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Determining The Selection Of Departments At Abdi Negara Vocational School Using The Additive Ratio Assessment (Aras) Method Putri Lishayani; Relita Buaton; Tio Ria Pasaribu
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.v3i1.251

Abstract

Along with the occurrence of competition and the development of technology and information in the current era of globalization requires skilled and ready-to-use human resources in the world of work. The efforts made are to improve the quality of education in Indonesia which always receives attention from various parties. One way to improve education is to determine the right majors at Vocational High Schools (SMK). The differences in each student with a different background must be considered because they can determine whether student achievement is good or bad. In ddition, the decision also greatly influences the alternative process chosen, especially in choosing the concentration of majors that are in accordance with the skills and expertise of students. Based on the author's observations at ABDI NEGARA VOCATIONAL SCHOOL through data collection both by conducting interviews and through available documents, the reasons students choose majors are usually based on student parents' references, besides that due to trend reasons (most students take that major). Therefore, through research using Decision Support Systems, it is hoped that it can provide recommendations to find out which majors to choose according to the interests or abilities of each student. So that there are no problems regarding failure or dropping out of school (drop out).
IoT-based Hydroponic Plant Monitoring System Fadillah Fadillah; Relita Buaton; 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.v3i1.255

Abstract

The Industrial Revolution 4.0 has an impact in the form of changes in various fields of human civilization, one of which is the agricultural sector. By applying IoT technology, hydroponic plants will effectively be accurate. IoT has room for improvement in the quality and quantity of agricultural production because it facilitates the automation of monitoring various processes with high precision This research uses the prototype method. Which uses the concept of direct monitoring and allows iterative changes to be made until the desired results are achieved. So this prototype method makes it possible to display the display directly. The microcontroller used is ESP32 which is connected to 3 sensors, namely the TDS sensor, DHT11 sensor and HC-SR04 sensor which are directly updated in the blynk application. In making the software program used is the Arduino IDE. Implementation of the tool is carried out on a floating raft installation. This iot-based hydroponic plant monitoring system has been successfully made and is able to monitor well. Because the system made is related to water, it is necessary to design a tool that is safer and has more protection so that it can’t only run well but also safer for users and a high level of durability.
Sentiment Analysis Using Text Mining Techniques On Social Media Using the Support Vector Machine Method Case Study Seagames 2023 Football Final Muhammad Rifa'i; Relita Buaton; I Gusti Prahmana
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.v3i1.274

Abstract

This thesis aims to analyze sentiment on text data from social media related to the 2023 SEA Games, especially in the final match of the soccer sport. The method used is the Text Mining Technique with the SVM (Support Vector Machine) algorithm to classify user sentiment as positive or negative regarding the match. Text data is retrieved from various social media platforms during and after the match. The results of the sentiment analysis are expected to provide insight into the public's view of the sporting event. This research can contribute to the understanding of public sentiment towards the 2023 SEA Games final football match through the analysis of text data from social media.
Grouping Data On Infrastructure Development In Langkat District Using The Clustering Method (Case Study: PUPR, Langkat Regency) Diva Alifya; Relita Buaton; 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.v3i1.278

Abstract

A building is a man-made structure consisting of walls and a roof permanently erected in a place. Buildings can also be called houses and buildings, namely all facilities, infrastructure or infrastructure in culture as well as human life in building their civilization. Public Works and Public Housing (PUPR) play an important role in increasing the development of national infrastructure in Indonesia so that PUPR can assist in clustering research in infrastructure development in Langkat Regency which is very large every year by grouping the data based on activity names, company names, sub-districts development, and look at the last four years.To classify existing development infrastructure in Langkat Regency with the previous system used by the PUPR Service which is still running by recording in a ledger and hindering reporting performance in grouping PUPR service infrastructure development in road construction, bridge construction and others. So that the existence of grouping using the clustering method helps the PUPR service in clustering infrastructure development data in Langkat Regency to be more effective and efficient.The clustering method is one of the methods that can be applied in classifying infrastructure development data taken from the analysis of Langkat Regency PUPR data regarding developments that have taken place in several sub-districts in Langkat Regency. This clustering method has been widely used by previous studies to group data
Application of Data Mining in Analyzing the Effect of Parents' Employment and Education Level on Student Behavior Using the A PRIORI Method (Case Study: SDN 024769 Binjai) Suha Baby Mayaza; Relita Buaton; 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.v3i1.279

