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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika SEINASI-KESI JUSIM (Jurnal Sistem Informasi Musirawas) JSAI (Journal Scientific and Applied Informatics)
Purba, Mariana
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Computer Science & IT Decision Sciences, Operations Research & Management

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ANALISIS SENTIMEN MARKETPLACE DI ERA SOCIETY 5.0 MENGGUNAKAN ALGORITMA NAIVE BAYES Yadi, Yadi; Asminah, Asminah; Purba, Mariana; Padya, Inka Rizki
JUSIM (Jurnal Sistem Informasi Musirawas) Vol 8 No 1 (2023): JUSIM (Jurnal Sistem Informasi Musirawas) JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusim.v8i1.1953

Abstract

Konsep dari perkembangan teknologi yang semakin berinovasi membawa dampak yang sangat besar bagi masyarakat sebagai unsur pendukung untuk mempermudah dalam proses penyelesaian permasalahan, marketplace merupakan hasil dari perkembangan teknologi yang berbasis ecomerce pada era society 5.0 dimana masyarakat harus mampu berkolaborasi dengan teknologi. Pemanfaatan marketplace sebagai sarana transaksi jual beli beraneka macam produk yang besar tidak terlepas dari opini masyarakat, oleh sebab itu Tujuan penelitian untuk melihat reviews masyarakat terhadap pemanfaatan marketplace berdasarkan pada opinion positif, negatif dan netral. Analisis sentimen dipergunakan untuk melakukan pengolahan teks data mining melalui teks analytic dengan algortima naïve bayes. Hasil penelitian analisis sentiment marketplace dengan data reviews Shopee sebanyak 11.7M, Bukalapak 2.19M, Lazada 21.4M dan Tokopedia 6.52M di era society 5.0 terlihat bahwa interaksi manusia dalam pemanfaatan teknologi sangat besar hal ini terlihat dari jumlah pengguna dan reviews yang dilakukan oleh masyarakat pada kondisi ini analisis sentimen yang telah dilakuan berdasarkan presentase positif sebesar 88%, negatif 3% dan netral 9% . Sehingga dapat disimpulkan bahwa kolaborasi yang dilakukan oleh masyarakat terhadap teknologi sudah baik dalam pendukung informasi pemenuhan kebutuhan aktivitas sehari-hari.
Implementation Opinion Mining For Extraction Of Opinion Learning In University Purba, Mariana; Yadi, Yadi
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.11994

Abstract

Opinion mining is a field of Natural Language Processing (NLP) that is used to carry out the process of extracting and processing textual data which functions to obtain information through sentiment analysis from a document in the form of text, among others, to detect attitudes towards objects or people. Sub-processes in opinion mining can use documents of subjectivity, opinion orientation, and detection targets to find out the data used as sentiment analysis, sentiment analysis aims to assess emotions, attitudes, opinions, and evaluations conveyed by a speaker or writer towards a product or towards a public figure. In this study, an opinion mining system was developed to analyze learning in college. The methodology used is quantitative descriptive, while the processing of sentiment analysis data uses Azure machine learning. Sentiment analysis results are very good at assessing opinions or opinions and emotions, and attitudes conveyed by someone. The learning process is the main element that must run well so that competency and achievement in learning can be maximally conveyed to students. Documents that identified opinions were then classified into negative, neutral, and positive opinions based on the results. In general, it can be concluded that the value obtained by sentiment analysis using Azure Machine Learning tools is quite good, judging from the results of a positive class of 0.79 and a neutral class of 0.53. The use of cleaning and labeling techniques and other classifications is still very possible to use. To get a better accuracy value.
Perbandingan Implementasi Algoritma CT-PRO dan Algoritma C45 Untuk Menentukan Pola Nasabah Wati, Ade Sukma; Octavia, Pipin; Putra, Azhar Andika; Purba, Mariana; Wibisono, M Bayu
PROSIDING SEINASI-KESI Vol 1, No 1 (2022): SEMINAR NASIONAL INFORMATIKA, SISTEM INFORMASI, DAN KEAMANAN SIBER
Publisher : Fakultas Ilmu Komputer UPN Veteran Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Bank merupakan salah satu instansi pemerintah atau perusahaan untuk mengelola keuangan. Sebagai upaya untuk memberikan kinerja yang baik kepada nasabah diperlukan tata kerja yang tertib, rapi dan teliti sehingga akan menghasilkan informasi yang cepat, akurat dan tepat waktu sesuai kebutuhan. Dalam instansi bank banyak data yang setiap tahunnya bertambah. Salah satunya yaitu data nasabah baru. Akan tetapi dengan sekian banyaknya data nasabah baru maka semakin sulit juga data pola nasabah baru tersebut dipelajari lebih lanjut dan umumnya hanya digunakan sebagai arsip saja. Pada penelitian ini, telah diterapkan metode Algoritma CT-PRO serta ALgoritma c45 suatu studi kasus, yaitu kasus menentukan “Pola Nasabah”. menentukan pola nasabah dari ratusan atau ribuan field. Dari hasil implementasi yang dilakukan, ada sebuah aplikasi yang dapat menerapkan algoritma CT-PRO dan algoritma C45 pada kasus tersebut. 
Evaluasi Aplikasi Pemesanan Tiket Menggunakan Metode System Usability Scale (SUS) dan Model D&M IS Success Purba, Mariana; Dianing Asri, Sri; Noprisson, Handrie; Utami, Marissa; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6444

