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All Journal International Journal of Advances in Intelligent Informatics JOURNAL OF APPLIED INFORMATICS AND COMPUTING JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer The Indonesian Journal of Computer Science
Laila, Rahma
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Mechanical Engineering

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IMPLEMENTASI ALGORITMA RC4 PADA SISTEM INFORMASI KOPERASI VIRTUAL BAWASLU PROVINSI SULAWESI TENGAH VIRTUAL BAWASLU Ngemba, Hajra Rasmita; Ulhaq, Muhammad Naufal Daffa; Hendra, Syaiful; Azhar, Ryfial; Alamsyah, Alamsyah; Laila, Rahma
PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer Vol. 11 No. 1 (2024): Prosisko Vol. 11 No. 1 Maret 2024
Publisher : Pogram Studi Sistem Komputer Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/prosisko.v11i1.8182

Abstract

Koperasi merupakan hal yang penting bagi kemajuan ekonomi Indonesia yang berlandaskan kekeluargaan dan gotong royong. Perkembangan teknologi berupa internet dapat digunakan untuk mempermudah operasional koperasi, dan keamanan data di dalamnya tetap terjaga. Penelitian ini bertujuan untuk meningkatkan kualitas koperasi Bawaslu khususnya di Sulawesi Tengah, dan mempermudah menghubungkan koperasi dengan mitra serta bertujuan untuk mengamankan suatu transaksi yang dilakukan oleh karyawan dengan mitra nantinya tanpa adanya keamanan saat melakukan transaksi maka sangat berbahaya karena pihak-pihak lain yang tidak bertanggung jawab akan memanfaatkan celah keamanan tersebut sehingga dapat merugikan karyawan nantinya. Oleh karena itu penelitian ini menggunakan metode kriptografi dengan menggunakan algoritma RC4. Algoritma RC4 digunakan untuk enkripsi barcode pada saat melakukan transaksi. Jika id dari barcode telah diamankan, maka kecil kemungkinan pihak lain yang tidak bertanggung jawab dapat menggunakan barcode tersebut. Algoritma ini digunakan karena efektif, mudah diimplementasikan, dan ringan. Pengembangan sistem menggunakan bahasa pemrograman PHP dengan menggunakan framework Laravel. Pengujian sistem menggunakan Blackbox dan juga metode BIG-O. Hasil penelitian berdasarkan pengujian bahwa aplikasi dengan menggunakan Algoritma RC4 berjalan dengan baik karena proses enkripsi berhasil
Usability Analysis of The Student Service Information System at The Faculty of Engineering Tadulako University Using Heuristic Evolution and The System Usability Scale (SUS) Noviantika, Noviantika; Syahrullah, Syahrullah; Laila, Rahma; Lapatta, Nouval Trezandy; Wirdayanti, Wirdayanti
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 1 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i1.3532

Abstract

The Student Service Information System is defined as a system designed to assist students, faculty, and administration at Tadulako University's Faculty of Engineering in managing various academic aspects. This research identifies issues or obstacles users face while utilizing the website. The usability evaluation employs the Heuristic Evaluation method and the System Usability Scale (SUS). Based on the research conducted with 100 respondents, all active students at Tadulako University, the usability measurements revealed significant findings. According to the Heuristic Evaluation method, which utilizes 10 principles, areas requiring improvement were identified in qualifications B1.2, B3.3, B8.2, B10.2, and B10.3. Recommendations for enhancements include adding a notification feature, ensuring the search function is easily discoverable, selecting appropriate color combinations, and improving the placement of the user guide. The System Usability Scale yielded a score of 50, categorizing the website as "OK" on the adjective scale, "D" on the grade scale, and "Marginal" on the acceptability scale, with a net promoter score indicating a "Passive" reception.
a PREDIKSI SISWA PUTUS SEKOLAH DAN KEBERHASILAN AKADEMIK MENGGUNAKAN MACHINE LEARNING: Prediksi Siswa Putus Sekolah dan Keberhasilan Akademik Fitriana, Siti; riniyanty; laila, rahma; pratama, septiano anggun; lamasitudju, chairunnisa ar
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4453

