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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JSI (Jurnal sistem Informasi) Universitas Suryadarma Jurnal Mantik Tematik : Jurnal Teknologi Informasi Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Kajian Ilmiah Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat IICS Journal of Students‘ Research in Computer Science (JSRCS) Jurnal Abdimas Ekonomi Dan Bisnis (JAMEB) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan SIGMA: Information Technology Journal Jurnal Sistim Informasi dan Teknologi Jurnal Pengabdian Pelitabangsa International Journal of Information Technology and Computer Science Applications (IJITCSA) Jurnal Sistem Informasi Indonesian Journal of Education And Computer Science Jurnal Inovasi dan Pengembangan Hasil Pengabdian Masyarakat VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Journal of Computer Science Contributions (Jucosco) The Indonesian Journal of Computer Science Journal of Informatics and Information Security
Priatna , Wowon
Informatika, Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Journal : Journal of Students‘ Research in Computer Science (JSRCS)

 1 
Algoritma K-Means Clustering Untuk Menentukan Rekomendasi Pemberian Beasiswa Bagi Siswa Berprestasi Febry Sandrian Sagala; Mugiarso; Wowon Priatna
Journal of Students‘ Research in Computer Science Vol. 2 No. 2 (2021): November 2021
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (438.099 KB) | DOI: 10.31599/jsrcs.v2i2.840

Abstract

Scholarships are given to underprivileged students or outstanding students through a selection involving certain criteria. The criteria include the average value of report cards, parents' income, distance from home to school, number of dependents of parents, condition of the house, and status of the house. This study aims to assist the selection team in determining the award of scholarships so that they can provide appropriate and inappropriate recommendations, taking into account 6 criteria. The problem is that the existing scholarships are only given to students who do not have a father. The K-Means Clustering Algorithm can help Cluster students who are not eligible and eligible to get scholarship recommendations. The dataset used was 145 instances from the MAS scholarship selection committee. Attaqwa 02 Babylon. The data is calculated and tested using the K-Means Clustering algorithm. The results of the test were 32 people were recommended as eligible and 113 people were not eligible. The K-Means Clustering Algorithm can help the selection team to determine the scholarship award.   Keywords: K-Means Clustering Algorithm, Scholarship Award, Students.   Abstrak   Beasiswa diberikan kepada siswa yang kurang mampu atau siswa berprestasi melalui seleksi yang melibatkan kriteria-kriteria tertentu. Kriterianya antara lain nilai rata-rata rapot, penghasilan orang tua, jarak rumah ke sekolah, jumlah tanggungan orang tua, kondisi rumah, dan status rumah. Penelitian bertujuan untuk membantu tim penyeleksi dalam menetukan pemberian beasiswa sehingga dapat memberikan rekomendasi layak dan tidak layak, dengan pertimbangan 6 kriteria. Masalahnya beasiswa yang ada hanya diberikan kepada siswa yang tidak memiliki Ayah. Dengan Algoritma K-Means Clustering dapat membantu pembuatan Clustering siswa yang tidak layak dan layak untuk mendapatkan rekomendasi beasiswa. Dataset yang digunakan sebanyak 145 instance yang berasal dari panitia seleksi beasiswa MAS. Attaqwa 02 Babelan. Data tersebut dihitung serta pengujiannya menggunakan algoritma K-Means Clustering. Hasil pengujian sebanyak 32 orang direkomendasikan layak dan 113 orang tidak layak. Dengan Algoritma K-Means Clustering dapat membantu tim seleksi untuk menetukan pemberian beasiswa.   Kata Kunci: Algoritma K-Means Clustering, Pemberian Beasiswa, Siswa.
Penentuan Pola Frekuensi Jenis Perawatan Kecantikan Berbasis Web Menggunakan Algoritma Apriori (Studi Kasus: Peterson Salon Bekasi) Herlawati Herlawati; Rahmadya Trias Handayanto; Sri Rejeki; Wowon Priatna; Prima Dina Atika; Syahbaniar Rofiah; Endang Retnoningsih; Faisal Adi Saputra; Galih Apriansha Pradana
Journal of Students‘ Research in Computer Science Vol. 3 No. 2 (2022): November 2022
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jsrcs.v3i2.1381

