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Journal Of Artificial Intelligence And Software Engineering
Published by Politeknik Negeri Lhokseumawe
ISSN : 2797054X     EISSN : 2777001X     DOI : http://dx.doi.org/10.30811/jaise
Core Subject : Science,
Computer Science & IT
Artificial Intelligence Natural Language Processing Computer Vision Robotics and Navigation Systems Decision Support System Implementation of Algorithms Expert System Data Mining Enterprise Architecture Design & Management Software & Networking Engineering IoT
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 215 Documents
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Design Of Decision Support Systems Determining Priority Customers PT. XYZ with Topsis Method Web Based Mayrizkiy, Muhamad Dafhi; Mulyati, Mulyati
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6464

Abstract

The priority customer assessment process at Company XYZ has a direct influence on increasing the company's operational profits. There are problems in determining priority customers by companies resulting in reduced efficiency and the potential for financial losses due to the use of random, manual and individual opinion-based selection methods, causing significant waste of time. The aim of this research is to design a Decision Support System (DSS) based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) which can help the priority customer assessment process effectively. This system has several assessment indicators that are used to assess priority customers, namely number of orders, length of subscription, amount/nominal payment, payment history. The results of testing and system implementation show that Customer D's alternative received the highest score, namely 0.839, followed by other alternatives with appropriate assessments. With the TOPSIS method, company XYZ can make better decisions related to the weight of the criteria based on the provisions of the criteria that have been determined and can determine the weight of the criteria objectively, prioritize criteria based on customer eligibility levels, and speed up the assessment process. As a result, assessments become fairer, more accurate and in line with company expectations.
Development of Quadcopter Drone and IoT Module Technology in Geospatial-Based Air Emission Monitoring Hapsari, Anindya Ananda; Vresdian, Devan Junesco; Dionova, Brainvendra Widi; Andreansyah, Teddy
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6300

Abstract

his research introduces an innovative drone-based air quality monitoring system, equipped with multi-parameter sensors to measure temperature, humidity, CO2 concentration, and PM2.5 in real-time. The system is designed with integration to the Internet of Things (IoT), enabling direct data transmission to smart devices for instant access and quick analysis. This system provides a practical solution for monitoring air quality flexibly, especially in areas that are difficult to reach with conventional monitoring devices. Simulations showed that the drone canoperate for 4.8 to 14.77 minutes with an 80% battery depletion, depending on environmental conditions. Calibration testing of the sensors showed high accuracy, although data variations were significantly affected by temperature changes. The system underwent trial and calibration as an initial step to ensure device reliability and open opportunities for broader application development, including air quality monitoring in urban areas, industrial zones, and natural environments. The main advantage of this system lies in its ability to provide real-time data and flexibility in data collection from various locations. However, the study also identified several challenges, such as battery capacity limitations and communication range, which will be the focus of further development. Potential improvements include optimizing battery capacity, expanding communication range, and developing predictive
Fruit Image Classification Using Naive Bayes Algorithm with Histogram of Oriented Gradients (HOG) Feature Extraction Saputra, Andika Jodhi; Andriyani, Widyastuti
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6536

Abstract

A classification system using Naïve Bayes algorithm was developed to distinguish between fresh and rotten fruits, specifically apples, bananas and oranges. This research utilized a dataset consisting of 13,599 images and applied the Histogram of Oriented Gradients (HOG) technique for feature extraction, followed by model training and evaluation. The results showed that the Naïve Bayes algorithm achieved an accuracy of 87%, with the highest precision in the fresh apple class (0.9792) and the highest recall in the rotten apple class (0.9843). The rotten banana class showed a balanced performance with the highest F1-score of 0.9085. Although there were some misclassifications, especially in the rotten citrus fruit category, this study shows that image processing techniques have great potential and are reliable for assessing fruit quality based on visual characteristics.
KerjaKarya: An Inclusive Digital Solution to Expand Access for the Disabled Labour Force Mohaimin, Susetiyo; Aditya, Addin
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6429

