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Paradigma
Published by Universitas Bina Sarana Informatika
ISSN : 14105063     EISSN : 25793500     DOI : http://dx.doi.org/10.31294/p
Core Subject : Science,
Computer Science & IT
The first Paradigma Journal was published in 2006, with the registration of the ISSN from LIPI Indonesia. The Paradigma Journal is intended as a media for scientific studies of research, thought and analysis-critical issues on Computer Science, Information Systems and Information Technology, both nationally and internationally. The scientific article refers to theoretical review and empirical studies of related sciences, which can be accounted and disseminated nationally and internationally. Paradigma Journal accepts scientific articles research at: Expert Systems, Information Systems, Web Programming, Mobile Programming, Games Programming, Data Mining, and Decision Support Systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 18 Documents
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Search results for , issue "Vol 22, No 2 (2020): Periode September 2020" : 18 Documents clear
Analysis Name Entity Disambiguation Using Mining Evidence Method Adelya Astari; Moch. Arif Bijaksana; Arie Ardiyanti Suryani
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (814.724 KB) | DOI: 10.31294/p.v22i2.8196

Abstract

Hadith is the second guideline and source of Islamic teachings after the Qur'an. One of the most Saheeh hadith is the book of Saheeh al-Bukhaari. Hadith Sahih Bukhari has a chain of narrators, hadith numbers, and contents of different contents. This tradition also has science that discusses the history of the narrators of the hadith called the Science of Rijalul Hadith. In the Sahih Bukhari hadith there are the names of the narrators of the hadith who have the same name, causing obligation between names. That makes it difficult for many ordinary people to understand these ambiguous names because it is not yet known whether the two names are the same person or not. So, it raises the problem of a name ambiguation for ordinary people who cannot distinguish whether the name of the narrator is the same person or not. To solve these problems, a solution is built, namely the disambiguation of names to eliminate the ambiguity of the name by checking the name, hadith number, narrators chain, content topics, circles, countries, and companions of the Prophet that are seen from the 3 last names before the Prophet based on the chain of narrators. Also, the solution is assisted by using a method Mining Evidence with several other approaches, i.e. Association label documents, word association labels, context similarity, cosine similarity, and word2vec to obtain all similarity values between name entities. After the similarity values are obtained, the data are grouped using the Clustering algorithm. This system is expected to be able to produce a good system performance with a confusion matrix based on value precision, recall, and accuracy.
Penerapan Metode Algoritma Apriori dan FP-Tree Pada Penentuan Pola Pembelian Obat Rizal Rachman; Nanang Hunaifi
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1219.75 KB) | DOI: 10.31294/p.v22i2.8258

Abstract

Dewasa ini perkembangan industri kesehatan khususnya farmasi meningkat. Itu bisa dilihat dari kemunculan Prodi farmasi di berbagai Akademika civitas. Seiring pertumbuhan industri, informasi tentang produknya menjadi kebutuhan bagi perusahaan. Salah satu kebutuhan penting adalah informasi tentang penjualan obat-obatan dan informasi tentang persiapan atau produksi obat-obatan. Informasi mengenai berapa banyak obat yang akan diproduksi merupakan hal yang sangat penting karena hal ini berkaitan dengan berapa banyak penjualan yang terjadi dalam kurun waktu tertentu atau target pasar yang akan dicapai. Algoritma priori termasuk jenis aturan asosiasi pada data mining. Aturan yang menyatakan hubungan antara berbagai atribut sering disebut analisis afinitas atau analisis pasar basket. Analisis asosiasi atau asosiasi aturan penambangan adalah teknik penambangan data untuk menemukan aturan kombinasi item. Dan FP-Tree adalah struktur penyimpanan data terkompresi. FP-Tree dibangun dengan memetakan setiap catatan transaksi ke setiap jalur spesifik di FP-tree. Berdasarkan data transaksi penjualan obat di pabrik Farma kimia Jakarta, dilakukan analisis menggunakan algoritma Apriori dengan dukungan parameter minimum 10% dan kepercayaan minimum 50%. Hasil penelitian menghasilkan 7 aturan Asosiasi dengan kombinasi item terbesar hingga 2 item.
Eksperimen Pengenalan Wajah dengan fitur Indoor Positioning System menggunakan Algoritma CNN Yessi Hartiwi; Errissya Rasywir; Yovi Pratama; Pareza Alam Jusia
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (621.118 KB) | DOI: 10.31294/p.v22i2.8906