Abstract

In 2020-2023. The issue of high school dropouts at SMA Negeri 2 Sigi increased, causing impacts such as declining school accreditation, a decrease in the number of students, and operational aid. This research aims to build an early prediction system for student dropouts using Machine Learning (ML). In this study, data from 200 students were used. With 16 students labeled as dropout. The results showed a model accuracy of 0.942 and an area under the curve (AUC) of 0.948. the factors most influencing student droppout are average grades, meeting targets, and father’s education leve.
RANCANG BANGUN SISTEM INFORMASI DIREKTORAT SAMAPTA POLDA MENGGUNAKAN ALGORTIMA RC4 BERBASIS WEBSITE Harani, Makruf; Lamasitudju, Chairunnisa Ar; Angreni, Dwi Shinta; Azhar, Ryfial; Laila, Rahma; Miftah, Miftah
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6312

Abstract

sistem informasi kepegawaian adalah untuk data menangani kepegawaian, hal ini sangatlah penting mengingat kebutuhan akan ada data peningkatan dan informasi. Saat ini Direktorat Samapta Polda Sulteng masih mengolah data personel terutama dengan manual, termasuk pengolahan data dan penyimpanan informasi. File sangat penting untuk menjaga data kerahasia, terutama untuk dokumen yang isinya hanya dapat diakses oleh individu yang berwenang. Tanpa tindakan pencegahan keaman, kerahasia dan intersepsi akan terancam menjadi penghambat produktivitas pekerja. Demi menjaga kerahasiaan berkas dokumen yang merupakan aset berharga Direktorat Samapta Polda Sulteng, RC4 dalam penelitian ini dimanfaatkan untuk membantu pengarsipan data dan data perlindungan. Pengujian keberhasilan sistem menggunakan Delone Dan Mclean ADALAH Model Sukses menunjukan bahwa pengguna puas dengan sistem informasi pegawai ditsamapta polda provinsi Sulawesi Tengah Menggunakan RC4 beserta kualitas informasi yang disajikan.
Optimization of Inventory Management with QR Code Integration and Sequential Search Algorithm: A Case Study in a Regional Revenue Office Fajar, Moh; Azhar, Ryfial; Anshori, Yusuf; Laila, Rahma; ., Rinianty; Lapatta, Nouval Trezandy
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8919

Abstract

Inventory management at a government office was previously conducted manually, leading to issues such as data inaccuracies, delays in item searches, and low work efficiency. This study develops a web-based inventory management system integrated with QR Code technology and a sequential search algorithm to address these challenges. The system was developed using the prototyping method, with iterative design based on user feedback until the final version met the office's operational needs. Key features of the system include digital inventory recording, item tracking using QR Codes, and real-time information access through a web-based interface. The system was tested in two stages: simulation and direct implementation in a real-world environment, involving 10 respondents to evaluate effectiveness and usability. The test results showed a 95% improvement in data recording accuracy, a 60% reduction in item search time, and an average user satisfaction score of 77.25 based on the System Usability Scale (SUS). This research successfully improved inventory management efficiency and demonstrated the system’s potential for adoption by other similar organizations, with modular adjustments tailored to their needs.
CNN Algorithm for Herbal Leaf Classification Using MobileNetV2 and ResNet50V2 Pagiu, Harry T.; Kasim, Anita Ahmad; Lapatta, Nouval Trezandy; Pratama, Septiano Anggun; Laila, Rahma
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 2 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i2.3776

