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All Journal Jurnal Media Infotama Jurnal Sains dan Teknologi Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Majalah Ilmiah Kaputama JTIK (Jurnal Teknik Informatika Kaputama) MEANS (Media Informasi Analisa dan Sistem) Jurnal Manajemen Informatika Jayakarta Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Journal of Vision and Ideas (VISA) EXPLORER Bulletin of Multi-Disciplinary Science and Applied Technology Archive: Jurnal Pengabdian Kepada Masyarakat Jurnal Nasional Teknologi Komputer Sci-Tech Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA) International Journal of Informatics, Economics, Management and Science Journal of Engineering, Technology and Computing (JETCom) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer 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 Jurnal Penelitian Teknologi Informasi dan Sains Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika 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 Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Saturnus: Jurnal Teknologi dan Sistem Informasi International Journal of Information Engineering and Science
Buaton, Relita
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Sistem Pakar Mengidentifikasi Kegemaran Anak Dalam Proses Belajar Menggunakan Metode Certainty Factor Berbasis Web (Studi Kasus : RA Wildan) Alma Diana Rangkuti; Relita Buaton; Siswan Syahputra
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 6 No. 1 (2022): Volume 6, Nomor 1, Januari 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v6i1.378

Abstract

Perkembangan dapat mempengaruhi kegemaran atau minat yang terjadi pada anak, yang dipengaruhi oleh dua faktor yaitu perkembangan fisik dan perkembangan kognitif. Perkembangan kognitif berperan penting karena dapat menentukan jenis kegemaran yang membantu menentukan minat yang akan memetakan arah pemilihan studi dan pengembangan diri untuk mendapatkan kompetensi dan keterampilan yang dibutuhkan oleh anak. Banyak guru yang masih bingung bagaimana mengetahui perkembangan kognitif anak karena keterbatasan pengetahuan yang mereka miliki. Sistem pakar merupakan suatu sistem yang dirancang untuk dapat menirukan keahlian seorang pakar dalam menjawab pertanyaan dan memecahkan masalah. Dimana keahlian pakar inilah yang akan memudahkan guru dalam mengetahui proses perkembangan anak dan membantu menentukan stimulasi yang tepat. Certainty Factor adalah salah satu metode dari sistem pakar yang dapat melihat apakah sebuah fakta bersifat pasti atau tidak pasti dan dapat memberikan hasil yang akurat yang didapatkan dari perhitungan dari bobot gejala yang dipilih oleh pakar dan mampu memberikan jawaban pada permasalahan yang tidak pasti hasilnya.
Kepatuhan Wajib Pajak Bumi dan Bangunan Berdasarkan Wilayah Kota Binjai Menggunakan Algoritma Clustering Indah Malasari; Relita Buaton; Anton Sihombing
Jurnal Manajamen Informatika Jayakarta Vol 3 No 3 (2023): JMI Jayakarta (Juli 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v3i3.1135

Abstract

Land and Building Tax (PBB) is one type of regional tax regulated by the government in determining the amount of tax for implementation and development and increasing the prosperity and welfare of the people. Based on taxpayer compliance data at BPKPAD Kota Binjai, it shows that the more taxpayers in a region, the more data stored will also increase. From the tests carried out using the Clustering algorithm, it can be known the variables of area area, Kelurahan, Payment Status level. It is known that Cluster 1,2,3 of 518 UN mandatory data is where Cluster 1 amounts to 242 data, Area is 1,000,000 – 501,000, with Binjai Village and Payment Rate is Poor, Cluster 2 has 60 data Area is 500,000 – 251,000, with Kelurahan Suka Maju and Payment Rate is Poor and Cluster 3 is 216 data Area Area is 1,000,000 – 501,000, with Jati Negara Village and Payment Rate is Not Good.
Application of Numerical Measure Variations in K-Means Clustering for Grouping Data Relita Buaton; Solikhun Solikhun
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 1 (2023)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.3269

