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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
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Application of the K-Means Algorithm in Traffic Violations In Langkat District (Case Study: Langkat Police) Elisa Puspita Sari; Yani Maulita; Milli Alfhi Syari
Indonesian Journal of Education And Computer Science Vol. 1 No. 2 (2023): INDOTECH - August 2023
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/indotech.v1i2.50

Abstract

Societal activities are intertwined with traffic, and people prefer using vehicles. The lack of education and limited understanding of traffic regulations have led to numerous violations. The increasing number of traffic violations has resulted in a rise in traffic violation data. The abundance of traffic violation data has led to data accumulation within institutions. Therefore, data processing through data mining utilizing the K-Means Algorithm is deemed necessary. Research findings have unveiled a cluster of traffic violation data that stands out as the highest and most frequent during processing: the age group of 17 to 25 years, involving Honda Vario 150 vehicles, and evidence of violations related to driver's licenses (SIM) and vehicle registration certificates (STNK). Test results on three clusters from a dataset of 502 traffic violation records reveal the following: Cluster 1 comprises traffic violation data pertaining to individuals aged 26 to 45 years, using Honda CBR 250 vehicles, and violations tied to driver's licenses (SIM) and vehicle registration certificates (STNK). Cluster 2 includes traffic violation data concerning individuals aged 26 to 45 years, utilizing Suzuki Nex vehicles, and violations involving driver's licenses (SIM) as well as carrying more than one passenger. Cluster 3 involves traffic violation data associated with individuals aged 17 to 25 years, employing Honda Vario 150 vehicles, and violations linked to driver's licenses (SIM
Sistem Pakar Diagnosis Penyakit Leukosit Menggunakan Metode Certainty Factor Rizki Irwansyah; Yani Maulita; Siswan Syahputra
Syntax : Journal of Software Engineering, Computer Science and Information Technology Vol 3, No 1 (2022): Juni 2022
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/syntax.v3i1.2088

Abstract

  Abstrak: RSU Al Fuadi merupakan salah satu rumah sakit yang menangani penyakit leukosit, penyakit langka yang sering terjadi pada anak usia dini dan remaja, pada kasus leukosis dengan jumlah sel darah putih yang sangat ekstrim tinggi dapat menyebabkan darah sangat kental dan menyebabkan aliran darah menjadi tidak lancar. Kondisi seperti ini disebut sebagai sindrom hiperviskositas yang ditandai dengan stroke, gangguan penglihatan, sesak nafas, perdarahan pada selaput lendir di mulut, lambung, dan usus. Kondisi ini merupakan kasus gawat darurat yang mengancam nyawa. Oleh karena itu perlu adanya suatu sistem untuk mendiagnosa penyakit leukosit lebih awal, dengan gejala yang dialami oleh pasien dan dengan adanya sistem ini dapat dijadikan alternatif pemanfaatan teknologi yang dapat digunakan untuk mendeteksi penyakit leukosit sejak dini secara cepat, tepat, dan akurat, sehingga untuk kedepannya penanganan terhadap penderita penyakit leukosit bisa lebih cepat dan lebih banyak jiwa yang bisa diselamatkan Kata kunci: Sistem Pakar, Leukosit, Certainty Fector Abstract: Al Fuadi RSU is one of the hospitals that treats leukocyte disease, a rare disease that often occurs in early childhood and adolescents, in cases of leukosis with a very high white blood cell count, it can cause the blood to become very thick and cause blood flow to become not smooth. This condition is known as hyperviscosity syndrome which is characterized by stroke, visual disturbances, shortness of breath, bleeding in the mucous membranes in the mouth, stomach, and intestines. This condition is a life-threatening emergency. Therefore, it is necessary to have a system to diagnose leukocyte disease early, with the symptoms experienced by patients and with this system it can be used as an alternative to the use of technology that can be used to detect leukocyte disease early on quickly, precisely, and accurately, so that for the future handling of patients with leukocyte disease can be faster and more lives can be saved Keywords: Expert System, Leukocytes, Certainty Factor 
Sistem Pelaporan Kerusakan Jalan Raya Berbasis Android Dengan Metode Item Collaborative Filtering (Studi Kasus : Dinas PU Kota Binjai) Muhammad Prabowo Hartanta Sitepu; Yani Maulita; Hermansyah Sembiring
Nusantara Journal of Multidisciplinary Science Vol. 1 No. 2 (2023): NJMS - September 2023
Publisher : PT. Inovasi Teknologi Komputer

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Abstract

Kerusakan jalan raya merupakan masalah yang umum terjadi di berbagai kota di seluruh dunia, termasuk Kota Binjai. Dalam upaya untuk mengatasi masalah ini, Dinas Pekerjaan Umum (PU) Kota Binjai membutuhkan sistem pelaporan kerusakan jalan yang efisien dan responsif. Penelitian ini mengusulkan pengembangan Sistem Pelaporan Kerusakan Jalan Raya Berbasis Android dengan menerapkan Metode Item Collaborative Filtering. Sistem ini dirancang untuk memungkinkan masyarakat secara mudah melaporkan kerusakan jalan raya melalui aplikasi Android yang dapat diunduh secara gratis. Metode Item Collaborative Filtering digunakan untuk mengelola laporan kerusakan jalan dan memberikan rekomendasi prioritas perbaikan berdasarkan histori laporan sebelumnya. Hal ini akan membantu Dinas PU Kota Binjai dalam mengalokasikan sumber daya dengan lebih efisien. Penelitian ini juga mencakup studi kasus pada Dinas PU Kota Binjai untuk menguji keefektifan sistem yang diusulkan. Hasil penelitian menunjukkan bahwa sistem ini dapat membantu dalam mendeteksi dan mengatasi kerusakan jalan raya dengan lebih cepat dan efisien, serta memberikan rekomendasi prioritas perbaikan yang lebih akurat. Dengan demikian, sistem ini memiliki potensi besar untuk meningkatkan layanan infrastruktur jalan raya di Kota Binjai dan berpotensi diadopsi oleh kota-kota lain dalam upaya meningkatkan kualitas infrastruktur jalan secara keseluruhan.
SPK Penentuan Pemberian Kredit Pada Koperasi CV. Karya bersama kota Binjai menggunakan metode Topsis Piper Warni Gea; Yani Maulita; Suci Ramadani
Jurnal Widya Vol. 3 No. 2 (2022): Vol 3 No 2 (2022)
Publisher : Akademi Manajemen Informatika dan Komputer Widyaloka

