testing. Dari kondisi pembagian data tersebut memperoleh nilai RMSE sebesar 8447373.485 untuk data training dan 9769609.026 untuk data testing. Sedangkan untuk nilai koefesien determinasi memperoleh nilai sebesar 0.579 untuk data training yang tingkat hubungan antar variabelnya cukup kuat dan 0.662 untuk data testing yang berarti tingkat hubungan antar variabelnya kuat. Dengan melakukan prediksi menggunakan metode regresi linear berganda dapat memberikan informasi yang membantu pemerintah dalam mengambil kebijakan yang tepat terahadap permasalahan kasus korupsi serta meminimalisir dan mengantisipasi kerugian negara yang lebih besar untuk tahun selanjutnya.]]>
<![CDATA[Implementasi CRISP-DM Model Menggunakan Metode Decision Tree dengan Algoritma CART untuk Prediksi Curah Hujan Berpotensi Banjir ]]>
<![CDATA[Msy Aulia Hasanah]]>;
<![CDATA[Sopian Soim]]>;
<![CDATA[Ade Silvia Handayani]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i2.3200
<![CDATA[Indonesia is part of a tropical climate with high rainfall intensity. High rainfall intensity can potentially cause flooding. To minimize this, accurate weather predictions are needed to be able to anticipate beforehand. This research was conducted with the aim of classifying based on the rain category with the dichotomy of heavy rain and very heavy rain using data mining techniques with the CRISP-DM methodology. The algorithm used in the classification technique is CART (Classification And Regression Tree) with Confusion Matrix test parameters. Based on the results of the model evaluation, it shows that the CART algorithm has a fairly good performance in classifying with an accuracy value of 89.4%.]]>
<![CDATA[Mendeteksi Kematangan Pada Buah Mangga Garifta Merah Dengan Transformasi Ruang Warna HSI ]]>
<![CDATA[Ahmad Muslih Syafi’i]]>;
<![CDATA[Muhammad Fajar Ahadi]]>;
<![CDATA[Muhammad Iqbal Rasyid]]>;
<![CDATA[Faisal Dharma Adhinata]]>;
<![CDATA[Apri Junaidi]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v5i2.3217
<![CDATA[Garifta Mango is obtained from the combination of the best quality local mangoes. Garifta mango is said to have a sweeter taste variant than the quality of other types of mango. However, when choosing Red Garifta mangoes with a good level of ripeness, we are often confused. Sometimes Red Garifta mango entrepreneurs still use manual methods to distinguish the ripeness of Red Garifta mangoes. Therefore, this study carried out a systematic design using the HSI color space transformation method. We used 15 Red Garifta mangoes as test data and 30 Red Garifta mangoes as training data in the testing phase. After doing the test, we get the accuracy, precision, and recall of 15 test data, respectively 80%, 80%, and 87%. From this percentage value, it can be concluded that the method we use can be used to detect the ripeness of the Red Garifta mango fruit.]]>
