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All Journal Jurnal Nasional Komputasi dan Teknologi Informasi STRING (Satuan Tulisan Riset dan Inovasi Teknologi) JISICOM (Journal of Information System, Infomatics and Computing) Journal Zetroem Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Jurnal Rekayasa Komputasi Terapan Bulletin of Information System Research International Journal of Informatics and Computing
Ega Shela Marsiani
Department Of Informatics, Universitas Indraprasta PGRI, Indonesia
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Neuroscience Transportation

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Penerapan Metode Moora dalam Keputusan Pemilihan Produk Layak Produksi Terbaik Natsir, Fauzan; Izzatilah, Millati; Marsiani, Ega Shela
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 9, No 3 (2025)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/string.v9i3.28708

Abstract

Decision support system is a system that can be a problem solving quickly, especially in ranking and identifying the score of choices from highest to lowest. The research conducted aims to use the MOORA approach in determining superior products, so that it can help companies in the marketing process, selection, and production decisions based on the best product recommendations produced. In this research, the case study discussed is the selection of production-worthy products to meet quality. If the process is still done manually, it takes a long time and the evaluation process becomes inefficient. Therefore, a decision support system was designed to support the evaluation process. The MOORA method is used in the implementation of this system to test its accuracy. The results obtained from this system will be tested through sensitivity tests to criteria, value weighting, and correction tests, with the aim of knowing the number of criteria that can be added.
Support Vector Machine Based Machine Learning for Sentiment Analysis of User Reviews of the Bibit Application on Google Play Store Ega Shela Marsiani; Fauzan Natsir; Redo Abeputra Sihombing; Millati Izzatillah; Rajiansyah Rajiansyah
JICO: International Journal of Informatics and Computing Vol. 1 No. 2 (2025): November 2025
Publisher : IAICO

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

Abstract

The increasing use of financial technology (fintech) applications has changed the investment patterns of users in Indonesia. Bibit, as one of the popular fintech investment platforms, receives many user reviews through the Google Play Store that reflect user perceptions and satisfaction levels. Although the volume of user reviews continues to increase, systematic analysis of user sentiment is still limited, making it difficult for developers to understand the needs and experiences of users. Therefore, an artificial intelligence-based approach is needed to efficiently and objectively extract and analyze user opinions. This study aims to conduct sentiment analysis of user reviews of the Bibit application using a Machine Vector Machine (SVM) based machine learning model. The research methodology includes data collection, pre-processing of texts, extraction of features using TF-IDF, as well as classification of sentiment into positive, negative, and neutral categories. Of the total review data, 7,801 data (79.99%) were used as training data, and 1,561 data (20.01%) were used as test data with a division ratio of 80:20 according to general standards in machine learning. The purpose of this study was to identify the dominant user sentiment and evaluate the classification performance of the SVM algorithm. The results of the experiment showed that the SVM model achieved high accuracy and was able to capture user opinions effectively, thus providing valuable input for developers in improving the quality of applications and user engagement on fintech platforms.
Hajjmate: Aplikasi Panduan Manasik Haji Mobile dengan Human-Centered Design Millati Izzatillah; Fauzan Natsir; Ega Shela Marsiani; Redo Abeputra Sihombing; Aprilia Sulistyohati
Bulletin of Information System Research Vol 4 No 1 (2025): December 2025
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/bios.v4i1.276

Abstract

Ibadah haji merupakan salah satu rukun Islam yang wajib ditunaikan bagi umat Muslim yang mampu. Namun, kompleksitas tata cara pelaksanaannya sering menjadi tantangan bagi calon jamaah, terutama bagi mereka yang baru pertama kali menunaikan ibadah ini. Metode pembelajaran konvensional seperti bimbingan tatap muka dan buku panduan terkadang kurang efektif dalam memberikan pemahaman yang mendalam. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan Hajjmate: Aplikasi Panduan Manasik Haji Mobile dengan Human-Centered Design guna memastikan bahwa aplikasi yang dikembangkan benar-benar sesuai dengan kebutuhan pengguna. Penelitian ini menggunakan metode pengembangan perangkat lunak berbasis Human-Centered Design (HCD), yang melibatkan pengguna dalam setiap tahap perancangan, mulai dari analisis kebutuhan, desain antarmuka, implementasi, hingga evaluasi. Aplikasi ini dirancang dengan fitur utama berupa panduan manasik haji berbasis audio-visual, simulasi interaktif, serta kuis evaluasi untuk menguji pemahaman pengguna. Pengujian sistem dilakukan menggunakan metode usability testing berdasarkan standar ISO 25010, guna mengukur efektivitas, efisiensi, dan tingkat kepuasan pengguna terhadap aplikasi yang dikembangkan. Hasil penelitian ini mempermudah calon jamaah dalam memahami tahapan manasik haji secara interaktif, fleksibel, dan mudah diakses dibandingkan dengan metode konvensional. Berdasarkan hasil usability testing, aplikasi ini mendapatkan tingkat kepuasan pengguna yang baik, menunjukkan bahwa pendekatan HCD berhasil menciptakan sistem yang intuitif dan sesuai dengan kebutuhan calon jamaah. Dengan demikian, implementasi aplikasi ini diharapkan dapat menjadi solusi inovatif.
e-Growth Posyandu: Transformasi Digital Monitoring Tumbuh Kembang Anak dengan Metode Human-Centered Design (HCD) Millati Izzatillah; Ega Shela Marsiani; Aprilia Sulistyohati
Bulletin of Information System Research Vol 4 No 2 (2026): April 2026
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/bios.v4i2.277