Abstract

Facial recognition work combined with the facial owner's position estimation feature can be utilized in various everyday applications such as face attendance with position detection. Based on this, this study offers a system testing experiment that can be run with facial recognition features and an Indoor Positioning System (IPS) to automatically check the location of the owner of the face. Recently, deep learning algorithms are the most popular method in the world of artificial intelligence. Currently, the Deep Learning algorithm toolbox has provided various programming language platforms. Departing from research findings related to deep learning, this study utilizes this method to perform facial recognition. The system we offer is also capable of checking the position or whereabouts of objects using Indoor Positioning System (IPS) technology. Facial recognition evaluation using CNN obtained a maximum value = 92.89% and an accuracy error value of 7.11%. Meanwhile, the average accuracy obtained is 91.86%. In the evaluation of the estimated position tested using DNN, the highest value of r2 score is 0.934, the lowest is 0.930 and an average is 0.932 and the highest value is MSE is 4.578, the lowest is 4.366 and the average is 4.475. This shows that the facial recognition process that is tested is able to produce good values but not the position estimation process. Keywords: Face Recognition, IPS, CNN, MSE, Accuraccy.
Analisis Sentimen Pengguna Aplikasi Duolingo Menggunakan Metode Naïve Bayes dan Synthetic Minority Over Sampling Technique Saifurrachman Chohan; Arifin Nugroho; Achmad Maezar Bayu Aji; Windu Gata
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (510.885 KB) | DOI: 10.31294/p.v22i2.8251

Abstract

Belajar bahasa asing menjadi salah satu perhatian penting agar dapat bersaing dengan dunia internasional. Keterbatasan waktu dan biaya membuat aplikasi belajar bahasa inggris pada perangkat mobile lebih disukai sebagai media pembelajaran bahasa asing. Salah satu aplikasi yang sering di gunakan untuk belajar bahasa asing pada perangkat mobile adalah duolingo. Penelitian ini bertujuan untuk menemukan dan membandingkan klasifikasi dalam sentimen analisis dari ulasan pengguna aplikasi duolingo yang didapat dari google playstore. Text mining digunakan untuk membagi ulasan yang diberikan pengguna menjadi dua kelompok yaitu ulasan positif dan ulasan negatif. Rapid miner digunakan untuk mencari dan membandingkan dua metode klasifikasi yang berbeda antara dataset yang menggunakan Naive Bayes Classification saja dan data set yang menggunakan algoritma naive bayes dengan syntetic minority over-sampling technique (SMOTE). Hasil dari dua metode dalam penelitian ini menemukan bahwa hasil tertinggi didapatkan menggunakan algoritma naive bayes dengan syntetic minority over-sampling technique (SMOTE) dimana memiliki tingkat akuransi 91,95% dan AUC sebesar 0.740.
Penerapan Model Rapid Application Development Pada Perancangan Sistem Informasi Jasa Pengiriman Barang Lala Nilawati; Dedeh Sulastri; Yuyun Yuningsih
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1085.413 KB) | DOI: 10.31294/p.v22i2.8314