Abstract

The K-Means Clustering algorithm is commonly used by researchers in grouping data. The main problem in this study was that it has yet to be discovered how optimal the grouping with variations in distance calculations is in K-Means Clustering. The purpose of this research was to compare distance calculation methods with K-Means such as Euclidean Distance, Canberra Distance, Chebychev Distance, Cosine Similarity, Dynamic TimeWarping Distance, Jaccard Similarity, and Manhattan Distance to find out how optimal the distance calculation is in the K-Means method. The best distancecalculation was determined from the smallest Davies Bouldin Index value. This research aimed to find optimal clusters using the K-Means Clustering algorithm with seven distance calculations based on types of numerical measures. This research method compared distance calculation methods in the K-Means algorithm, such as Euclidean Distance, Canberra Distance, Chebychev Distance, Cosine Smilirity, Dynamic Time Warping Distance, Jaccard Smilirity and Manhattan Distance to find out how optimal the distance calculation is in the K-Means method. Determining the best distance calculation can be seen from the smallest Davies Bouldin Index value. The data used in this study was on cosmetic sales at Devi Cosmetics, consisting of cosmetics sales from January to April 2022 with 56 product items. The result of this study was a comparison of numerical measures in the K-Means Clustering algorithm. The optimal cluster was calculating the Euclidean distance with a total of 9 clusters with a DBI value of 0.224. In comparison, the best average DBI value was the calculation of the Euclidean Distance with an average DBI value of 0.265.
Sistem Pendukung Keputusan Pemilihan Pegawai Non-PNS Terbaik di Dinas Pengendalian Penduduk Dan Keluarga Berencana Kota Binjai Menggunakan Metode Moosra Dan Roc Rianty Zabitha Siregar; Relita Buaton; Rusmin Saragih
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 2 No. 4 (2024): November : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v2i4.2454

Abstract

Employee evaluations within an organization are efforts to measure and motivate employees to enhance their skills and abilities. These evaluations are expected to help the organization assess and identify improvements or developments in employee capabilities to support the organization in achieving its goals. The evaluations are anticipated to produce fair and transparent results that are acceptable to all parties involved. The rapid advancement of information technology has brought changes to the employee evaluation process. Specifically, the Population Control and Family Planning Office of Binjai City requires a system that can assist in evaluating the performance of its non-permanent employees. There are various methods that can be used in designing a system to produce the best decisions. Among them is the MOOSRA (Multi-Objective Optimization on the Basis of Simple Ratio Analysis) method, which is one of the multi-objective optimization techniques used in decision support systems. The MOOSRA method is similar to the MOORA method but differs in performance score determination: MOORA uses a reduction operator, while MOOSRA relies on calculations based on criteria and alternative division operators. MOOSRA performs calculations based on the provided criteria and alternatives. To determine the weight of each criterion, the ROC (Rank Order Centroid) method is employed, which assigns weights to each criterion based on their ranking and priority levels. This ensures that the evaluation of non-permanent employees at the Population Control and Family Planning Office of Binjai City produces the best results. The MOOSRA and ROC methods can be used to build a decision support system that delivers optimal evaluations of non-permanent employees. Awarding the title of "best employee" can enhance morale and motivation among employees in achieving the organization's previously established goals. The selection of the best non-permanent employee must be conducted fairly and transparently so that the results are accepted by all non-permanent employees of the Population Control and Family Planning Office of Binjai City. A decision support system performs calculations based on established criteria for each alternative and provides recommendations that can help leadership make the best decisions. The MOOSRA method is a decision support system technique that uses multi-criteria analysis in its calculations, while the ROC method aids in determining the weight of criteria based on their priority.
Grouping Data of Patients Who Are Conducting Drugs Abuse Rehabilitation Using The Clustering Method (Case Study: BNNK Binjai) Ana, Putri; Buaton, Relita; Simanjuntak, Magdalena
Journal of Engineering, Technology and Computing (JETCom) Vol. 2 No. 2 (2023): JETCom, July 2023
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/jetcom.v2i2.103