Abstract

Behavior is a person's reaction to a stimulus that comes from the external environment. Parents are one of the main factors in the formation of children's behavior. This study aims to find out the effect of parents' work and education on student behavior. By using RapidMiner in testing 234 SDN 024769 Binjai student data, using the Apriori method and setting a minimum support value of 8% and 70% confidence, 1207 rules were obtained in the entire set and 2 rules in 9 itemsets. And the best rule with the highest value is obtained, if the father's job is self-employed, the mother's job is self-employed, the father's last education is high school, the mother's last education is high school, the time the father spends working is more than 8 hours per day, the time the mother spends working is more than 8 hours per day, the time the father spends on family is every day, and the time the mother spends on family is every day then the student has good behavior at school, with a support value of 8.5% and a certainty value of 95.2%.
Application of the Clustering Algorithm for the Classification of General Criminal Cases at the Binjai District Attorney's Office Ratih; Relita Buaton; Katen Lumbanbatu
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.v3i1.296

Abstract

The Binjai District Attorney's Office in carrying out its duties and functions, one of which handles general crimes, where so far the SPDP (Warranty to Commence Investigation) from the police that has entered the Binjai District Prosecutor's Office amounted to approximately 50 (fifty) cases each month. This amount consists of several types of general criminal cases. It is known that the types of general criminal cases amount to approximately 215 (two hundred and fifteen) types of cases, from this data, a method of classifying/clustering is needed from the types of cases that exist each month so that the data can be processed so as to produce the highest, moderate and highest scores. the lowest value of a type of case. The Binjai District Attorney's Office often receives requests for data from other ministries or agencies such as the BPS (Central Statistics Agency), the National Commission on Women and the National Commission on Children in the form of data recapitulation of crimes against women and children as perpetrators of crimes. The Binjai District Attorney's Office has a case handling system where the recapitulation cannot be taken directly but instead collects data manually, because the existing case handling system does not have the recapitulation as requested.The application of clustering has been carried out by many previous researchers. Among them, the K-Means Clustering Algorithm Analysis Mapping the Number of Crimes. The research was carried out using a data mining model in classifying illegal fishing with the K-Means algorithm analysis by determining the shortest distance using the eulclidean distance, more optimal than using the mahattan distance and chbchep distance in classifying student achievement, determining the centroid (central point) in the early stages of the algorithm K-Means is very influential on cluster results as the results of tests carried out using 267 records with different centroids produce different cluster results as well, a clustering model is obtained that can be used for illegal fishing in decision making for illegal fishing crimes high, medium, moderate .
Jaringan Syaraf Tiruan Memprediksi Pernikahan Di Kementerian Agama Kota Binjai Dengan Menggunakan Metode Backpropagation Anisa Anisa; Budi Serasi Ginting; Relita Buaton
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v6i2.217

Abstract

Pada dasarnya teknologi merupakan fasilisator yang saat ini telah mewadahi segala aspek dankegiatan-kegiatan manusia, baik dibidang Pendidikan, Kesehatan, Sosial, Ekonomi, dan Budaya. Menurut hasil dari penelitian Kantor Kementerian Agama Kota Binjai belum sepenuhnya memanfaatkan Sumber data yang ada untuk memprediksi jumlah data nikah berikutnya lebih banyak atau lebih sedikit. Jaringan Syaraf Tiruan merupakan salah satu sistem pemrosesan informasi yang didesain dengan menirukan cara kerja otak manusia dan menyelesaikan masalah. Dalam penerapannya JST sering digunakan pada peramalan atau prediksi, dalam prediksi metode JST yang sering digunakan yaitu metode Backpropagation. Berkaitan denganhal tersebut, untuk membantu dan mempermudah dalam memprediksi jumlah tingkat data nikah Kantor Kementerian Agama Kota Binjai. Untuk 1 interasi dengan menggunakan metode Backpropagation hasilnya 0,562312667.
IMPLEMENTASI METODE APRIORI DALAM PERENCANAAN PERSEDIAAN OBAT PADA APOTEK SAFANA Yusnan Sepriadi Ginting; Relita Buaton; Nurhayati Nurhayati
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v6i2.226

