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All Journal Jurnal Media Infotama METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Jurnal Abdi Ilmu Majalah Ilmiah Kaputama JTIK (Jurnal Teknik Informatika Kaputama) KAKIFIKOM : Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer MEANS (Media Informasi Analisa dan Sistem) Syntax: Journal of Software Engineering, Computer Science and Information Technology Journal Of Information And Technology Unimor (JITU) Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Jurnal Widya Bulletin of Multi-Disciplinary Science and Applied Technology Journal of Computer Science and Informatics Engineering Journal of Artificial Intelligence and Engineering Applications (JAIEA) International Journal of Informatics, Economics, Management and Science Journal of Engineering, Technology and Computing (JETCom) Journal of Mathematics and Technology (MATECH) Jurnal Pengabdian Pada Masyarakat METHABDI International Journal of Health, Engineering and Technology Jurnal Penelitian Sistem Informasi Indonesian Journal of Education And Computer Science Indonesian Journal of Science, Technology, and Humanities Nusantara Journal of Multidisciplinary Science Jurnal Penelitian Teknologi Informasi dan Sains Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Modem : Jurnal Informatika dan Sains Teknologi Repeater: Publikasi Teknik Informatika dan Jaringan Switch: Jurnal Sains dan Teknologi Informasi Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Saturnus: Jurnal Teknologi dan Sistem Informasi Pascal: Journal of Computer Science and Informatics
Yani Maulita
STMIK Kaputama
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Journal : Journal of Artificial Intelligence and Engineering Applications (JAIEA)

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Use of Case Based Reasoning (CBR) Methods to Diagnosis Diseases in Pregnancy Fadilah, Nurul Elsa; Yani Maulita; Husnul Khair
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.292

Abstract

Diseases in pregnant women are diseases that many people need to pay attention to, because diseases that occur in pregnant women will not only endanger one life, but more than that. Hypertension currently occupies the 2nd position as a type of disease that threatens the lives of many pregnant women. The application of Case Based Reasoning (CBR) in diagnosing diseases that occur during pregnancy is motivated by the difficulty of consulting an obstetrician due to costs, time or even the limited number of doctors in a hospital. The use of CBR aims to solve new problems by adapting solutions to problems that occurred before. The expert system itself is one of the solutions to solve problems faced by users in the health sector, this system can minimize costs incurred to consult about diseases in pregnancy to specialist doctors. "Use of Case Base Reasoning (CBR) to Diagnose Diseases in Pregnancy" is expected to help the general public, especially pregnant women, make a simple diagnosis of symptoms and diseases in pregnancy.
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.
Rivest Shamir Adleman (RSA) Super Encryption Algorithm with Vigenere Cipher Algorithm Modification for Image Security Mariza; , Achmad Fauzi; Yani Maulita
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.v4i1.581

Abstract

The development of information technology makes information easy to transfer and transmit digital media such as images and videos, but also brings security risks to data that is vulnerable to being infiltrated by irresponsible parties. Digital image security is a major concern in areas such as design security, medical science and architecture. Cryptography is a solution for protecting digital images, where encryption and decryption are the core. This research proposes a double encryption algorithm that combines Rivest Shamir Adleman (RSA) and Vigenere Cipher. The RSA algorithm, as the leading asymmetric cryptography algorithm, is used to secure the Vigenere key, which is then used to encrypt the image. This approach provides multiple layers of security, making attacks on images more difficult. The aim of this research is to analyze and implement the RSA algorithm with the Vigenere Cipher modification in digital image encryption, as well as evaluating the effectiveness, security and efficiency of the algorithm. The results show the success of this approach in protecting digital images from data attacks and hacking, although there is still room for improvement. In addition, this algorithm provides security without sacrificing the quality of the digital image. This research contributes to the development of digital image security methods, which are important in today's information age. By using this dual encryption approach, this research provides a solution that can be applied in a variety of contexts, maintaining the security and integrity of digital data in the face of increasingly complex threats.
Design of an Automatic Trash Can Wheel Robot with Bluetooth Navigation Control Through Smartphone Application Irfan Yusuf; Yani Maulita; Saragih, Rusmin
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.v4i1.631