Abstract

Rehabilitation is an appropriate alternative punishment for drug addicts. By utilizing data mining using input data in the form of rehabilitation patient data at BNNK Binjai, the data will be processed using the clustering method using the k-means algorithm. K-Means is a non-hierarchical data clustering method that seeks to partition existing data into one or more clusters or groups so that data has characteristics. Of the 20 data tested in cluster 1 there are a total of 13 data and are located in the Age group (X) which is 26-35 years old, and for the substance type group (Y) used is methamphetamine and in the Occupational group (Z), namely Self-employed. in cluster 2 there is a total of 5 data and it is located in the Age group (X) which is 26-35 years old, and for the Substance type group (Y) used is Shabu and in the Employment group (Z) namely Not Yet Working. in cluster 3 there is a total of 2 data and it is located in the Age group (X) which is 26-35 years old, and for the Substance type group (Y) used is Shabu and in the Occupational group (Z) namely Private Employees.
DECISION SUPPORT SYSTEM FOR DETERMINING ADDICTION COUNSELORS USING THE ARAS METHOD AT THE BINJAI CITY BNN OFFICE Hardiningsih, Sri; Buaton, Relita; Prahmana , I Gusti
Journal of Engineering, Technology and Computing (JETCom) Vol. 2 No. 3 (2023): JETCom, November 2023
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/jetcom.v2i3.123

Abstract

Konselor Adiksi merupakan orang yang bertugas melaksanakan kegiatan rehabilitasi kecanduan atau ketergantungan secara fisik dan mental terhadap suatu zat dan memiliki kompetensi di bidang kesehatan dan sosial yang mengkhususkan diri dalam membantu orang dengan ketergantungan narkotika, psikotropika dan zat adiktif lainnya. Sistem Pendukung Keputusan (SPK) akan dibangun menggunakan metode Additive Ratio Assesment (ARAS) yang merupakan metode pengambilan keputusan multi kriteria berdasarkan pada konsep perangkingan menggunakan utilitydegree yaitu dengan membandingkan nilai indeks keseluruhan setiap alternatif terhadap nilai indeks keseluruhan alternatif optimal.
BPJS SERVICE DATA CLUSTERIZATION USING K-MEANS ALGORITHM : (Case Study: BPJS Binjai Office) Br. Ginting, Rosa Lina; Buaton, Relita; Khair, Husnul
Journal of Engineering, Technology and Computing (JETCom) Vol. 2 No. 3 (2023): JETCom, November 2023
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/jetcom.v2i3.131

Abstract

 Employment BPJS is a program formed by the government to provide social protection to workers. Due to the large number of workers, for example, using the Death Insurance program (JKM), it will produce abundant and accumulating data. To find out BPJS service data is to group BPJS service data in BPJS. One of the most widely used methods in the clustering method is to use the K-Means algorithm. K-Means is a non-hierarchical (block) grouping method that seeks to partition data into clusters/groups so that data with the same characteristics will be included in the clustering method. in the same cluster and data with different characteristics are grouped into another group. From the 20 data obtained 3 groups, Cluster 1 has 3 data, Cluster 2 has 4 data, and Cluster 3 has 13 data. Cluster 1 has the male sex who has the BPJS Old Age Guarantee (JHT) program which gets class III services. Cluster 2 has the male sex who has the BPJS Death Insurance (JKM) program who gets class I services. cluster 3 there are women who have the BPJS Death Guarantee program (JKM) who get class II types of services.
Application of Data Mining Correlation Between Family Socio-Economy And Student Achievement Level Sany Lubis, Fauzan Al An; Buaton, Relita; Sembiring, Hermansyah
Journal of Engineering, Technology and Computing (JETCom) Vol. 3 No. 1 (2024): JETCom (March 2024)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/jetcom.v3i1.141

