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Journal of Artificial Intelligence and Innovative Applications (JOAIIA)
Published by Universitas Pamulang
ISSN : 27161501     EISSN : 27754057     DOI : -
Core Subject : Science,
Computer Science & IT
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 142 Documents
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PENGEMBANGAN SISTEM ABSENSI KARYAWAN BERBASIS ANDROID PADA APOTEK AINI Mulyana, Tita; Dola Irwanto
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 6 No. 4 (2025): November
Publisher : Teknik Informatika Universitas Pamulang

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Abstrak Indonesia – Penelitian ini mengembangkan sistem absensi karyawan berbasis Android pada Apotek Aini untuk mengatasi ketidakefektifan dan kerentanan pencatatan kehadiran manual. Sistem ini dirancang untuk mempermudah proses pencatatan absensi, meningkatkan akurasi data, serta mempercepat pembuatan laporan. Metode pengembangan yang digunakan adalah model Waterfall, meliputi analisis kebutuhan, desain, implementasi, pengujian, dan pemeliharaan. Aplikasi mobile dibangun menggunakan Flutter, sedangkan Laravel digunakan sebagai backend yang mengelola logika bisnis dan menyediakan API untuk integrasi dengan basis data. MySQL digunakan sebagai sistem manajemen basis data untuk penyimpanan data absensi secara terstruktur dan aman. Hasil pengujian menunjukkan bahwa sistem mampu mencatat kehadiran secara real-time, menyajikan data yang akurat, serta menghasilkan laporan kehadiran yang sistematis. Sistem ini juga meningkatkan efisiensi kerja, mengurangi potensi kesalahan pencatatan, dan mempermudah akses data bagi administrator. Pengembangan ini menjadikan proses administrasi kehadiran di Apotek Aini lebih modern, efektif, dan terintegrasi secara digital.
Implementasi Metode Advanced Encryption Standard (Aes) dalam Mengamankan Data File Soal Ujian SMK Media Informatika Berbasis Web Nur Utami, Mega; Bani
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

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The rapid development of information and communication technology has brought significant impacts, both positive and negative. One of the main challenges is data security. Organizations, educational institutions, and companies face high risks of data interception and information leaks that threaten privacy and system integrity. Although storing student exam files in softcopy form offers efficiency, weaknesses in security still pose risks of cyber-attacks such as hacking, malware, and data theft. In this context, SMK Media Informatika Jakarta places a high emphasis on the security of exam data, which is sensitive and must not be accessed before the exam schedule. Storage without adequate protection can lead to significant damage. Therefore, advanced digital security strategies are necessary. One recommended solution is the use of cryptography, specifically the Advanced Encryption Standard (AES) method. Cryptography secures data by encrypting files, making them accessible only to authorized parties. This study proposes the implementation of the AES method to secure web-based exam files at SMK Media Informatika Jakarta, providing an additional layer of protection and ensuring that sensitive information remains safe from unauthorized access, while also allowing secure and controlled access for authorized users.
Implementasi Sistem Pakar untuk Menentukan Status Gizi Balita Menggunakan Metode CBR Berbasis Website Rahmi, Najmi; i Made Sugi Ardana
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

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Studi ini berfokus pada pembangunan sistem pakar berbasis web sebagai alat bantu bagi orang tua maupun pengasuh untuk mendeteksi status gizi balita secara mandiri dan efisien. Metode yang diterapkan adalah Case-Based Reasoning (CBR). Mekanisme sistem berjalan dengan cara melakukan komparasi antara gejala pada kasus baru terhadap basis data kasus lama. Proses ini melibatkan perhitungan tingkat kemiripan (similarity) yang mengacu pada pembobotan gejala sesuai pedoman Kementerian Kesehatan serta validasi pakar di Puskesmas XYZ. Pengembangan sistem menggunakan model Expert System Development Life Cycle (ESDLC), dan diimplementasikan dengan PHP, MySQL, serta XAMPP sebagai server lokal. Hasil pengujian menggunakan Black Box Testing dan User Response menunjukkan bahwa seluruh fitur sistem berfungsi dengan baik mulai dari input gejala, proses perhitungan, hingga penentuan status gizi, dan menunjukkan bahwa sistem dinilai mudah dipahami, informatif, dan memberikan rekomendasi yang sesuai. Dengan demikian, sistem pakar ini dapat menjadi alat bantu awal yang efektif bagi masyarakat dalam mendeteksi kondisi gizi balita serta mendukung upaya peningkatan kesehatan anak.
Penerapan Metode Fuzzy Logic dalam Estimasi Waktu Produksi Konveksi Kaos Massal Azzahra Nur Oktavia; Dimas Abisono Punkastyo
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