Abstract

Dalam penelitian ini akan dilakukan proses penentuan pemberian obat yang tepat sangat menentukan tingkat kepuasan pasien terhadap pelayanan apotek. Oleh karena itu, maka persediaan obat perlu diperhatikan agar obat – obatan dengan beragam jenis dan fungsi tetap tersediasetiap saat. Untuk  mengetahui  obat-obatan apa saja  yang  dibeli  oleh para  konsumen, dilakukan  teknik  analisis  keranjang  pasar  yaitu analisis dari kebiasaan membeli konsumen. Hasil analisis pola diatas menunjukkan bahwa nilai support yang semakin besar dari sebuah kombinasi persediaan obat memberikan rekomendasi persediaan obat yang paling sering dibeli oleh konsumen adalah Ambroxol, Amoxilin, Amlbumin, Perban elastis. Sebaliknya semakin kecil nilai support suatu kombinasi persediaan obat artinya rekomendasi diberikan berdasarkan berdasarkan persediaan obat yang jarang dibeli. Adapun hasil dari penerapan metode apriori dengan minimum support 30% dengan kombinasi 3 dan 4 itemset adalah jika Neurobion Forte Tab, Clindamycin 300 mg, Amlodipine 5 mg tab. Metode apriori yang digunakan cukup efektif dalam memberikan hasil akhir kombinasi obat yang sering dibeli oleh konsumen. Tingkat keakuratan pengujian menggunakan metode apriori yaitu 100 %.
PERBAIKAN KUALITAS CITRA GOOGLE MAPS MENGGUNAKAN METODE CONTRAST STRETCHING Deri Kurniawan; Relita Buaton; Achmad fauzi
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v6i2.227

Abstract

Citra peta (Maps) digital dapat digunakan untuk menelusuri, menjelajahi dan menemukan jalan di seluruh dunia. Grafik yang dihasilkan dari perekaman gambar oleh satelit mewakili beberapa warna pada objek yang ditampilkan pada Google Maps. Proses mengambilan (capture) citra Google Maps sering digunakan untuk keperluan tertentu, seperti menggambarkan wilayah perkebunan yang dapat menggambarkan lahan tandus tanaman atau lahan dengan tanaman yang subur dan sebagainya. Jika hasil perekaman satelit tidak maksimal dapat mengakibatkan informasi yang terdapat pada citra Google Maps menjadi berkurang. Berdasarkan pengamatan, maka perlu di bangun sebuah sistem yang terkomputerisasi untuk memperbaiki kualitas citra Google Maps, sehingga citra yang ditampilkan memiliki kualitas yang lebih baik setelah melalui proses perbaikan. Proses perbaikan yang dimaksud adalah untuk memperjelas objek-objek pada citra Google Maps yang tidak dapat digambarkan dengan baik oleh penangkapan satelit. Salah satu metode image enhancement yang dapat digunakan adalah Contrast Stretching. Pemanfaatan metode Contrast Stretching dapat memperbaiki kualitas citra yang kurang baik dengan meningkatkan nilai kontras dari citra digital tersebut, melalui proses peningkatan pixel gray level. Sistem dirancang dengan aplikasi pemrograman MATLAB R2014a, setelah melakukan proses pengujian pada beberapa citra Google Maps, didapatkan hasil bahwa rata-rata persentasi proses perbaikan citra diatas 75% dan citra Google Maps hasil perbaikan sistem menjadi lebih baik dari citra yang diinputkan pada sistem.
DATA MINING PENGELOMPOKAN INDUSTRI KECIL DAN MENENGAH BERDASARKAN HASIL PRODUKSI MENGGUNAKAN METODE CLUSTERING DI KABUPATEN LANGKAT Lidya Hasna; Relita Buaton; Siswan Syahputra
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v6i2.299