Abstract

Learning achievement is the result of an achievement by students after going through the process of teaching and learning activities. Several factors influence student achievement, one of which is the family's socio-economic environmental factors. The family environment is very influential in the formation of children's character and also the child's mindset. The socio-economic level of the family has an influence on the success of children in achieving academic achievement. This study aims to determine the correlation between family socio-economic and student achievement at SMP Negeri 11 Binjai using the a priori method where this method helps the school and parents to more easily find out what factors are most dominant in influencing family socio-economic correlations to student achievement. From the 20 data tested, the best rule was obtained, namely if the parents of students with junior high school education worked as entrepreneurs and had an income of between IDR 1,000,000 - IDR 1,999,000. Then the student is not in the top 10 in his class with a supporting value of 10% and a certainty value of 100%
Data Mining Pengelompokan Pasien Rawat Inap Berdasarkan Kelas Bpjs Menggunakan Metode Clustering (Studi Kasus : Rumah Sakit Umum Daerah Dr. Rm. Djoelham Binjai) Lubis, Anjelia Alsar; Buaton, Relita; Ambarita, Indah
Jurnal Sistem Informasi Kaputama (JSIK) 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/jsik.v6i2.189

Abstract

RSUD Dr. R.M. Djoelham Kota Binjai merupakan lembaga penyedia jasa layanan kesehatan berdiri sejak tahun 1927 di kota Binjai yang menyediakan pelayanan rawat inap bagi pasien yang sedang sakit, kecelakaan maupun pemulihan kondisi (pasca operasi). RSUD Dr. R.M. Djoelham memberikan pelayanan rawat inap yang baik, dari segi pelayanan yang diberikan perawat, pelayanan medis, pelayanan kamar, maupun fasilitas lainnya. BPJS kesehatan membantu ketersediaan untuk semua kebutuhan biaya dokter, obat-obatan, rawat inap, sampai dengan tindakan operasi. Pengelompokkan pasien rawat inap berdasarkan kelas BPJS menjadi hal yang penting pada database rumah sakit terdiri dari banyak kelas BPJS yang digunakan dalam kegiatan rawat inap rumah sakit. Namun, dalam kegiatan ini masih susah untuk didentifikasikan karena disetiap harinya banyak pasien masuk. Teknik data mining dapat menggali data kasus yang berjumlah besar dan menghasilkan informasi tentang pengelompokkan pasien rawat inap berdasarkan kelas BPJS sesuai dengan clustering masing-masing.
Penerapan Sistem Pakar Menentukan Covid-19 Dengan Metode KNN (K Nearest Neighbor) Berbasis Web (Studi Kasus : RSU Sylvani) Haryanto, Septian; Buaton, Relita; Ambarita, Indah
Jurnal Sistem Informasi Kaputama (JSIK) 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/jsik.v6i2.198

Abstract

Covid-19 adalah virus yang baru muncul di wuhan pada akhir tahun 2019. Gejala yang di timbulkan oleh covid-19 bervariasi antara suhu tubu meningkat, demam, batuk dan lain nya. Untuk mengatasi faktor ketidakpastian dalam mendiagnosis gejala covid-19, system pakar dirancang untuk menemukan kasus serupa mengenai covid 19 tersebut. Gejala-gejala akan dimasukkan dan dicocokan dengan data penelitian untuk diolah dengan data latih, yaitu data lama pasien yang telah terdiagnosi. suatu sistem yang dapat mencegah sejak dini, sehingga membantu mengatasi penyakit yang disebabkan oleh virus covid-19 lebih dini. Subjek penelitian ini adalah sistem pakar untuk menentukan covid-19. Tahap pengembangan sistem dimulai dengan menganalisis kebutuhan sistem, merancang sistem, antara lain membangun basis pengetahuan, pengambilan tabel keputusan, tabel aturan, memonitor kesimpulan, merancang aliran data, diagram relasional entitas yang kemudian melakukan implementasi dan pengujian. dari sistem. Dengan black box test dan alpha test. Hasil penelitian menunjukkan bahwa aplikasi layak dan bermanfaat
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