Abstract

Software product development not only focuses on features but also usability aspects. User experience is very important in the evaluation of reusability to understand the user's interaction with the product or system. Reusability factors include user satisfaction, efficiency, and effectiveness to achieve specific goals. The main purpose of this study is to evaluate the usability aspect of online ticket booking applications. This evaluation process is important to identify development and improvements to user views and application usage satisfaction. In this study, the object studied was an online travel booking application in Indonesia. The research instrument uses a quantitative and qualitative mixed-method approach. For the quantitative approach, the System Usability Scale (SUS) is used and as a basis for a qualitative approach, the D&M IS Success Model approach is used. Based on the evaluation results, there are several points that should be improved including the interface design should be simple, the reduction in the size of memory used by applications, features to communicate with customer service easily, data integration, and time notifications to complete payments.
Perancangan Aplikasi Manajemen Persediaan Barang di Perusahaan Pengelola Jaringan Akses Telekomunikasi Menggunakan Unified Modelling Language dan Prototyping Purba, Mariana; Dianing Asri, Sri; Ghufron, Akhmad; Umilizah , Nia; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6445

Abstract

Managing inventory in a telecommunications access network management company is very important because applications with good data management effectively increase the chances of success and maximize profits for the company. In addition, proper inventory data management is essential for identifying new market opportunities, forecasting risks, and understanding market trends. This study aims to clarify the design of inventory applications in accordance with the problems that exist at PT. XYZ is owned by the government as a case study location based on minimum service standards (SPM). This design uses unified modelling language (UML) such as use cases, activity diagrams, class diagrams and prototyping models to support the development of inventory applications in telecommunications access network management companies. The inventory management application in the telecommunication access network management company provides features for admins / users in processing supplier data, incoming goods data and outgoing goods data, and printing monthly reports on inventory of goods
Analysis of Travel Ticket Booking Application Services Based on Supporting Factors for Purchase Intention Purba, Mariana; Dianing Asri, Sri; Noprisson, Handrie; Utami, Marissa; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6446