Abstract

Environmental cleanliness is an important aspect that must be maintained, especially in this modern era. The use of appropriate technology can help increase awareness of cleanliness, one of which is by developing automatic trash cans. This research designs and builds a mobile robot in the form of an automatic trash can that can be controlled via an Arduino Uno microcontroller using Bluetooth and controlled via a smartphone application. This research designs a mobile robot in the form of an automatic trash can that can be controlled via an Arduino Uno microcontroller with Bluetooth and a smartphone application. The system receives navigation commands from the app and uses ultrasonic sensors to detect objects in front of the trash can. The microcontroller processes the command and sensor data to drive the DC motor and servo motor. The servo motor opens and closes the trash can lid automatically when an object is detected at a certain distance. The test results show that this robot can move according to instructions from a smartphone and successfully open and close the trash can lid automatically when detecting objects.
Clustering Students Level of Understanding of Programming Language Courses Using the K-Means Algorithm Ramadana, Noval; Yani Maulita; Sembiring, Hermansyah
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.v4i1.650

Abstract

This study aims to categorize students based on their level of understanding of programming language courses using the K-Means algorithm. Students often experience difficulties in understanding the basic concepts of programming languages, which can affect their ability to solve programming problems. Using data obtained from questionnaires filled out by STMIK Kaputama Binjai students, this study analyzed variables such as attendance rate, learning interest, and level of understanding. The analysis results show the existence of patterns and relationships between these variables, which can be used to identify groups of students who have a good, poor, or no understanding of the course. This research is expected to provide input for educational institutions in designing learning strategies that are more effective and attractive to students.
Data Mining Predicts the Number of Scout Enthusiasts in Binjai City Using the Linear Regression Method Rahmat Ramadhan; Yani Maulita; 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.v4i1.651

Abstract

This study aims to predict the number of scout enthusiasts in Binjai City using a linear regression method. The data used includes the number of active scout members from the Alert, Fundraiser, and Enforcer levels during the 2018-2024 school year. The linear regression method was chosen because of its ability to predict future trends based on historical data. This research implements a linear regression algorithm through the Python programming language for the development of prediction systems. The problem in this study is that scout education in Binjai City has many impacts that can affect the number of scout enthusiasts in an educational institution. Some of the factors that can affect the quality of the teacher can be a determining factor in the interest in participating in scouting. With the existence of qualified scout teaching staff and creativity, students will be more in demand to participate in scouting.and the achievement of providing facilities provided from the School Level to the Branch Committee can also be a factor in attracting interest in participating in scouting and the support of school principals and the surrounding government can also be a determining factor in the development of scouting in the region so that activities from the school level to the international level are carried out which will be more in demand by scouting students. This finding is expected to help the Branch of the Binjai City Scout Movement in preparing and optimizing the number of scouting students in the future. This value means that the relationship between the free variable / predictor X and the bound variable / response Y is a low increase, the percentage is 93%. With the overall interest of 3191 scout members active scout members in the coming year with the number of Standby (1756 people), Fundraisers (662 people), Enforcers (773 people) So, the interest of scouts in the city of Binjai is influenced by the number of active Scout members this year.
Decision Support System for Extracurricular Determination to Increase Student Involvement in Activities Outside the Classroom Using the AHP Method Rizky Ramadhan; Yani Maulita; Br Sitepu, Kristina Annatasia
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.v4i1.664

