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Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Published by Yayasan Kita Menulis
ISSN : -     EISSN : 28084519     DOI : https://doi.org/10.53842/jaiea.v1i1
Core Subject : Science, Engineering,
Automotive Engineering Computer Science & IT Control & Systems Engineering
The Journal of Artificial Intelligence and Engineering Applications (JAIEA) is a peer-reviewed journal. The JAIEA welcomes papers on broad aspects of Artificial Intelligence and Engineering which is an always hot topic to study, but not limited to, cognition and AI applications, engineering applications, mechatronic engineering, medical engineering, chemical engineering, civil engineering, industrial engineering, energy engineering, manufacturing engineering, mechanical engineering, applied sciences, AI and Human Sciences, AI and education, AI and robotics, automated reasoning and inference, case-based reasoning, computer vision, constraint processing, heuristic search, machine learning, multi-agent systems, and natural language processing. Publications in this journal produce reports that can solve problems based on intelligence, which can be proven to be more effective.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 430 Documents
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Design and Implementation of Gereja Kristen Sumba Jemaat Wulla Financial Management Information System Atahau, Fonensia Djati; Hariadi, Fajar; Talakua, Alfrian Carmen
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.540

Abstract

Gereja Kristen Sumba Jemaat Wulla merupakan gereja yang berada di bawah naungan Sinode Gereja Kristen Sumba yang berdiri pada tanggal 4 November 2015 dan memiliki struktur Badan Pekerja Majelis Jemaat (BPMJ) yang dikelola oleh Pdt. Ina Margaretha, S.Th sebagai ketua dan dibantu oleh Yuliana Atakuni (wakil), Rina Ana Wulang (sekretaris), dan Amelia Lima (bendahara). Sebagai lembaga yang mengelola keuangan yang dihimpun secara sukarela dari masyarakat, diperlukan akuntabilitas dan transparansi dalam administrasi dan pengelolaannya. Permasalahan di Gereja Kristen Sumba Jemaat Wulla cukup kompleks karena pengelolaan data keuangan masih tercatat dalam buku yang menyebabkan proses pengelolaan membutuhkan waktu lama, tidak tercatat dengan baik, serta ada kemungkinan buku rusak atau hilang, penilaian tidak akurat, dan sering terjadi kesalahan pada saat merekapitulasi data. Dalam membangun sistem ini digunakan metode Waterfall yang mana terdapat tahapan-tahapan antara lain Analisis Persyaratan, Perancangan Sistem, Penulisan Kode Program, Pengujian Program, Implementasi dan Pemeliharaan Program. Dari pengujian menggunakan System Usability Scale (SUS) diperoleh hasil skor 85, yang menunjukkan bahwa sistem informasi manajemen keuangan yang dibuat layak untuk digunakan dengan rentang tingkat penerimaan “Acceptable” dan rentang tingkat penerimaan “High”. Dengan skala nilai berada pada kelas “B”, maka penilaian kata sifat “Excellent”. Hasil tersebut menunjukkan bahwa sistem informasi manajemen keuangan gereja dapat diterima oleh para penggunanya. Sistem ini dapat memudahkan bendahara gereja dalam melakukan pendataan dan meningkatkan keakuratan data pendapatan dan pengeluaran gereja.
Clustering of Student Expertise Fields Using the K-Means Algorithm (Case Study: STMIK Kaputama Binjai) Aulia, Damai Aulia Br Karo; Maulita, Yani; Prahmana, I Gusti
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.541

Abstract

Grouping students' fields of expertise in higher education is an important issue that can provide significant benefits for students and educational institutions. STMIK Kaputama is one of the universities that has students with various fields of expertise, but the absence of data that informs the field of expertise of students is very unfortunate. Research data was obtained through questionnaires distributed to students, which included information about study programs, Grade Point Average (GPA), and areas of expertise. Clustering analysis was conducted using Matlab software to validate and implement the clustering results. The results show that the K-Means algorithm is effective in grouping students into clusters that have similar characteristics. The first cluster consists of students with expertise in programming and database, the second cluster focuses on students with networking expertise, and the third cluster includes students with various combinations of expertise.This study also found a tendency that students with certain expertise have a higher GPA than students with other expertise.
Design and Development of a Prototype Water Level Control System for Early Flood Detection Based on The Internet of Things: a Case Study of Kambaniru Dam Manutede, Imaniaro; Pingky Alfa Ray Leo Lede; Hawu Yogia Pradana Uly
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.542