Abstract

People with disabilities often face significant challenges in accessing the world of work due to limited inclusive information media and the stigma of low productivity. To address these issues, this research aims to develop and test the KerjaKarya application, a web-based platform specifically designed to facilitate people with disabilities, especially the physically, hearing, and speech impaired, in finding job vacancies, submitting applications, and building communities. This research uses the System Development Life Cycle (SDLC) method with a waterfall approach, involving data collection from literature studies, interviews with people with disabilities, and testing using black box techniques and user trials. The trial involved five job applicants, four companies, and one customer service with a Likert scale-based questionnaire instrument. The results showed that the application successfully met the needs of users with a friendly interface and relevant features, such as registration, application submission, and vacancy management. The implication of this research is that it provides a practical solution to improve accessibility and participation of people with disabilities in an inclusive labour market. This research also opens up opportunities for further development, such as the integration of artificial intelligence and skills training services
Android Based Wedding Organizer Service Ordering Information System Naihely, Stefanus Apriyanto; Kelen, Yoseph Pius Kurniawan; Syarifuddin, Risald
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6463

Abstract

Salon Michelle, as one of the wedding organizer service providers, is experiencing an increase in demand for wedding organizer services. The process of ordering wedding organizer services at Salon Michelle, which is still done manually, presents various challenges, such as the length of time it takes to make an order, difficulties in managing schedules, coordinating with clients, and the risk of communication errors with potential customers. Therefore, to make it easier for prospective brides and grooms to choose wedding packages available at Salon Michelle, an information system for wedding package providers is needed that provides complete information regarding the wedding packages offered by Salon Michelle vendors. By using this information system, it is hoped that customers can adjust their needs and desires to the availability of wedding facilities on offer, as well as see in detail the prices and facilities that can be obtained from Salon Michelle vendors, so that it will be very helpful in organizing wedding receptions.
Smart Lighting System Design at STMIK AMIKOM Surakarta Using Blynk Adristiawan, Ranu Arva; Widiati, Ina Sholihah; Sugiarto, Lilik
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6292

Abstract

The Internet of Things (IoT) is a technology that enables automation in human activities by connecting hardware, software, and the internet for communication and control. This study focuses on an IoT-based smart light control system designed using the Blynk app. The system utilizes the ESP8266 NodeMCU module and a 5V 8-Channel Relay as the primary components. The Blynk app is used as the controller, connecting the hardware to the user through an Android device. The research follows an experimental approach with three phases: tool design, tool construction, and tool testing. A miniature of the STMIK AMIKOM SURAKARTA environment was used as a prototype to simulate the system’s implementation. Test results show that the system operates effectively in remote control with internet coverage of up to 30 meters, achieving a 100% success rate within a range of 5–30 meters. All lights responded correctly to input commands from the Blynk app with 100% success. The monitoring system also showed stable connectivity between the app and hardware, though slight delays occurred due to internet network stability. This system is expected to serve as a practical solution for efficient management of electrical devices in educational settings, improving both energy efficiency and convenience.
Sentiment Analysis of Visitor Reviews on Google Maps at Kampung Coklat Tourism Hamdana, Elok Nur; Nur Wardani, Alifah Okta; Tri Hayati Ririd, Ariadi Retno
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6488

Abstract

Google Maps plays an important role in the tourism industry, allowing visitors to share their reviews widely. These reviews not only influence potential visitors' decisions but also impact the reputation of tourist destinations. However, evaluating service quality based on offline reviews remains suboptimal compared to online reviews, which are more accessible and interpretable. This research focuses on sentiment analysis of visitor reviews on Kampung Coklat in Blitar using the Naïve Bayes algorithm. The goal is to classify reviews into positive, neutral, or negative to understand visitors' perspectives on the tourism services. Data was collected from Google Maps and processed using the Naïve Bayes method, which has proven effective in sentiment classification even with relatively small training data sets. Experimental results showed the highest accuracy of 75% with an 80% training data and 20% testing data ratio. WordCloud analysis also depicts frequently occurring words in positive, neutral, and negative reviews, providing insights into aspects influencing tourists' experiences.
Comparison of K-Nearest Neighbor and Naive Bayes Algorithms for Tuberculosis Diagnosis Classification Setiadi, Dedi; Arif, Alfis; Oktaria, Anik
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6456