Abstract

SMK Dharma Pancasila Medan is a private school located at Jl. Dr. T. Mansyur No.71 C Medan, Kel. PB Selayang. Currently, the selection of extracurricular activities at the school relies on a conventional manual system, lacking a formal system to identify the best extracurricular activities among the available options. This study aims to develop a Decision Support System (DSS) using the Analytical Hierarchy Process (AHP) method to evaluate and prioritize extracurricular activities based on four main criteria: achievement, short-distance running, height, and discipline. The system is designed to provide objective and measurable recommendations, facilitating students in choosing the most suitable extracurricular activities to enhance their success in out-of-class activities. The research findings demonstrate that the DSS developed with the AHP method is effective in providing accurate recommendations and increasing student engagement in extracurricular activities. The analysis and assessment process using AHP results in more targeted decisions aligned with the goal of enhancing student involvement. Overall, the system not only aids students in optimal extracurricular selection but also contributes to the development of better extracurricular activity strategies at SMK Dharma Pancasila Medan. This research enriches educational theory and practice by offering practical solutions to the challenges in extracurricular selection and enhances the overall educational experience for students.
Identification of Longan Species Based on Leaf Shape Texture and Color Using KNN Classification Lubis, Setia Adiyasa; Maulita, Yani; Syari, Mili Alfhi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.238

Abstract

This study aims to identify the type of longan based on the shape, texture and color of the leaves using KNN classification. With a method that can identify the type of longan automatically, farmers and researchers can obtain information more quickly and accurately about the type of longan that is being cultivated or studied. This can help in choosing the right variety, more efficient maintenance, and improve the quality and productivity of longan plants. This research is an experimental research consisting of eight steps, namely preparation, theoretical studies, data collection, data analysis and processing, testing and implementation and the last is the final stage. Based on research conducted at UD Mitra Tani on Jalan Madura No. 81 Kebun Lada, Kec. Binjai Utara, Binjai City, North Sumatra, the results of data analysis from longan leaves show that the most common type of longan found in the nursery is Red longan. This study was conducted to identify the dominant longan species in the population and gain a deeper understanding of the diversity of longan varieties in the region.
Classification Of Population Data On Status In The Family Based On Last Education And Work Using The Clustering Method (Case Study: Sei Prison Village Office) Ningsih, Fauziah; Maulita, Yani; Sihombing, Marto
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.264

Abstract

Population data is structured individual or individual data through population registration, civil registration and population census activities. It is important to know population data because in making policies and planning regional or state development, population data is needed to describe the condition of an area. Population data include births, deaths, transfers or migration, population composition, population density and so on. This grouping is done so that population data that is already in the archives will be input into an application that will be designed to make it easier for parties who need data without having to look at the data that is still manual. The problems that exist are such as the increase in the number of residents in a city, village or even a district which is increasing while the population that has been recorded still does not have a job, such as status in the family, namely the head of the family is still there who does not work in terms of recent education can still be considered to get a job that matches the last type of education. From the research process conducted on 20 data, 3 groups were obtained, Cluster 1 contained 16 data, Cluster 2 contained 1 data, and Cluster 3 contained 3 data. And the most group obtained is cluster 1, there is education last high school, has a type of work that has not worked and status in the family of the head of the family.
Diagnosis of Parasitic Diseases in Animals Cat Using Bayes Theorem Method Khairunisa, Salsabila; Maulita, Yani; Simanjuntak, Magdalena
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.265