Abstract

Indonesia is home to over 30,000 types of herbal plants, with approximately 1,200 species utilized as raw materials for alternative and traditional medicine. Leaves play a crucial role in herbal medicine preparation. However, many people struggle to identify different herbal leaves due to their similar appearances, making classification difficult. Each leaf possesses unique characteristics such as shape, size, midrib, stalk, blade, and type, which can be used for differentiation. To assist in identifying herbal leaves, a classification system based on image recognition is essential. Convolutional Neural Networks (CNN) are deep learning algorithms designed for processing two-dimensional image data. Model performance can be enhanced through transfer learning, with MobileNetV2 and ResNet50V2 being widely used architectures. These pretrained models have been trained to recognize images with high accuracy. This study focuses on classifying herbal plants based on leaf shape using CNN architectures from MobileNetV2 and ResNet50V2. The evaluation results show that the MobileNetV2 architecture, with a 90%:10% data split, achieved an accuracy of 98.51%, precision of 98.92%, recall of 98.51%, and an F1-score of 98.56%. These findings indicate that CNN with transfer learning can effectively classify herbal leaves with high accuracy.
UI/UX Design of Jepun Bali Store Product Ordering Application Using Design Thinking Method Widiani, Ni Nengah; Syahrullah, Syahrullah; Laila, Rahma; Lamasitudju, Chairunnisa Ar; Angreni, Dwi Shinta
CCIT (Creative Communication and Innovative Technology) Journal Vol 19 No 1 (2026): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v19i1.3965

Abstract

The internet as a form of technological advancement continues to develop every year and has a great influence on human activities, including in terms of sales. The Jepun Bali Store, which sells products typical of Hinduism and Balinese customs, markets its products online with Instagram, Facebook, and WhatsApp. Instagram and Facebook are used to display the catalog, while WhatsApp is used for order communication. However, this system is considered less efficient because customers have to switch applications to view products, ask questions, and order. Stock and price information is not available in real-time, and the ordering process is still done manually, making it difficult for customers. From the manager's side, manual order recording risks creating errors, while admins are often overwhelmed with handling queries across multiple platforms, which impacts customer satisfaction. This research aims to simplify the transaction process, speed up services, and increase efficiency by applying the Design Thinking method. This method helps in understanding the needs of the user, structuring problems, and producing solutions through systematic stages. The results of the design test using the System Usability Scale (SUS) method with 30 respondents obtained a score of 88.5833 out of 100, included in category A (Excellent) and considered acceptable.
IMPLEMENTASI PEMBOBOTAN TF-IDF PADA CHATBOT TELEGRAM UNTUK SISTEM LAYANAN INFORMASI Maulana, Muhammad Syahputra; Anshori, Yusuf; Azhar, Ryfial; Laila, Rahma; Lapatta, Nouval Trezandy
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6314

Abstract

Chatbot populer dalam interaksi manusia-mesin dan efektif dalam layanan pelanggan, bantuan pengguna, dan pengelolaan informasi. Pengembangannya meliputi pengumpulan data pertanyaan, pem-rosesan teks, dan penerapan algoritma TF-IDF untuk mengekstrak in-formasi relevan dari dataset. Penelitian ini mengkaji penerapan algo-ritma TF-IDF pada chatbot Telegram menggunakan dataset yang terdiri dari 94 dokumen dan 300 data uji. Hasil penelitian menunjuk-kan bahwa algoritma TF-IDF menghasilkan 268 respons yang relevan dan akurat, 12 respons yang tidak relevan namun tetap diberikan, dan 32 respons yang seharusnya relevan tetapi tidak ditemukan. Penggunaan algoritma TF-IDF, yang memberikan pembobotan pada kata-kata berdasarkan pentingnya dalam dokumen, menunjukkan akurasi yang cukup baik. Hasil ini didukung oleh pengujian relevansi menggunakan metrik umum dalam bidang information retrieval, yang menghasilkan nilai precision sebesar 95,71%, recall sebesar 89,33%, dan F1-Score sebesar 92,4%. Dengan nilai-nilai tersebut, kinerja chat-bot Telegram dinilai sangat baik dalam memberikan respons.
PENERAPAN CONVOLUTION NEURAL NETWORK (CNN) UNTUK DETEKSI MEGALITIKUM DI SULAWESI TENGAH BERBASIS MOBILE Fahmi, Moh.; Laila, Rahma; Pusadan, Mohammad Yazdi; Syahrullah, Syahrullah; Azhar, Ryfial; Sani, Ilham Abdillah; Magfirah, Magfirah
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6458