Abstract

Tuberculosis is an infectious disease caused by the bacteria mycobacterium tuberculosis. Tuberculosis is a serious global health problem and can cause death if not treated properly. At the Sidorejo Health Center, the current process of diagnosing patients uses several benchmarks of medical history obtained from patients regarding complaints, symptoms, and risk factors, while the results of the diagnosis calculation are not yet known. Comparison of the K-nearest neighbor and naïve bayes algorithms in classifying tuberculosis can provide input for the Sidorejo Health Center in seeing the accuracy of the diagnosis of tuberculosis, with medical information such as symptoms and medical history, where later patient data will be processed using the rapid miner application. The system development method used in this study is CRISP-DM, which consists of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The testing method uses a confusion matrix to measure the accuracy of the algorithm model with the results being that the K-nearest neighbor algorithm produces a high accuracy of 98% while the naïve bayes algorithm is the lowest with an accuracy of 0.70%.
Chatbot Model Design Based On Pattern Matching For Information Services About Pest Organisms In Rice Fields Larasati, Vina; Kristalina, Prima; Ningsih, Norma
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6408

Abstract

Pada dunia pertanian terutama pertanian padi, banyak ditemukan berbagai hambatan yang menyebabkan petani mengalami gagal panen.. Chatbot padiku hadir dengan fiturnya yang memberi kemudahan. Fitur yang disediakan oleh chatbot yakni 19 macam informasi tentang hama padi dan penyakit padi. Jenis informasi yang disediakan untuk hama padi berupa ciri fisik, gejala, cara pembasmian, cara berkembangbiak, kemunculan, dan gambar. Chatbot berbasis pattern matching ini didesain untuk memudahkan pengguna mengakses chatbot dengan sistemnya yang menyerupai pilihan ganda. Uji performansi website menggunakan Jmeter menunjukkan kinerja server dapat bekerja dengan baik dengan skala pengguna ≤ 300. Serta pengujian performansi menggunakan GTmetrix yang memiliki hasil performansi bagus dengan keseluruhan nilai B dan dibutuhkan waktu 3.8s untuk memunculkan konten website sepenuhnya, untuk pengujian website moda kuesioner didapatkan hasil yang memuaskan dengan nilai rata-rata vote 70%-90%, responden setuju bahwa website dan chatbot berjalan sesuai yang diharapkan. Pengujian sukses juga terjadi pada pengujian akuran sistem yang memiliki hasil sebenarnya 100% sama dengan hasil prediksi.
Systematic Literature Review on String Matching Algorithms to Analyze Research Trends Using Vosviewer Wijaya, Hartono
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6465

Abstract

String matching memiliki peran penting dalam berbagai kegunaan seperti pemrosesan teks dan analisis terutama di tengah kompleksitas data yang terus meningkat. Meskipun berbagai algoritma telah dikembangkan tantangan dalam memilih algoritma yang sesuai untuk aplikasi tertentu tetap menjadi isu yang relevan. Penelitian ini bertujuan untuk mengkaji tren penelitian dan perkembangan terbaru dalam algoritma string matching. Data penelitian dikumpulkan menggunakan Publish or Perish untuk memperoleh literatur terkait, diikuti dengan analisis bibliometrik, PRISMA, dan menggunakan VOSviewer yang meliputi tahapan identifikasi masalah, pengumpulan data, pengolahan data, dan analisis data. Hasil penelitian menunjukkan bahwa algoritma klasik seperti Knuth-Morris-Pratt dan Aho-Corasick tetap relevan terutama dalam aplikasi seperti deteksi plagiarisme dan pemrosesan teks. Tren terkini mencakup integrasi algoritma dengan teknologi machine learning dan bioinformatika, serta pengembangan algoritma hibrid yang menggabungkan metode klasik dengan teknik modern. Penelitian ini menyarankan agar dilakukan pengembangan algoritma yang lebih responsif terhadap data berubah-ubah, penelusuran aplikasi algoritma di area baru, serta analisis perbandingan antar algoritma untuk memperdalam pemahaman dan pemilihan algoritma yang paling efektif, yang dapat mendorong inovasi dan penerapan praktis dalam pengembangan algoritma string matching

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