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JARINGAN SYARAF TIRUAN UNTUK MEMPREDIKSI NILAI KELULUSAN SIDANG (STUDI KASUS : STMIK KAPUTAMA BINJAI ) Retni Noviyanti Siregar; Lina Arliana Nur Kadim; Yani Maulita
JSIK (Jurnal Sistem Informasi Kaputama) Vol 3, No 2 (2019): VOLUME 3, NOMOR 2, EDISI JULI 2019
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jsik.v3i2.166

Thesis session is a process that must be followed by a student in order to account for the thesis that has been done. Thesis trial scores determine student graduation, and student graduation rates are used as a measure of campus quality. The problem is that many students are depressed and afraid in the face of a thesis hearing, not a few among students who are stressed in facing thesis and some even delay the work of the thesis so that it affects the trial value obtained. Besides that there are students who have good IP but the trial value is not good, and vice versa. This method the Artificial Neural Network using the Backpropagation algorithm was chosen because it was able to predict the graduation value of the thesis trial based on input from the value of the semester IP from semester I to semester VII and the value of the trial. The study was conducted in two ways, namely training and testing. The training process aims to recognize or look for expected results by using a lot of training, so that it will produce the best pattern for training the data. After the training reaches the goal based on the best pattern, it will be tested with new data to see the accuracy between the targets using Matlab R2014a software. Based on the results of testing using Matlab R2014a software, the results are convergent, with a target error of 0.2. From the results of the training and the tests carried out, it was predicted that the graduation score of the thesis trial was predicted to be 0.8727. This research can also help predict the graduation score of thesis students at STMIK Kaputama Binjai

PENERAPAN DATA MINING PENGELOMPOKAN PESERTA BPJS KETENAGAKERJAAN BERDASARKAN PROGRAM YANG DIAMBIL MENGGUNAKAN METODE CLUSTERING Zema Zema; Yani Maulita; Lina Arliana Nur Kadim
JSIK (Jurnal Sistem Informasi 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: 10.1234/jsik.v6i2.839

Penyelenggaraan program jaminan sosial merupakan salah satu tanggung jawab dan kewajiban Negara, untuk memberikan perlindungan sosial ekonomi kepada masyarakat. Indonesia seperti halnya negara berkembang lainnya, mengembangkan program jaminan sosial berdasarkan funded social security, yaitu jaminan sosial yang didanai oleh peserta dan masih terbatas pada masyarakat pekerja di sektor formal. BPJS Ketenagakerjaan terus meningkatkan kompetensi di seluruh aspek pelayanan sambil mengembangkan berbagai program dan manfaat yang langsung dapat dinikmati oleh pekerja dan keluargan. Pekerja Bukan Penerima Upah (BPU) merupakan karyawan yang melakukan kegiatan atau usaha ekonomi secara mandiri untuk memperoleh penghasilan dari kegiatan atau usahanya. Permasalahan yang menghambat lamanya pendataan peserta BPJS Ketenagakerjaan adalah proses penentuan program jaminan sosial yang akan diambil oleh pekerja Bukan Penerima Upah (BPU) dari program yang diambil oleh peserta BPJS Ketenagakerjaan, permasalahan baru yang timbul adalah iuran yang dikeluarkan masih cukup besar untuk dibayarkan, sementara pendapatan yang dimiliki sangat kecil dan hanya cukup untuk kebutuhan sehari-hari bagi peserta. Data Mining merupakan suatu proses penambangan data dalam jumlah data yang sangat besar dengan menggunakan metode statistika, matematika, hingga memanfaatkan teknologi Artificial Intelligence terkini. Data mining dalam proses pengelompokan data dapat menggunkan metode pengelompokan yaitu metode Clustering. Sistem dirancang dengan aplikasi pemrograman MATLAB R2014a, setelah melakukan pengujian dengan sistem didapatkan hasil yaitu pada gurp 1 terdapat 370 data, grup 2 terdapat 359 data dan grup 3 terdapat 271 data dengan total keseluruhan data sebanyak 100 data peserta.

PELATIHAN PEMBUATAN ECO ENZYM SECARA ONLINE DARI SAMPAH BUAH DAN SAYURAN SEBAGAI DISINFECTANT DAN HAND SANITIZER HERBAL KEPADA GURU-GURU SMK PUSAT KEUNGGULAN Lina Arliana Nur Kadim; Indah Ambarita; Yani Maulita; Novriyenni Novriyenni; Magdalena Simanjuntak; Suci Rahmadani; Ahmad Fauzi; Anton Sihombing
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 2 No 1 (2022): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Garbage is a waste material as a result of human activities which is a material that can no longer be used. Waste is solid waste consisting of organic and inorganic substances which are considered useless and must be managed so as not to harm the environment. Including organic waste, one of which is waste that comes from kitchen waste in every household, namely fruit and vegetable peel waste. Waste processing to reduce pollution and preserve the environment is to process waste into Eco Enzymes. The purpose of making Eco Enzyme is to process enzymes from organic waste that are usually thrown into trash cans into disinfectants and hand sanitizers.