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Abstract

Pemberian kredit bagi nasabah merupakan salah satu upaya yang dapat dilakukan untuk dapat membantu masyarakat dalam mengembangkan usaha atau mengatasi masalah mendesak lain. Namun, dalam pemberian kredit kepada nasabah, diperlukan suatu ketelitian agar pemberian kredit tersebut dapat dipergunakan sesuai dengan peruntukannya dan nasabah mampu melunasi kredit tersebut sesuai dengan waktu yang ditetapkan. Sistem pendukung keputusan merupakan sebuah sistem yang dirancang untuk mampu menghasilkan rekomendasi keputusan berdasarkan ketentuan yang ditetapkan. Metode saw adalah salah satu metode dalam sistem pendukung keputusan. Hasil akhir dari penelitian ini adalah mengetahui cara kerja metode saw dalam menghasilkan rekomendasi keputusan serta aplikasi sistem pendukung keputusan yang dapat membantu stakeholder dalam memberikan kredit bagi nasabah.
Identification of Longan Species Based on Leaf Shape Texture and Color Using KNN Classification Setia Adiyasa Lubis; Yani Maulita; Mili Alfhi Syari
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) Fauziah Ningsih; Yani Maulita; Marto Sihombing
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 Salsabila Khairunisa; Yani Maulita; Magdalena Simanjuntak
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 Jhody Alkhalis Sembiring; Yani Maulita; Suci Ramadani
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 Chairmayni Pratiwi Tiwi; Yani Maulita; Imeldawaty Gultom
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 ɸ (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 Diah Wardhani Wardhani; Yani Maulita; Siswan Syahputra
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.
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 Chairmayni Pratiwi Tiwi Citra Ayu Wasih Dea Syafitri Dhea Armaya Diah Wardhani Wardhani Dicky Ananda Azhari Dieo Alfiky Ananda Dila Aulia Putri Dimas Prayogi Dina Ervianna Simarmata Dita Sahputri Elfira Iriani Elisa Puspita Sari Esti Sundari Eva Sasmita Farid Reza Malau Farid Reza Malau Farida Hanum Fauzi Ahmad Muda Fauzi, Achmad Fauziah Ningsih Fisyanda Yusmalizar Fresti Anjeli Gea, Wisda Wati Gultom, Imeldawaty Hafizh, Faisal Hermansyah Sembiring Hermansyah Sembiring I Gusti Prahmana Ika Indah Rahayu Intan Sari Irfan Yusuf Jecika Azzahra Jhody Alkhalis Sembiring Kadim, Lina Arliana Nur Katen Lumbanbatu Katen Lumbanbatu Khair, Husnul Kristina Annatasia Br Sitepu Kristina Annatasia Br Sitepu Kusmananda Lubis Lala Arika Leni Tri Ramadhayanti Lina Arliana Liyanti Armaya Sari Lumbanbatu, Katen Magdalena Simanjuntak Malau, Farid Reza Manik, Laurensia Agustin Mariza Marto Sihombing Maskanda Rizky Maulidina, Nadia Melda Pita Uli Sitompul Mhd Arif Permata Mili Alfhi Syari Mirah, Alta Muammar Khadafi Muhammad Prabowo Hartanta Sitepu Muhammad Rivaldi Prastowo Muhammad Yusri Nadilla Ayudia Pasa Naftali, Juliana Nisrina Naufalia Santoso Novriyenni Novriyenni - Novriyenni, Novriyenni Nurhayati Nursakinah Nurul Elsa Fadilah 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 Rangga Wahyu Dealova Ratih Puspadini Rayuni, Rayuni Retni Noviyanti Siregar Rindi Asti Ananda Rizki Irwansyah Rizky Ramadhan Rusmin Saragih, Rusmin Salsabila Khairunisa Saripurna, Darjat Selfira, Selfira Selviyani, Selviyani Sembiring, Hermansyah Sembiring, Wildan Yuanda Malik Setia Adiyasa Lubis Setia Ningsih Shella Nadya Shely Eninta BR PA Sihombing, Anton Silvia, Sindy Simanjuntak, Magdalena Simanjuntak, Magdalena Sinurat, Sylvia Natalia Siregar, Retni Noviyanti Siswan Syahputra 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, Milli Alfhi Tarigan, Kiki Dea Ananda Tria Damayanti Wardhani, Diah wildan yuanda malik sembiring Wildan Yuanda Malik Sembiring Winda Sari Yuyun Arnia Zehy Fadia Zema Zema Zema Zema Zhya Anggraini