Article Per Year (5 Year)
p-Index From 2021 - 2026
10.209
P-Index
This Author published in this journals
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
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 110 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 110 Documents
Search

 7   8   9   10   11 
Penerapan Metode K-Nearest Neighbor untuk Mengetahui Tipe Gangguan Kecemasan Berdasarkan Faktor yang Mempengaruhi Zehy Fadia; Yani Maulita; Husnul Khair
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 6 (2025): November: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i6.1137

Abstract

Anxiety disorders are common mental health problems in society, often unrecognized by the sufferer. Identifying the type of anxiety disorder and its influencing factors is crucial for proper treatment. This research aims to apply the K-Nearest Neighbor (K-NN) method in identifying types of anxiety disorders based on influencing factors, focusing on patient data from Sylvani Hospital, Binjai. The K-NN method was chosen because of its ability to classify based on data proximity. This study used medical record data of patients with anxiety disorders, which were processed using MATLAB and Microsoft Excel software. The results show that the K-NN method is effective in identifying types of anxiety disorders, with a high level of accuracy, especially in the identification of Panic Disorder (K05) and Social Anxiety Disorder (K03). The use of MATLAB simplified the identification process by automating results, while data processing in Excel improved classification accuracy. This study concludes that the K-NN method can be an effective alternative in identifying anxiety disorder types based on the factors that influence them. It is recommended for future research to involve more variables and mental health experts for a more comprehensive validation of the results.
PELATIHAN PERENCANAAN BERBASIS DATA PADA PENGAWAS SEKOLAH, KEPALA SEKOLAH DAN GURU MENGGUNAKAN METODE INDENTIFIKASI, REFLEKSI DAN BENAHI (IRB) SECARA DARING Fauzi, Achmad; Rahayu, Rizka Putri; Khair, Husnul; Maulita, Yani
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 3 No 2 (2023): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methabdi.Vol3No2.pp170-174

Abstract

Data-based planning training is carried out online based on various sources which can be used to carry out or prepare an agenda for future activities and budgets. The data-based planning training activity was carried out online for two days. This implementation started with the experience of the school principal sharing his experience with the education unit in planning and compiling activities and making budgets at the school, then the facilitator provided reinforcement for data mining from the independent teaching platform (PMM ), Education Report Card Platform as well as through data sourced from the North Sumatra Education Quality Assurance Center (LPMP). Then the facilitator reflects on the training on the material that has been explained. On the second day of implementation, each educational unit grouped to discuss and fill in the evaluation sheet, then carried out identification, reflection and improvement in planning activity plans and preparing budgets for the unit, then apart from that, the educational units held discussions to make follow-up plans starting from the date, unit involved and the media used. Next, reflect on your experience at school, then work on an evaluation worksheet that is synchronized with the Identification worksheet, then a reflection worksheet and a fix worksheet, then the education unit finishes working on an activity plan that comes from several data and can prepare a budget that is planned for the long term.
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%.
Grouping Patient Data Based On Work And Place Of Residence On Perceived Complaints Sembiring, Jhody Alkhalis; Maulita, Yani; Ramadani, Suci
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.v3i1.268

Abstract

Every day the Sawit Seberang Health Center serves many patients with various kinds of disease complaints from various areas in Sawit Seberang District. The number of patients can even reach tens of people in one day resulting in a large number of patient visit data. Limited information regarding the spread of diseases that are often suffered by patients in several areas at the Sawit Seberang Health Center has resulted in less optimal policy action, anticipation of treatment and prevention of disease in the community. To find information about grouping patient data based on work and place of residence for perceived complaints, a large or large data mining technique is needed, namely data mining techniques using the clustering method. The purpose of this study is to process and cluster patient data based on work, place of residence and complaints that are felt using the Clustering method, to analyze the results of applying data mining using K-Means Clustering in grouping patient data based on work, place of residence and complaints that are felt and find out the results of the settlement grouping patient data based on work and place of residence on perceived complaints using clustering and data mining methods.
The Effect of Social Media on Student Learning Motivation Using the Apriori Method Tiwi, Chairmayni Pratiwi; Maulita, Yani; Gultom, Imeldawaty
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.v3i1.273