Abstract

Flooding can occur due to overflowing water during the rainy season, therefore early detection of the water level in dams as water runoff processing structures is needed. When heavy rain occurs it can result in flood disasters that are detrimental to communities, dam infrastructure and agricultural land. This research aims to monitor water levels online as initial information about impending flood disasters. Monitoring using Internet of Things (IoT) based technology is intended to obtain water level information in real time. In this device the HC-SR04 ultrasonic sensor is used as a water level reader, a waterflow sensor as a water discharge reader and a servo motor as a sluice gate controller. The results of this research are a prototype of a water level detection device that can provide water level information and can control sluice gates. automatically and can be controlled manually or remotely via the latest notifications in the Blynk application using the MQTT protocol. This research was carried out by taking information based on the results of direct observations and interviews with officers at Kambaniru Dam, Lambanapu Village, Kambera District. In this way, the prototype of this detection tool will be easy to use as initial information about the possibility of flooding.
Classification Of Students Based On Factors That Affect Student Learning Achievement Using The K-Means Clustering Algorithm (Case Study: STMIK Kaputama Binjai) Dea, Dea Puspita; Buaton, Relita; Khair, Husnul
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.546

Abstract

In the world of education, students are the main object of every educational implementation that always prioritizes disciplines that are beneficial to the students themselves. However, in lecture activities there are students who are diligent in participating in lecture activities and there are also those who rarely participate in lecture activities, this can be caused by internal and external factors, so that there can be significant variations in student learning achievements, with some achieving high grades, while others face difficulties in achieving the same achievements. Based on the description of the problem, the researcher conducted a study that aimed to group students based on factors that affect student learning achievement using the k-means clustering algorithm. The results of the research conducted produced 3 clusters with cluster 1 there were 5 data, the group of students with a very satisfactory predicate GPA (3.50-4.00), supported by both internal and external factors (interval 3.1-4). Cluster 2 has 3 data, the group of students with a satisfactory predicate GPA (3.00-3.49), supported by both internal and external factors (interval 2.1-3), and cluster 3 has 5 data, the group of students with a satisfactory predicate GPA (3.00-3.49), supported by both internal and external factors (interval 3.1-4).
Development of the Dukcapil Application In Setia Mekar Village Mubarok, Ahmad Syahrul; Farhan, Dhia; Satria, Rian; Pamungkas, R Wisnu Prio
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.551

Abstract

Technology will develop more and more every year. Many things currently use technology from various aspects, including general elections for government institutions in Indonesia. Data collection on general election participants in Indonesia is still relatively slow because data collection is still used manually and handwritten. The creation of this data collection system involved village government agencies including population administration and civil registration services (Dukcapil). This article discusses the design of the Dukcapil election application in Setiamekar Village which aims to simplify the administrative process and increase the efficiency of public services. The methods used in this design include needs analysis, system design, implementation and evaluation. The research results show that this application can help speed up the administration process, reduce manual errors, and increase public satisfaction.
Design Of a Web-Based School Operational Assistance (Bos) Management Information System at SMA Negeri 1 Nggaha Ori Angu Melda Kareri Hara; Yustina Rada; Erwianta Gustial Radjah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.553

Abstract

The management of School Operational Assistance (BOS) funds is an annual obligation for educational institutions. The Treasurer is responsible for this activity, which is overseen by the Principal. However, at SMA Negeri 1 Nggaha Ori Angu, the School Operational Assistance (BOS) fund management system is still conducted using a physical ledger. This process has encountered several challenges, including the difficulty in calculating the total funds managed and the lack of efficiency in managing the School Operational Assistance (BOS) funds. The process of utilising the ledger currently results in the unnecessary expenditure of time and effort, in addition to a considerable risk of errors and inaccuracies in the recorded data. In light of the challenges encountered in the management of School Operational Assistance (BOS) funds at SMA Negeri 1 Nggaha Ori Angu, this research aims to develop an Information System for the Management of School Operational Assistance Funds (BOS) using the Rapid Application Development (RAD) method. The web development in this research will employ the Hypertext Preprocessor (PHP) programming language with the CodeIgniter framework, which implements the Model-View-Control (MVC) concept. This technology has the potential to optimize and enhance the quality of School Operational Assistance (BOS) fund management at SMA Negeri 1 Nggaha Ori Angu.
Optimizing the Preparation of Work Plans Using Linear Regression Astrika, Rahayu; Pardede, Akim Manaor Hara; Sihombing, Anton
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.555