PENERAPAN ALGORITMA APRIORI MENENTUKAN KORELASI DATA PENJUALAN PUPUK (STUDI KASUS : PT. KARUNIA ROTORINDO TANI) Ardianti Ardianti; Novriyenni Novriyenni; Lina Arliana Nur Kadim
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.v3i3.1195

Currently information technology is developing so fast that the need for information is increasing. Information will be of no value if it is not managed properly. However, if the available data is large, conventional methods will no longer be able to analyze data to explore existing potentials. Therefore we need a method that can analyze, summarize and extract data to become useful information. In order to find out what fertilizers are often purchased by consumers, it is necessary to perform analysis techniques from data on sales using the Apriori algorithm method to determine combinations between item-sets from fertilizer sales transaction data at PT. Karunia Rotorindo Tani. If T1 and P3 then BT1 with support value = 20% and 100% confidence and S*C value = 20% if the T1 soil type is (Alluvial Soil) then the customer will buy P3 fertilizer, namely (Organic Formula Palm Oil Specific Fertilizer) with the brand name the fertilizer that many of these customers buy is BT1 (BT_Kelapa Sawit). with a supporting value of 20%, a certainty value of 100%.

PENERAPAN METODE AHP DALAM PENGAMBILAN KEPUTUSAN UNTUK PENILAIAN KOMPETENSI SOFT SKILL KARYAWAN Nursakinah; Maulita, Yani; Nur Kadim, Lina Arliana
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.v2i3.117

Bagi pengusaha atau manajemen puncak suatu perusahaan, kualitas sumber daya manusia termasuk soft skill merupakan faktor yang paling penting untuk diperhatikan agar dapat menjalankan bisnis secara optimal. Dalam mengevaluasi kompetensi soft skill karyawan PT Mitra Mas biasanya melakukan penilaian soft skill karyawan yang dilakukan minimal 2 kali dalam setahun. Dalam proses penilaian kompetensi soft skill karyawan di PT Mitra Mas ini masih belum optimal dikarenakan harus membaca dan mengisi dokumen secara tertulis serta melakukan perhitungan manual dan dalam penilaiannya juga masih subjektif. Tujuan penelitian ini adalah membangun sebuah Sistem Pendukung Keputusan penilaian kompetensi soft skill karyawan berdasarkan kriteria-kriteria yang telah ditentukan oleh perusahaan untuk memudahkan perusahaan dalam mengevaluasi kompetensi soft skill karyawan. Metode AHP (Analytical Hierarchy Process) dipilih karena metode AHP melakukan seleksi dengan proses pembentukkan hierarki terlebih dahulu, sehingga memudahkan peneliti dalam proses penelaian. Hasil urutan perangkingan nilai akhir karyawan PT Mitra Mas antara perhitungan sistem dan perhitungan manual dengan metode AHP adalah sama.

JARINGAN SYARAF TIRUAN UNTUK MEMPREDIKSI NILAI KELULUSAN SIDANG (STUDI KASUS : STMIK KAPUTAMA BINJAI ) Siregar, Retni Noviyanti; Kadim, Lina Arliana Nur; Maulita, Yani
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 3 No. 2 (2019): Volume 3, Nomor 2, Juli 2019
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v3i2.771

Thesis session is a process that must be followed by a student in order to account for the thesis that has been done. Thesis trial scores determine student graduation, and student graduation rates are used as a measure of campus quality. The problem is that many students are depressed and afraid in the face of a thesis hearing, not a few among students who are stressed in facing thesis and some even delay the work of the thesis so that it affects the trial value obtained. Besides that there are students who have good IP but the trial value is not good, and vice versa. This method the Artificial Neural Network using the Backpropagation algorithm was chosen because it was able to predict the graduation value of the thesis trial based on input from the value of the semester IP from semester I to semester VII and the value of the trial. The study was conducted in two ways, namely training and testing. The training process aims to recognize or look for expected results by using a lot of training, so that it will produce the best pattern for training the data. After the training reaches the goal based on the best pattern, it will be tested with new data to see the accuracy between the targets using Matlab R2014a software. Based on the results of testing using Matlab R2014a software, the results are convergent, with a target error of 0.2. From the results of the training and the tests carried out, it was predicted that the graduation score of the thesis trial was predicted to be 0.8727. This research can also help predict the graduation score of thesis students at STMIK Kaputama Binjai

Pengelompokan Data Keluhan Masyarakat Terhadap Fasilitas Umum diKota Binjai Menggunakan Metode Clustering Dea Syafitri; Yani Maulita; Lina Arlianan Nur Kadim
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 3 (2024): SEPTEMBER : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v2i3.2381