Abstract

The success of student learning can be determined by their motivation. Students who have high learning motivation tend to have high achievement as well, otherwise their learning motivation is low, their learning achievement will also be low. student learning motivation in the subject is very low. Some students prefer to play social media rather than pay attention to the material explained by the teacher during class hours. Therefore, this study aims to explore the influence of social media on students' learning motivation. This research uses data mining method with Apriori algorithm to identify patterns related to social media usage and students' learning motivation. The Apriori algorithm is one of many algorithms in data mining that is used for frequent itemsets and association rules in databases on transactional data that are generated by identifying each item that exists, and combining larger sets of items provided that the items appear frequently enough in the database. Based on the research that has been done, the author can draw the conclusion that using the Rapid Miner 7.1 application tools in applying the apriori algorithm produces the same rules as manual calculations using 300 data on the learning motivation of Abdi Negara Binjai SMKS students and the system can generate association rules using 300 student learning motivation data with a minimum support of 12% and a minimum confidence of 75% and produce 5 association rules 3 itemsets to determine the learning motivation of Abdi Negara Binjai SMKS students. One of the rules that has the highest confidence value is, if YT and J2 then M1. Which means that every student who uses YOUTUBE Social Media with a length of use is 3-4 HOURS then INCREASES STUDY MOTIVATION. Then the less the ΙΈ (frequent) value is set, the more data that can be processed, as well as the minimum support value and confidence value, where the smaller the value determined, the more association results will be issued.
Expert System To Diagnose Stem Border In Sugarcane Plant With Certainty Factor Method Wardhani, Diah Wardhani; Maulita, Yani; Syahputra, Siswan
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.v3i1.291

Abstract

Sugarcane (Saccharum Officanarum L) is an annual plantation crop, which has its own characteristics, because it contains sugar in its stems. Sugarcane belongs to the grass family (graminae) like rice, reeds, corn, bamboo and others. One of the problems that exist in sugarcane plantations at PT Perkebunan Nusantara II is stem borer pests. Losses due to borer attacks can be in the form of a decrease in sugarcane weight, yield and quality of the sap obtained. pests on sugarcane plants cause a decrease in sugar production of about 10%. There are three types of stem borer pests found in PT Perkebunan Nusantara II, namely shoot borer pests, striped stem borer pests, and giant stem borer pests. Meanwhile, biological control is by spreading natural predators of pests which will suppress the population of widespread distribution and breeding of pests which are commonly called parasitoids. Parasitoids will become predators of their respective hosts, so appropriate diagnostic therapy for stem borer pests is needed so that the spread of stem borer pests does not become more widespread and the parasitoids to be spread operate effectively. By using the Certainty Factor method, you can find out the types of pests that are attacking sugarcane plants. Based on manual calculations, the dipole yield was 79% on one of the selected pest types based on the symptoms induced in the sugarcane plant.
Application Of The Profile Matching Method In The Selection Of New Students For Batak Karo Bridal Makeup Skills In The PKK Program Suma Dia Syahwani; 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.v3i1.293

Abstract

Makeup is the art of using makeup materials to change the natural face shape into an artistic face. Work Skills Education (PKK) itself is an education and training service program oriented towards the development of work skills provided to students in order to have competence in certain skills that are in accordance with job opportunities. Profile matching is the process of comparing the actual data value of a profile to be assessed with the expected profile value so that it can be known the difference in competence or the distance between one value and another. This research aims to facilitate the selection of new prospective students in the PKK program at the Pelawi Salon Binjai Course and Training Institute (LKP) and optimize admin work time in the process of selecting new students. By applying this method, it aims to see the eligibility of prospective students according to predetermined criteria so that the opportunity to take part in the PKK program can be received by the right person. There are 5 sample data with 6 criteria in this research, the final result in this study is 3.5 being the highest value and 2.99 being the lowest value.
Pengelompokan UMKM Kota Binjai Menggunakan Metode Clustering K-Means Untuk Mengidentifikasi Pola Perkembangan Bisnis Intan Sari; Yani Maulita; Lina Arliana Nur Kadim
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 3 (2024): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i3.148

Abstract

Grouping is a process or activity to develop a system that is more organized and easy to understand, making it easier to analyze, identify or manage data and can also be used to explore information so that it becomes new knowledge for anyone who wants to obtain it. and in this case the information we want to explore is about MSME data in Binjai City. Namely, it is difficult to know how to identify existing business development patterns, whether they are not yet developed, less developed, already developed, and very developed. Offline and online promotions have not been optimal in increasing the growth and change of a business from time to time. And most MSMEs still don't understand how to market their products and services effectively and efficiently. MSMEs are one of the most numerous community business groups in Binjai City. To obtain this information, one solution that can be implemented is by utilizing data mining using input data in the form of Binjai City MSME data. This data will be processed using the clustering method with the k-means algorithm using MSME business type variables, sales type variables and development pattern variables. .Based on the results of grouping Binjai City MSMEs using the K-Means Clustering Method from 20 grouped data, 3 clusters and 2 iterations were obtained where cluster 1 contained 4 data and was located in the MSME business type group, namely the businesses included in this cluster were businesses in the field of Fashion, for the sales type group, uses online and offline types, and for business development patterns, it has a development pattern that has developed. cluster 2 has 11 and is located in the MSME business type group, namely the businesses included in this cluster are businesses in the culinary sector, for the sales type group the offline type is used, and for the business development pattern it has a development pattern that has developed. and cluster 3 has 5 data and is located in the MSME business type group, namely the businesses included in this cluster are businesses in the culinary sector, for the sales type group it is using the offline type, and for the business development pattern it has a less developed development pattern. so it can be concluded that the pattern of business development of Binjai City MSMEs produces relevant data so as to produce designs that can be used for this research.
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 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