Abstract

Preparing effective and efficient work plans to achieve regional government strategic goals is often faced with budget management challenges, especially in the face of increasing indicative ceilings. This research optimizes this process at the Langkat Regency Regional Secretariat using the linear regression method. This method evaluates previous work plans and adapts them to regional financial capabilities for more efficient budget use. The research results show that linear regression provides accurate predictions of budget needs, with an error rate (MAPE) of 0.08% and an accuracy rate of 99.92%. It is hoped that this optimization can support regional development goals in a structured and measurable manner.
Educational Game Introducing Cells in Animals and Plants Based on Android Using the Linear Congruential Generator Algorithm Ina, Anggri Hada; Lede, Pingky Alfa Ray Leo; Mira, Trisari Dewi Novyanti B
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.558

Abstract

In the world of education, science lessons have been taught since elementary school. However, material related to the introduction of animal and plant cells is only given at the junior high school level. State Junior High School 2 Kanatang, East Sumba is one of the secondary schools that provides introductory material to animal and plant cells for class VIII students. In teaching and learning activities, the delivery of material by teachers still uses limited teaching materials, which results in students not understanding the material related to the introduction of animal cells and plant cells. This is proven based on data on student scores for learning material on animal cells and plant cells. Student scores are still below average. flat. For this reason, an educational game about the introduction of cells in animals and plants was created to help students learn science. The method used in this research is the Multimedia Development Life Cycle (MDLC) method. In making the application, the Linear Congruential Generator algorithm was applied to randomize the practice questions in the educational game application for introducing cells in animals and plants. The aim of this research is to produce an educational game for recognizing cells in animals and plants which is able to improve students' ability to remember the cells in animals and plants at SMP N 2 Kanatang, East Sumba. The tools used to build this application are Unity.
Enhancing SQL Injection Attack Detection Using Naïve Bayes and SMOTE Method on Imbalanced Datasets Arnap, Adam; Kusrini
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.559

Abstract

SQL injection attack detection is a crucial aspect of cybersecurity, considering the potential damage that such attacks can cause. This study aims to evaluate the effectiveness of the Naive Bayes model in detecting SQL injection attacks on an imbalanced dataset. To address the data imbalance issue, the SMOTE (Synthetic Minority Over-sampling Technique) method was applied. The study consists of two phases: first, training and testing the Naive Bayes model on the original dataset without SMOTE, and second, training and testing on the dataset with SMOTE applied. The results indicate that the Naive Bayes model on the dataset without SMOTE achieved an accuracy of 0.9948, F1 Score of 0.9885, Precision of 0.9906, and Recall of 0.9946. After applying SMOTE, the model's performance improved significantly, with an accuracy of 0.9950, F1 Score of 0.9950, Precision of 0.9950, and Recall of 0.9950. This improvement suggests that SMOTE effectively enhanced class balance in the dataset, improving the model's ability to detect both malicious and safe queries. The study recommends exploring other resampling methods, feature engineering analysis, and testing on more diverse datasets as well as implementation in real-world environments for future research.
Analysis of Two Translation Applications : Why is DeepL Translate more accurate than Google Translate? Telaumbanua, Yasminar Amaerita; Marpaung, Angelin; Gulo, Ceria Putri Damai; Waruwu, Dodi Kardo Wijaya; Zalukhu, Erika; Zai, Novita Purnawirati
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.560

Abstract

DeepL Translate and Google Translate are two leading machine translation tools. The focus of this research is to analyze the accuracy of translation results provided by DeepL Translation and Google Translation specifically in translating English to Indonesian. This research used a qualitative approach of document analysis and interviews. The advanced neural machine translation technology of DeepL, by utilizing extensive data, enables it to recognize language nuances and provide contextually accurate translations. In contrast, Google Translate, despite having grown to be supported by hundreds of languages, often struggles with complex sentences and idiomatic expressions. DeepL's accuracy and natural-sounding translations make it a top choice for professional and detailed translations. The study concludes that DeepL's focus on quality and accuracy, rather than the breadth of language support, makes it a more reliable translation tool.

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