Public Facilities in Binjai City are infrastructure that is provided free of charge that can be enjoyed by the community and is one of the vacation spots that does not need to spend a lot of money, but there are several infrastructure facilities that are not maintained, dirty and have damage from minor to the most severe, even infrastructure, so that it greatly affects the comfort of the community. In the process of maintaining public facilities in Binjai City in accordance with the Binjai City Regional Regulation Letter Number 1 of 2024 concerning public facilities used for public purposes, including for educational, health, worship, socio-cultural, sports and recreational activities (Hamzah, 2024). The Environmental Service of Binjai City really needs input from the community to continue to help maintain and care for the facilities provided so that the agency can handle and respond to community complaints such as a lot of garbage, dirty, rusty, muddy facilities and others as well as input reported by the community on the cleanliness of public facilities in Binjai City. Therefore, the agency needs a system using the clustering method that can manage community complaint data to be used as information that can assist the agency in taking quick action to deal with the problem of community complaints about public facilities in Binjai City. Based on the research conducted on the case experiment above from testing 20 data, there are 3 groups, namely group 1 there are 5 data and group 2 there are 9 data, and group 3 there are 6 data which can be known that in cluster 2 the group of public complaints about public facilities in Binjai City with public facilities (X) Studion Field, with complaints (Y) Becek, Banyak Sampah, & Berkarat, with Advice (Z) Repair & Maintain Cleanliness.

DIKLAT MOTIVASI BERWIRAUSAHA SISWA SMK NUR AZIZI TANJUNG MORAWA: STMIK Kaputama Ambarita, Indah; Nur Kadim, Lina Arliana; Simanjuntak, Magdalena
Jurnal Abdimas Mutiara Vol. 3 No. 1 (2022): JURNAL ABDIMAS MUTIARA (In Press)
Publisher : Universitas Sari Mutiara Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Tidak ada bangsa yang sejahtera dan dihargai oleh bangsa lain tanpa kemajuan ekonomi. Kemajuan ekonomi bisa dicapai jika ada spirit kewirausahaan yang kuat dari masyarakatnya. Salah satu faktor yang menyebabkan suatu negara bisa maju yaitu ketika jumlah wirausahawan yang terdapat di negara tersebut berjumlah 2% dari populasi penduduknya. Di Indonesia ditemukan bahwa hampir 75% responden tidak memiliki rencana yang jelas setelah lulus. Tidak mengherankan jika setiap tahunnya selalu muncul pengangguran terdidik di Indonesia yang angkanya semakin meningkat. Terdapat kecenderungan bahwa lulusan SMK di Indonesia lebih senang milih bekerja nyaman, sementara lapangan kerja di sektor pemerintah dan sektor swasta tidak memungkinkan menyerap semua tenaga kerja lulusan SMK di Indonesia. Salah satu upaya dalam mengurangi tingkat pengangguran tinggi di Indonesia yaitu dengan menciptakan lulusan-lulusan SMK yang tidak hanya memiliki orientasi sebagai job seeker namun job maker atau yang disebut wirausaha. Untuk memulai menjadi seorang wirausaha, setiap siswa SMK harus memiliki impian yang kokoh yang dibangun tidak dalam waktu singkat. Impian ini sangat penting mengingat resiko dari wirausaha tidaklah kecil. Bila siswa SMK tidak memiliki impian yang kokoh maka sangat mungkin baginya untuk cepat menyerah. Konsep dasar yang harus disadari terlebih dahulu yaitu sukses itu bukan sebuah kebetulan, namun sukses itu by design.

Penerapan K-Means Clustering untuk Menentukan Lokasi Promosi Penerimaan Mahasiswa Baru : (Studi Kasus: STMIK Kaputama Kota Binjai) Ronauli Silaban; Achmad Fauzi; Lina Arliana Nur Kadim
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 2 No. 5 (2024): September : 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.v2i5.322

The process of accepting new students generates a lot of data in the form of profiles of students who register. From year to year there is an increase in the number of prospective new students who come from several areas in Binjai City, Langkat Regency and surrounding areas, so the location of the socialization of new student admissions promotions every year is increasing and wider. And from several schools that have been visited and are expected to provide new prospective students, in fact, it is not proportional to the final number of prospective students who register. In this study, applying the K-Means Clustering algorithm using 3 variables namely, region, school origin, major. In determining the location of new student admissions promotions, the promotion team first identifies what factors will influence the determination of promotional locations ranging from region, school origin and majors that are considered to be set as promotional locations. Based on the results of grouping new student admission data of STMIK Kaputama Binjai using the K-means Clustering method from 20 data that has been processed, 3 clusters and 3 iterations are produced where cluster 1 has 9 data, cluster 2 has 2 data and cluster 3 has 9 data.

Penerapan Algoritma K-Nearest Neighbor untuk Klasifikasi Usaha Masyarakat Berdasarkan Jenis Izin Usaha Brema Daniel Ginting; Yusfrizal Yusfrizal; Lina Arliana Nur Kadim
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 4 (2024): Oktober : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v2i4.233

Business legality is the identity of a business that legalizes a business so that it is recognized by the community. Business legality must be valid according to applicable laws and regulations so that the business can be protected by various documents that are valid in the eyes of the law. One of the supporting factors for the sustainability of a business is influenced by the existence of legal elements of the business being run. Business permits that must be owned by the community are a business establishment deed, business entity NPWP, trade business license (SIUP), company domicile certificate (SKDP) and business registration number (NIB). The increase in community businesses in Sei Bingai District, Langkat Regency has triggered many business permits that are not directly supervised by the local government. Community business permits are important documents in supervising the running of these community businesses. The types of businesses in Sei Bingai District also vary, such as tourism, C mining, trade, factories and so on.

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