Abstract

Taman Nasional Lore Lindu di Sulawesi Tengah, Indonesia, memiliki berbagai objek megalitikum, termasuk arca, kalamba, lumpang, dan batu dulang. Kawasan ini memiliki potensi untuk secara resmi diakui sebagai Situs Warisan Dunia, namun pengguna masih menghadapi tantangan dalam mengidentifikasi dan memahami artefak megalitikum ini. Sebagai tanggapan atas masalah ini, penelitian ini telah menciptakan sistem atau aplikasi yang menggunakan algoritma CNN (Convolutional Neural Network) dengan platform Teachable Machine untuk meningkatkan kemampuan pengguna dalam mengidentifikasi objek megalitikum. Program ini akan menawarkan informasi yang lebih luas untuk setiap objek megalitikum, termasuk penggunaan yang dimaksudkan dan konteks sejarahnya. Temuan uji menunjukkan bahwa program ini memiliki kemampuan untuk mengidentifikasi objek megalitikum dengan tingkat akurasi hingga 98%. Selain itu, pengguna dapat dengan mudah mengakses informasi yang lebih komprehensif tentang artefak-artefak ini. Program ini memungkinkan pengguna untuk dengan mudah mengidentifikasi dan memahami objek megalitikum, sambil juga memberikan mereka informasi yang lebih mendalam tentang artefak-artefak tersebut.
Pattern recognition for facial expression detection using convolution neural networks Pusadan, Mohammad Yazdi; Sasuwuk, James Rio; Pratama, Septiano Anggun; Laila, Rahma
International Journal of Advances in Intelligent Informatics Vol 11, No 4 (2025): November 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i1.1602

Abstract

The COVID-19 pandemic was a devastating disaster for humanity worldwide. All aspects of life were disrupted, including daily activities and education. The education sector faced significant challenges at all levels, from kindergarten to elementary, junior high, and high school, as well as in higher education, where learning had to be online. Human emotions are primarily conveyed through facial expressions resulting from facial muscle movements. Facial expressions serve as a form of nonverbal communication, reflecting a person’s thoughts and emotions. This research aims to classify emotions based on facial expressions using the Convolutional Neural Network (CNN) and detect faces using the Viola-Jones method in video recordings of online meetings. We utilize the VGG-16 architecture, which consists of 16 layers, including convolutional layers with the ReLU activation function and pooling layers, specifically max pooling. The fully connected layer also employs the ReLU activation function, while the output layer uses the Softmax. The Viola-Jones method is used for facial detection in images, achieving an accuracy of 87.6% in locating faces. Meanwhile, the CNN method is applied for facial expression recognition, with an accuracy of 59.8% in classifying emotions.
Co-Authors Alamsyah - Anita Ahmad Kasim Chairunnisa Ar. Lamasitudju Dwi Shinta Angreni Fahmi, Moh. Fajar, Moh Hajra Rasmita Ngemba Harani, Makruf Magfirah, Magfirah Maulana, Muhammad Syahputra Miftah Miftah, Miftah Mohammad Yazdi Pusadan Nouval Trezandy Lapatta Noviantika, Noviantika Pagiu, Harry T. Pratama, Septiano Anggun Rinianty, Rinianty Ryfial Azhar, Ryfial Sani, Ilham Abdillah Sasuwuk, James Rio Siti Fitriana Syahrullah Syahrullah Syaiful Hendra Ulhaq, Muhammad Naufal Daffa Widiani, Ni Nengah Wirdayanti Yusuf Anshori