Abstract

Industri Kecil dan Menengah (IKM) adalah rangkaian kegiatan dan ekonomi yang meliputi pengolahan, pengerjaan, pengubahan, perbaikan bahan baku atau barang setengah jadi menjadi barang yang berguna dan lebih bermanfaat untuk pemakaian dan usaha jasa yang menunjang berbagai kegiatan. Pada saat ini, jumlah IKM di Kabupaten Langkat terus meningkat, banyaknya data IKM yang pengelompokannya masih acak dan tidak teratur menyebabkan bagian Perindustrian cukup kesulitan dalam mengelompokan data IKM tersebut berdasarkan Kecamatan, Jenis Industri dan Hasil Produksi.Tujuan dari penelitian ini adalah untuk menerapkan Algoritma K-Means dalam mengelompokan data IKM di Kabupaten Langkat serta untuk memberikan informasi tambahan mengenai perkembangan dan pertumbuhan IKM yang berada di Kabupaten Langkat. Diperoleh hasil pengelompokan menjadi 3 cluster yaitu pada cluster 1 berjumlah 7 data dimana kelompok industri kecil dan menengah pada Kecamatan (X) Kutambaru dengan Jenis Industri (Y) adalah Industri makanan ringan dan Hasil produksi (Z) adalahTempe, cluster 2 berjumlah 6 dimana kelompok industri kecil dan menengah pada Kecamatan (X) Sawit Seberang dengan Jenis Industri (Y) adalah kerajinan/anyaman dan Hasil produksi (Z) adalah Ukir Batu akik, dan cluster 3 berjumlah 6 data dimana kelompok industri kecil dan menengah pada Kecamatan (X) Brandan Barat dengan Jenis Industri (Y) adalah Bangunan/Mebel/Logam dan Hasil produksi (Z) adalah Industri Kayu.
Co-Authors Achmad Fauzi ACHMAD FAUZI Ade Chairany Adek Maulidya Adinda Maudia Savira Ajisro Siringoringo Alma Diana Rangkuti Alma Diana Rangkuti Ambarita, Indah Ami Dilham Ana, Putri Andri Kristiawan Anisa Anisa Anisa Anisa Anisa Putri Pratiwi anjelia alsar anjeliaalsharlubis Anjelia Alsar Lubis Annatasia , Kristina Aprillianda Pasaribu Aula, Nurhasanah Auni Patrisyah Ayu Rahayu Febria Ayu Rahayu Febria Br. Ginting, Rosa Lina Budi Serasi Ginting Budi Serasi Ginting Cinta Apriliza Clara Rosa Wijaya David Jumpa Malem Sembiring Dea, Dea Puspita Deny Jollyta Deri Kurniawan Desva Karliana br Sembiring Dhea Agustina Akmal Dhea Alfiya Ningsih Dhovan Damara Santoso Dicha Mutia Dhani Dita Mawarni Diva Alifya Dwi Astuti Eli Yusrina Elviwani Elviwani Ema Sari Suwandi Fadillah Fadillah Fajar Amalia Putri Fany Juliawati Farid Reza Malau Fauzi, Achmad Febi Andini Fuji Dodo Aritonang Gultom, Imeldawaty Haryanto, Septian Hayati, Radhiah Heka Herawati Br Tarigan Herman Mawengkang Hermansyah Sembiring Hermansyah Sembiring Husnul K I Gusti Prahmana I Gusti Prahmana I Gusti Prahmana I Gusti Prahmana Indah Malasari Ivan Candra Dinata Kadim, Lina Arliana Nur Katen Lumbanbatu Khair, Husnul Kristina Ananatasia Kristina Annatasia Leni Tri Ramadhayanti Lestari, Chintiya Wahyuni Indah lidya hasna Lidya Hasna Lubis, Anjelia Alsar Magdalena Simanjuntak magdalena simanjuntak Malau, Farid Reza Marto Sihombing Melda Pita Uli Sitompul Mesra Yel Mili Alfhi Syari Muammar Khadapi Muhammad Arif Ridho Muhammad Rifa'i Muhammad Zarlis Muhammad Zarlis, Muhammad N Novriyenni Nadila Rahmawati Nike Alpio Rizky Ningsih, Novia Novita Anggraini Novriyenni Nur Fariza Khairani Nurhayati Nurlaila Nurlaila Nurlaila Nurlaila Nurul Syahrani Pardede, Akim Manaor Hara Prahmana , I Gusti Prisa Abela Purba, Ramen Antonov Putri Lishayani Putri Purwani, Dea Nanda Raja Rizki Alanta Nasution Ramadani, Suci Rani Lestari Rani Nuraini Rani Nuraini Ratih Ratih Puspadini Reza Alexandra Rianty Zabitha Siregar Rohana, Sherly Rusmin Saragih, Rusmin Sany Lubis, Fauzan Al An Selfira Selfira Sembiring, Hermansyah septian haryanto Septian Haryanto Sherly Eka Wahyuni Sihombing, Anton Sihombing, Marto Simanjuntak, Magdalena Sinaga, Ayu Puspita Sari Sinek Mehuli Br Perangin-Angin Siswan Syahputra Solikhun Solikhun Solikhun Solikhun, Solikhun Sri Astuti Sri Hardiningsih suci ramadani Suha Baby Mayaza Sundari, Yeni Sundari, Yeni Suria Alamsyah Putra Syahputra, Suria Alam Syahril Effendi Syari, Milli Alfhi T. Reza Pahlevi Teuku Reza Pahlefi Tiara Jelita Tio Ria Pasaribu Windy Indah Sary Sinaga Windy, Windy Alfira Yani Maulita Yusnan Sepriadi Ginting Yusnan Sepriadi Ginting Yuyun Arnia Zarlis Muhammad Zuliani Zuliani Zulkifli Zulkifli