Abstract

Freight forwarding company is a company or business entity which is engaged in providing freight forwarding services. In connection with business activities that occur in service companies, a good management information system is needed that can manage data delivery. The availability of a good and accurate information system will be increasingly needed along with the increasing human need for information that is fast, precise and accurate. The steps needed to produce a software system so that it has good performance, of course, can not be separated from how to choose and apply the analysis and design methods. In this research, a goods delivery system will be designed using Rapid Application Development (RAD), where the authors analyze the data management system contained in the company, then create a prototype design that is suitable for data management to make it more complete, efficient, and easy to use as a development from the old system using Java Script and MySQL as its database. In addition, in designing the proposed system, which is the information system of freight forwarding services, the tools used are using ERD (Entity Relationship Diagram) and UML (Unified Modeling Language). Based on the analysis and application of the system followed by testing the system, the delivery system designed can make it easier for system users to process data, control data and prepare reports related to shipping data.
Analisis dan Implementasi Diagnosis Penyakit Sawit dengan Metode Convolutional Neural Network (CNN) Errissya Rasywir; Rudolf Sinaga; Yovi Pratama
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (700.673 KB) | DOI: 10.31294/p.v22i2.8907

Abstract

Jambi Province is a producer of palm oil as a mainstay of commodities. However, the limited insight of farmers in Jambi to oil palm pests and diseases affects oil palm productivity. Meanwhile, knowing the types of pests and diseases in oil palm requires an expert, but access restrictions are a problem. This study offers a diagnosis of oil palm disease using the most popular concept in the field of artificial intelligence today. This method is deep learning. Various recent studies using CNN, say the results of image recognition accuracy are very good. The data used in this study came from oil palm image data from the Jambi Provincial Plantation Office. After the oil palm disease image data is trained, the training data model will be stored for the process of testing the oil palm disease diagnosis. The test evaluation is stored as a configuration matrix. So that it can be assessed how successful the system is to diagnose diseases in oil palm plants. From the testing, there were 2490 images of oil palm labeled with 11 disease categories. The highest accuracy results were 0.89 and the lowest was 0.83, and the average accuracy was 0.87. This shows that the results of the classification of oil palm images with CNN are quite good. These results can indicate the development of an automatic and mobile oil palm disease classification system to help farmers.
Sentimen Analisis Stay Home menggunakan metode klasifikasi Naive Bayes, Support Vector Machine, dan k-Nearest Neighbor Ikhwanul Hakim; Arifin Nugroho; Sulaeman Hadi Sukmana; Windu Gata
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (141.56 KB) | DOI: 10.31294/p.v22i2.8237

Abstract

Dunia sedang dilanda pandemi Corona Virus, virus yang berasal dari kota Wuhan di negara Cina sebagai awal pusat dari pandemi virus tersebut. Virus tersebut menyerang pernafasan akut dan menyebar dengan cepat hampir keseluruh dunia karena proses penularannya yang relatif mudah. Pemberitaan terkait virus tersebut terjadi dengan saat masif baik dimedia nasional maupun internasional. Hampir seluruh media memberitakan tentang penyebaran virus tersebut. Salah satunya melalui media sosial, twitter adalah salah satu media sosial yang cukup banyak penggunanya dan cukup digemari. Banyak pengguna twitter membagikan informasi, mengeluarkan pendapat, maupun berbagi beberapa hal. Penelitian ini fokus pada sentimen analisis stay home pada pengguna twitter, untuk dapat melihat efek dari kebijakan tersebut terhadap kehidupan mereka. Karena hampir diseluruh negara yang terkena pandemi ini mengeluarkan kebijakan seperti itu. Data yang diperoleh akan diolah menggunakan tiga metode klasifikasi yaitu Naive Bayes (NB), Support Vector Machine (SVM), dan k-Nearest Neighbor (k-NN). Dengan ketiga metode klasifikasi tersebut, akan dicari metode mana yang akan menghasilkan akurasi yang paling baik terkait dengan stay home dari tweets para penggunanya. Setelah dilakukan percobaan, algoritma Support Vector Machine + Smote mendapatkan hasil akurasi yang paling baik jika dibandingkan dengan dua algoritma lainnya. Hasil akurasi yang didapat sebesar 80,05%.
Pengaruh Media Terhadap Pengambilan Keputusan Dalam Menjalankan Program Keluarga Berencana Dengan Algoritma Decision Tree Ali Mustopa; Siti Khotimatul Wildah; Ganda Wijaya; Windu Gata; Sarifah Agustiani
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (64.58 KB) | DOI: 10.31294/p.v22i2.8141