Abstract

Cats are one of the most popular pets in the world, including Indonesian people who like to keep cats as pets, and even become a hobby for cat lovers. Diseases that often attack cats are caused by parasites, namely worms and fleas. Parasites that attack cats are grouped into two, namely ectoparasites and endoparasites. expert system which is a computer program , which is able to store knowledge and rules like an expert . With the help of an expert system, someone who is lay or not an expert in a particular field will be able to answer questions, solve problems, and make decisions that are usually made by an expert . The Bayes Theorem method can be applied to diagnose parasitic diseases in cats based on input symptoms chosen by the users, the system can perform analysis based on predetermined rules or knowledge base. Based on the probability value of each symptom and disease that has been made, the system can diagnose parasitic diseases in cats with different accuracy results, the highest value or percentage which is the result of the diagnosis of the parasitic disease. From the results of trials conducted by the expert system for diagnosing parasitic diseases in cats using the Bayes Theorem method, the highest value was obtained, namely the type of parasitic disease Flea Disease (P03) with a percentage of 38.66%.
Co-Authors , Achmad Fauzi ., Novriyenni Achmad Fauzi Acmad Fauzi Agi Kakana Bangun Ahmad Fauzi Ahmad Kurniawan Prahadi Alanis Humairoh Alfinaty, Nurma Ambarita, Indah Andika, Rio Andri Kristiawan Annatasia, Kristina Arisma Yulistiani Arisya, Feby Arliana, Lina Aula, Nurhasanah Aulia, Damai Aulia Br Karo Ayu Rahayu Febria Ayu Rahayu Febria Buaton, Relita Budi Serasi Ginting Budi Serasi Ginting Citra Ayu Wasih Dea Syafitri Dhea Armaya Dicky Ananda Azhari Dieo Alfiky Ananda Dila Aulia Putri Dimas Prayogi Dina Ervianna Simarmata Dita Sahputri Elfira Iriani Esti Sundari Eva Sasmita Fadilah, Nurul Elsa Farid Reza Malau Farid Reza Malau Farida Hanum Fauzi Ahmad Muda Fauzi, Achmad Fisyanda Yusmalizar Fresti Anjeli Gea, Wisda Wati Gultom, Imeldawaty Hafizh, Faisal Hermansyah Sembiring I Gusti Prahmana Ika Indah Rahayu Intan Sari Irfan Yusuf Jecika Azzahra Kadim, Lina Arliana Nur Katen Lumbanbatu Katen Lumbanbatu Khair, Husnul Khairunisa, Salsabila Kristina Annatasia Br Sitepu Kristina Annatasia Br Sitepu Kusmananda Lubis Lala Arika Leni Tri Ramadhayanti Lina Arliana Liyanti Armaya Sari Lubis, Setia Adiyasa Lumbanbatu, Katen Magdalena Simanjuntak Magdalena Simanjuntak magdalena simanjuntak Malau, Farid Reza Manik, Laurensia Agustin Mariza Marto Sihombing Maskanda Rizky Maulidina, Nadia Melda Pita Uli Sitompul Mhd Arif Permata Mirah, Alta Muammar Khadafi Muhammad Prabowo Hartanta Sitepu Muhammad Rivaldi Prastowo Muhammad Yusri Nadilla Ayudia Pasa Naftali, Juliana Ningsih, Fauziah Nisrina Naufalia Santoso Novriyenni Novriyenni - Novriyenni, Novriyenni Nurhayati Nursakinah Pakpahan , Victor Maruli Pakpahan, Victor Maruli Pardede, Akim Manaor Hara Pasaribu, Tioria Piper Warni Gea Prahmana, I Gusti Pramana, I Gusti Puteri Diyana Putri Ladya Elvanny Putri Lestari Rafli Pramudia Rahayu, Rizka Putri Rahmat Ramadhan Ramadana, Noval Ramadani, Suci Ratih Puspadini Rayuni, Rayuni Retni Noviyanti Siregar Rindi Asti Ananda Rizki Irwansyah Rizky Ramadhan Rusmin Saragih, Rusmin Sari, Elisa Puspita Saripurna, Darjat Selfira, Selfira Selviyani, Selviyani Sembiring, Hermansyah Sembiring, Jhody Alkhalis Sembiring, Wildan Yuanda Malik Setia Ningsih Shella Nadya Shely Eninta BR PA Sihombing, Anton Sihombing, Marto Silvia, Sindy Simanjuntak, Magdalena Sinurat, Sylvia Natalia Siregar, Retni Noviyanti Siswan Syahputra Suci Rahmadani suci ramadani Suci Ramadani Suci Ramadani Suci Ramadani Suci Ramadani Suci Ramadani Sujayanti Br.Giniting, Novia Suma Dia Syahwani Sundari, Yeni Sundari, Yeni Suria Alamsyah Suria Alamsyah Putra Surya Alamsyah Putra Syahputra , Siswan Syahputra, Siswan Syahputra, Suria Alam Syahputri, Heni Syari, Mili Alfhi Syari, Milli Alfhi Tarigan, Kiki Dea Ananda Tiwi, Chairmayni Pratiwi Tria Damayanti Wardhani, Diah Wardhani, Diah Wardhani Wildan Yuanda Malik Sembiring wildan yuanda malik sembiring Winda Sari Yuyun Arnia Zehy Fadia Zema Zema Zema Zema Zhya Anggraini