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The process of estimating production time in the garment manufacturing industry is generally performed manually and relies on experience, making it subjective and often causing discrepancies between estimated and actual completion times. This study aims to design and develop a web-based production time estimation system by applying the Fuzzy Logic Mamdani method to provide more objective and measurable estimates. The system processes production variables such as the number of products, design complexity, number of workers, and number of design sides using the Mamdani fuzzy inference mechanism to obtain estimated production times. System testing was conducted using Black Box Testing to ensure all features function according to specifications, and accuracy evaluation was performed using Mean Absolute Percentage Error (MAPE). The results show that the system can provide production time estimates with an average MAPE of 6.73%, categorizing it as highly accurate and suitable for supporting decision-making. Therefore, this web-based system proves to assist garment manufacturers in calculating production time quickly, objectively, and accurately.
Implementasi Data Mining Dalam Pengolahan Data Simpan Pinjam Koperasi Menggunakan Metode K-Means Berbasis Website Ariffiani Khusna, Latifah; Nanang
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

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The Srikandi Savings and Loans Cooperative is a microfinance institution that plays an important role in supporting the economic needs of its members through savings and loan services. Along with the annual increase in the number of members and transactions, the cooperative still processes savings and loan transaction data manually using members’ cash books. In addition, financial report preparation is conducted through manual calculations and recapitulation, which is time-consuming and prone to calculation errors. Therefore, an effective and accurate data management system is required to improve cooperative operational efficiency. This study implements a website-based data mining approach using the K-Means clustering method to process savings and loan transaction data. The K-Means method is applied to group member transaction data based on similar characteristics, such as deposit frequency and loan amounts. The clustering results are expected to support cooperative management in decision-making processes, including determining loan limits, evaluating member loyalty, and developing strategies to improve service quality.
SPK Metode SMART untuk Penentuan Strategi Promosi pada Efraim’s Billiard Tangerang Selatan Muhammad Adli Firjatullah; Achmad Sehan
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

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Penelitian ini dilakukan karena pemilihan strategi promosi di Efraim’s Billiard Tangerang Selatan sebelumnya belum memiliki dasar penilaian yang terstruktur dan objektif, sehingga diperlukan suatu sistem yang mampu membantu pengambilan keputusan secara lebih tepat. Penelitian ini bertujuan merancang Sistem Pendukung Keputusan berbasis web menggunakan metode Simple Multi Attribute Rating Technique (SMART) untuk menentukan strategi promosi paling efektif melalui pengolahan data pelanggan dan penilaian kriteria secara sistematis. Metode penelitian meliputi observasi, wawancara, kuesioner, dan studi pustaka, sedangkan pengembangan sistem menggunakan model Waterfall yang terdiri dari analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Proses perhitungan SMART mencakup penentuan kriteria, pembobotan, pemberian skala nilai, normalisasi, perhitungan nilai akhir, dan perangkingan. Hasil penelitian menunjukkan bahwa alternatif A5 (Event Turnamen Billiard Berhadiah) memperoleh nilai tertinggi sehingga direkomendasikan sebagai strategi promosi terbaik. Sistem ini mampu meningkatkan objektivitas pengambilan keputusan dan efektivitas promosi. Temuan ini diharapkan dapat membantu pelaku usaha dalam menentukan strategi pemasaran yang lebih tepat sasaran dan berkelanjutan.
IMPLEMENTASI METODE NAIVE BAYES UNTUK KESIAPSIAGAAN BENDUNGAN ALIRAN SUNGAI BANJIR BERBASIS WEBSITE (STUDI KASUS : KALI SABI TANGERANG) Rayhan Yusuf, Rayhan Yusuf; Fifi Julfiati
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