Abstract

Posyandu merupakan ujung tombak layanan Kesehatan bagi seluruh siklus kehidupan khususnya ibu dan anak di tingkat desa atau kelurahan, namun pencatatan tumbuh kembang anak masih dilakukan secara manual menggunakan buku KIA, sehingga rentan terhadap kesalahan data, keterlambatan deteksi, dan keterbatasan aksesibilitas informasi bagi orang tua. Penelitian ini bertujuan mengembangkan sistem digital berbasis web dan mobile bernama e-Growth Posyandu yang dirancang untuk memantau tumbuh kembang anak secara real-time dengan pendekatan Human-Centered Design (HCD). Metode HCD diterapkan melalui empat tahapan utama: (1) empathize, yaitu menggali kebutuhan pengguna melalui wawancara dengan kader posyandu dan orang tua; (2) define, mengidentifikasi permasalahan inti; (3) ideate, merancang solusi melalui brainstorming; (4) prototype yaitu merepresentasikan ide/konsep berupa sketsa, mockup digital; (5) test yaitu fase di mana prototype yang telah dibuat diuji langsung oleh pengguna. Fase ini bertujuan untuk menilai efektivitas, kegunaan, dan kesesuaian solusi dengan kebutuhan pengguna. Sistem e-Growth dilengkapi fitur pencatatan berat badan, tinggi badan, dan lingkar kepala anak secara digital, notifikasi jadwal posyandu, grafik pertumbuhan otomatis berbasis standar WHO, serta laporan yang dapat diunduh oleh orang tua. Pengujian dilakukan terhadap 30 kader posyandu dan 50 orang tua di tiga kelurahan di Kota Bandung. Hasil evaluasi menggunakan System Usability Scale (SUS) memperoleh skor rata-rata 82,4 yang termasuk dalam kategori "Excellent", dan 93% responden menyatakan sistem mudah digunakan. Penelitian ini menunjukkan bahwa pendekatan HCD efektif dalam menghasilkan solusi digital yang sesuai kebutuhan pengguna lapangan posyandu.
Smart Attendance System: AI Technology for Digital Attendance Using Computer Vision Technology Fauzan Natsir; Redo Abeputra Sihombing; Triana Dewi Salma; Millati Izzatillah; Ega Shela Marsiani; Farhan Maulana Arramsy; Anuj Kumar
ZETROEM Vol 8 No 1 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i1.7569

Abstract

Employee attendance is a crucial aspect of human resource management, particularly in maintaining discipline and ensuring the operational effectiveness of a company. PT KAMM currently uses a fingerprint-based attendance system which, although effective, often encounters issues such as sensor sensitivity to finger conditions, potential device damage caused by continuous physical contact, and employee inconvenience. This research aims to develop a face recognition-based attendance system as a more efficient and hygienic alternative. The dataset comprises 1,400 facial images from 20 PT KAMM employees (20 classes), split into 80% training, 10% validation, and 10% testing data. The method applied combines the Haar Cascade algorithm for face detection and a Convolutional Neural Network (CNN) for face recognition. The CNN architecture consists of four convolutional layers with 32 to 256 filters, ReLU activation, max pooling, flatten, a 512-neuron fully connected layer, dropout of 0.5, and softmax classification. The model was trained for 50 epochs using the Adam optimizer with a learning rate of 0.001 and batch size of 32. Evaluation was conducted using accuracy, precision, recall, and F1-score metrics. Results show the system achieved an accuracy of 95.71%, precision of 95.80%, recall of 95.60%, and an F1-score of 95.70%, with an average inference time of 0.12 seconds/frame in real-time. However, the system has limitations: accuracy drops by up to 12% under extreme lighting conditions and when employees wear masks. This study is expected to serve as a reference for other companies seeking to adopt similar face recognition technology for contactless attendance management systems.
Co-Authors Alqomari Cahyo Anuj Kumar Aprilia Sulistyohati Ek Ajeng Rahmi Pinahayu Farhan Maulana Arramsy Farras Raihan Rasyiq Fauzan Natsir Fauzan Natsir H. Nur Ali Hanggono Arie Prabowo Irawan Setiadi Izzatilah, Millati Karima Siti Masna Millati Izzatillah Millati Izzatillah Muhammad Bahar Mubarok Natalia Tri Astuti Natalia Triastuti Nilma Nilma Nurul Khoirunnisa Rajiansyah Rajiansyah Redo Abeputra Sihombing Redo Abeputra Sihombing Siti Suryani Triana Dewi Salma