Abstract

Aplikasi pemesanan tiket perjalnan ini harus memiliki kualitas dari segi perspektif produk agar dapat meningkatkan purchase intention oleh pengguna. Purchase intention dari layanan aplikasi dapat dilihat dari beberapa faktor antara lain usabilitas (usability), harga (price), kemudahan penggunaan (ease of use), complementarity dan hiburan (entertainment). Penelitian ini akan mengusulkan model penelitian untuk identifikasi kualitas layanan aplikasi online travel booking berdasarkan perspektif produk untuk meningkatkan purchase intention berdasarkan analisis dataset yang dikumpulkan dari sampel responden. Dari hasil pengumpulan data, dari total 1267 kuesioner yang dikumpulkan hanya memperoleh 1029 kuesioner yang valid. Model diuji menggunakan skor tingkat signifikan two-tails sebesar 0,05 untuk pengujian hipotesis. Menurut analisis data, faktor complementary memiliki pengaruh terbesar purchase intention dengan nilai uji-t sebsar 6,771. Selain itu, faktor entertainment memiliki pengaruh terbesar kedua dengan t-nilai 5.334. Faktor usability memiliki pengaruh terhadap purchase intention terbesar ketiga nilai uji-t 4.620. Faktor ease of use memiliki pengaruh terbesar keempat dengan nilai uji-t 3.641.
Classification of Text Datasets of Public Complaints Against the Government on Social Media Using Logistic Regression Purba, Mariana; Dianing Asri, Sri; Ayumi, Vina; Salamah, Umniy; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6447

Abstract

Di era teknologi saat ini, salah satu media sosial yang banyak digunakan dalam berinteraksi dan memberikan opini, pengaduan masyarakat, serta saran adalah Twitter. Dalam bidang pemerintahan, tweet yang mengandung opini atau pengaduan masyarakat terhadap suatu layanan atau program organisasi dapat digunakan sebagai umpan balik untuk memperbaiki atau meningkatkan kualitas layanan. Penelitian ini berfokus pada klasifikasi tweet untuk membedakan tweet yang tergolong pengaduan masyarakat atau non-pengaduan masyarakat dengan menerapkan algoritma pemelajaran mesin yaitu logistic regression (LR). Tahap dari penelitian ini antara lain crawling dan labeling dataset, pre-processing, pemodelan menggunakan classifier logistic regression, serta evaluasi kinerja classifier. Tahapan dalam penelitian ini seperti preprocessing, klasifikasi dan evaluasi dilakukan menggunakan bahasa pemrograman Python dengan bantuan scikit-learn library. Berdasarkan hasil eksperimen, model penelitian dengan menggunakan fitur ekstraksi CountVectorizer mencapai kinerja yang lebih baik daripada TfidfVectorizer. Eksperimen dengan menggunakan ekstraksi fitur TfidfVectorizer mencapai akurasi 92% (F1 score: 0.9181, precision: 0.9191 recall: 0.9181, kappa: 0.8363) sedangkan menggunakan akurasi CountVectorizer mencapai 94% (F1 score: 0.9355, precision: 0.9406, recall: 0.9356, kappa: 0.8715).
Studi Literatur: Transfer Learning Untuk Analisis Penyakit COVID-19 Berdasarkan Dataset Chest X-ray Purba, Mariana
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 2 (2024): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i2.6571

Abstract

The urgency of the impact of the COVID-19 disease that attacks people around the world encourages special research, especially in the field of artificial intelligence. This study aims to conduct a literature study related to the use of artificial intelligence, especially transfer learning in analyzing COVID-19 disease based on chest X-ray datasets. The research method of this research adapts the Preferred Reporting for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The results of the analysis of this data to answer research questions regarding the transfer learning model for the analysis of COVID-19 disease based on the chest X-ray dataset, it is known that the models used are MobileNet, Inception, VGG and ResNet. MobileNetV2 can be optimized by adding a global average pooling layer, dropout layer and dense layer and get an accuracy of 98.65%. InceptionV3 can be combined with Xception and get 98.8% accuracy. VGG-16 can be combined with ResNet-50 Xception and get 98.93% accuracy. ResNet-50 can be optimized by adding a dropout layer and a dense layer and getting an accuracy of 97.65%.
Co-Authors Asminah Asminah, Asminah Ayumi, Vina Azhar Andika Putra Dianing Asri, Sri Ghufron, Akhmad Iryani, Lemi Noprisson, Handrie Octavia, Pipin Padya, Inka Rizki Salamah, Umniy Umilizah , Nia Wati, Ade Sukma Wibisono, M Bayu Yadi, Yadi