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Banjir merupakan salah satu bencana alam yang paling sering terjadi di Indonesia dan menimbulkan dampak signifikan terhadap kehidupan masyarakat, khususnya di wilayah perkotaan seperti Kota Tangerang. Salah satu daerah yang rawan banjir adalah kawasan sekitar Bendungan Kali Sabi, di mana peningkatan debit air dan curah hujan yang tinggi sering kali menyebabkan luapan sungai. Kurangnya sistem peringatan dini berbasis data menjadi permasalahan utama yang menyebabkan masyarakat tidak siap menghadapi potensi banjir. Penelitian ini bertujuan untuk mengimplementasikan metode Naive Bayes dalam memprediksi tingkat kesiapsiagaan banjir berdasarkan data hidrologi seperti curah hujan, tinggi muka air, dan debit sungai, serta mengembangkan sistem informasi berbasis website yang dapat memberikan informasi status banjir secara cepat dan akurat. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan pendekatan Waterfall dalam pengembangan sistem. Data yang digunakan diperoleh melalui observasi lapangan, wawancara, serta studi pustaka yang relevan. Proses klasifikasi dilakukan menggunakan algoritma Naive Bayes, yang bekerja dengan menghitung probabilitas setiap kategori banjir, yaitu aman, siaga, dan bahaya. Sistem kemudian menampilkan hasil prediksi melalui antarmuka web yang dirancang responsif dan mudah diakses oleh pengguna. Hasil penelitian menunjukkan bahwa metode Naive Bayes mampu melakukan klasifikasi tingkat kesiapsiagaan banjir dengan akurasi yang tinggi berdasarkan data hidrologi yang dianalisis. Sistem berbasis web yang dikembangkan terbukti mampu menampilkan informasi prediksi banjir secara real-time, sehingga dapat digunakan oleh pihak pengelola bendungan maupun masyarakat sebagai alat bantu dalam meningkatkan kesiapsiagaan dan mitigasi
Perancangan Sistem Web untuk Hafalan Tahfidz menggunakan Metode Extreme Programming pada Pondok Pesantren Raudhatul Ulum Pranata, Angga; Savitri, Savitri
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

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The advancement of information technology has become an essential requirement for educational institutions in managing data effectively. Pondok Pesantren Raudhatul Ulum in Lebak Regency still applies a manual system for managing students’ tahfidz memorization data, which results in inaccurate records, delays in information delivery, and difficulties in data organization and reporting. This study aims to develop a web-based information system for managing tahfidz memorization data to improve efficiency and data accuracy. The system was developed using the Extreme Programming (XP) method, with testing conducted through Black Box and White Box techniques. The results indicate that the proposed system facilitates faster, more structured, and accurate processes of recording, managing, and reporting tahfidz memorization data, while reducing errors commonly found in manual systems.
Implementasi Sistem Penunjang Keputusan Untuk Destinasi Wisata Di Bogor Menggunakan Metode Collaborative Filtering dafa ramadhan, Aditya; Muhajir, Abdullah
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

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Bogor has many tourist destination options with diverse characteristics that often make tourists difficult to determine destinations according to their preferences. Therefore, a system is needed to assist tourists in making decisions effectively. This research implements a web-based Decision Support System to provide recommendations for tourist destinations in Bogor using the User-Based Collaborative Filtering method with cosine similarity. The system is developed using Python and Flask framework, analyzing similarity patterns of ratings between users to generate personal recommendations. The collaborative filtering method works by identifying users who have similar preferences, then recommending tourist destinations that are favored by users with similar preference characteristics. System performance evaluation using RMSE and MAE metrics shows a good level of prediction accuracy. This system helps tourists obtain more personalized and efficient recommendations, and can be utilized by tourism managers as a data-driven promotional tool. The implementation of this system is expected to improve tourist experience in choosing destinations and support the development of the tourism sector in Bogor
Sistem Penerjemahan Ucapan Bahasa Sunda Berbasis Web dengan Augmentasi Visual Menggunakan Convolutional Neural Network Saddad Nabbil; Yono Cahyono
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

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This research develops a web-based Sundanese speech translation system incorporating visual enhancement through Convolutional Neural Network (CNN). The primary challenge is insufficient accuracy in audio-only Automatic Speech Recognition (ASR) for low-resource languages under noisy conditions. The solution integrates fine-tuned Whisper Medium for transcription, CNN-based lip-reading, and attention-weighted audio-visual fusion. Training used OpenSLR36 Sundanese corpus with ~35,000 samples from 175,324 available instances (subset due to memory constraints). Optimization was executed on RunPod using NVIDIA RTX 4090 GPU (24GB VRAM) for 5,000 iterations (~11 hours). Results show the optimized model achieves Word Error Rate (WER) of 2.45% at optimal checkpoint (iteration 3500), improving 7.37 percentage points from baseline (9.82% at iteration 500). This performance approaches state-of-the-art by Raharjo & Zahra (2025) reporting 2.03% WER using Whisper Small. The visual module comprises three-layer CNN producing 512-dimensional features with MediaPipe facial detection. Black-box testing validates functional compliance, while responsive interface ensures cross-device compatibility. This work advances Sundanese preservation through accessible translation with competitive accuracy.

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