Abstract

Indonesia has become one of the countries with a diverse population so that it has the potential to experience social change, one of which is the influence of the media. Media is an information content that is almost a part of human life. One of the impacts of the media is in the health sector, one of which is in determining the Family Planning program. Family planning is one of the Indonesian government programs designed to reduce the speed of population growth. Since the implementation of the Family Planning Program in Indonesia many tools have been used to prevent pregnancy, namely contraception. Selection of a good contraction is certainly one important thing to plan. In determining good kotrasespi certainly there are influences from various things one of which is the media. Measurement of the influence of the media in determining the Family Planning program can be known by applying data mining. Research conducted with data mining uses a standard methodology called the Cross-Industry Center Process for Data Mining (CRISP-DM). The use of decissin tree in this study was done by comparing the same method by looking at the results of three models namely Split Validation, Cross Validation and Decision Tree Split. The results of Split Validation produce an accuracy of 90.50%, Cross Validation produces an accuracy of 91.58% and Decision Tree Split produces an accuracy of 89.83%. The best results are obtained by using cross validation where with the results of research on 1473 records the accuracy value is 91.58% and the AUC value is 0.690, where the results are obtained from the calculation of the True Positive (TP) 1328, False Negative (FN) ) 36, False Positive (FP) is 88 and True Negative (TN) 21. Exposure to the media is said to be good or influential if they do not have children and are Muslim and educate their husbands in junior high school with a low standard of living but the wife has a college education.  Keywords: Family Planning, Media Exposure, Data Mining, Decision Tree.
PENILAIAN RESIKO KEJAHATAN ILLEGAL CONTENT MENGGUNAKAN FRAMEWORK NIST 800-30 Ahmad Marsehan; Muhhamad Izman Herdiansyah; Ahmad Haidar Mirza; Darius Antoni
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (309.591 KB) | DOI: 10.31294/p.v22i2.8913

Abstract

In the current era, information dissemination tends to be easier to do, this is due to the development of the internet and smartphone technology, which causes everyone to act as a sender and receiver of news without having to be filtered. This will certainly lead to new problems, especially potential violations of the law or criminal acts of the ITE Law such as illegal content. To overcome this, it is necessary to apply cyber-risk management so that cyber risks in the aspect of illegal content can be managed. Based on research conducted using the NIST 800-30 Framework on several students in Lubuklinggau City, the behavior or actions that are usually carried out related to handling the dissemination of information on social media or the internet are in the aspect of not understanding differences in information containing illegal content and lack of understanding of legal consequences. in disseminating illegal content information on social media it is included in the high risk category, furthermore the inability of the public to assess the reliability and pleasure of sharing information without knowing the information's credibility falls into the medium risk category, and finally students are happy to read controversial information even though the information is not clearly its credibility is included in the low risk category.
Pengujian Implementasi Sistem Pengelolaan Keuangan Masjid Berbasis Web Dan Android Fachruddin Fachruddin; Muhammad Riza Pahlevi; Muhammad Ismail; Errissya Rasywir
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1145.465 KB) | DOI: 10.31294/p.v22i2.8908

Abstract

Manual financial management is one of the causes of data loss and report files. Meanwhile, financial reports are data that must be accounted for. As with our observations, the Darusalam Mosque (Pakuan Baru Village in Jambi City) quite often experiences these classic problems. With the use of Android-based application technology, it is hoped that the mosque's financial data will be more organized, neatly archived and transparent. The digital financial management or accounting system allows flexibility in accessing mosque financial reports. Therefore it is necessary to build a Mosque Financial Management System Based on the Android Platform. The Android-based financial management application will later be launched on Google Playstore, so that all parties who need this system can download this application for free. The application of applications with a whole series of good software engineering must be carried out in accordance with applicable business processes and do not change the flow of data and reports that have been running for years. The application of the Website-based application and the Android Platform that we did, was able to produce automatic and computerized mosque financial management and was considered very good in user testing

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