Abstract

Currently, technology can affect services in any field, both in areas such as salon services and sales of clothing products. How to plan a marketing strategy using the web based on service transaction data and products that are most often chosen by customers. Therefore, an information system for determining frequency patterns is needed using the website-based Apriori Algorithm method. The results of research on salons based on the type of beauty treatment obtained for the type of treatment with a minimum confidence = 70%, the first confidence value is 63% if the customer chooses to wash (shampoo), the customer chooses scissors, the second the confidence value is 100%, if the customer chooses to blow then chooses also cut, and the third confidence value is 86% if the customer chooses creambath then the customer chooses to cut too. Meanwhile at the shop clothes determining the frequency pattern of types of clothes with a minimum value of confidence = 70% so that the results include if a customer buys a veil, the customer buys a robe with a confidence value of 71.43% and if a customer buys khimar then the customer will also buy a robe with a confidence value of 78, 57%. With these results salon and clothing store owners can determine marketing strategies by providing the right product and service recommendations to customers. Keywords: Apriori Algorithm, Beauty Care, Recommendations, Sales   Abstrak Saat ini teknologi dapat mempengaruhi pelayanan dalam bidang apapun seperti jasa salon maupun penjualan produk pakaian. Bagaimana merencanakan strategi pemasaran menggunakan web berdasarkan data transaksi layanan dan produk yang paling sering dipilih oleh pelanggan. Oleh karena itu dibutuhkan sistem informasi penentuan pola frekuensi menggunakan metode Algoritma Apriori berbasis website. Hasil penelitian pada salon berdasarkan jenis perawatan kecantikan diperoleh untuk jenis perawatan dengan minimum confidence=70% yang pertama nilai confidence sebesar 63% jika pelanggan memilih cuci (keramas) maka pelanggan memilih gunting, yang kedua nilai confidence sebesar 100% jika pelanggan memilih blow maka memilih digunting juga, dan yang ketiga nilai confidence 86% jika pelanggan memilih creambath maka pelanggan memilih digunting juga. Sedangkan pada toko pakaian penentuan pola frekuensi jenis baju dengan nilai minimum confidence= 70% sehingga mendapatkan hasil diantaranya jika pelanggan membeli kerudung maka pelanggan membeli gamis dengan nilai confidence sebesar 71,43%  dan  jika  pelanggan  membeli  khimar maka pelanggan juga akan membeli gamis dengan nilai confidence sebesar 78,57%. Dengan hasil tersebut pemilik salon dan toko pakaian dapat menentukan strategi pemasaran dengan memberikan rekomendasi jasa dan produk yang tepat kepada pelanggan. Kata kunci: Algoritma Apriori, Penjualan, Perawatan Kecantikan, Rekomendasi
Algoritma K-Means Clustering Untuk Rekomendasi Pemberian Beasiswa Bagi Siswa Berprestasi Sagala, Febry Sandrian; Mugiarso, Mugiarso; Priatna, Wowon
Journal of Students‘ Research in Computer Science Vol. 2 No. 2 (2021): November 2021
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jdy9g441

Abstract

Scholarships are given to underprivileged students or outstanding students through a selection involving certain criteria. The criteria include the average value of report cards, parents' income, distance from home to school, number of dependents of parents, condition of the house, and status of the house. This study aims to assist the selection team in determining the award of scholarships so that they can provide appropriate and inappropriate recommendations, taking into account 6 criteria. The problem is that the existing scholarships are only given to students who do not have a father. The K-Means Clustering Algorithm can help Cluster students who are not eligible and eligible to get scholarship recommendations. The dataset used was 145 instances from the MAS scholarship selection committee. Attaqwa 02 Babylon. The data is calculated and tested using the K-Means Clustering algorithm. The results of the test were 32 people were recommended as eligible and 113 people were not eligible. The K-Means Clustering Algorithm can help the selection team to determine the scholarship award.
Penentuan Pola Frekuensi Menggunakan Algoritma Apriori pada Sistem Informasi Berbasis Web Herlawati , Herlawati; Handayanto , Rahmadya Trias; Rejeki , Sri; Priatna , Wowon; Atika , Prima Dina; Rofiah , Syahbaniar; Retnoningsih , Endang; Saputra , Faisal Adi; Pradana , Galih Apriansha
Journal of Students‘ Research in Computer Science Vol. 3 No. 2 (2022): November 2022
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/nxkyrb30

Abstract

Currently, technology can affect services in any field, both in areas such as salon services and sales of clothing products. How to plan a marketing strategy using the web based on service transaction data and products that are most often chosen by customers. Therefore, an information system for determining frequency patterns is needed using the website-based Apriori Algorithm method. The results of research on salons based on the type of beauty treatment obtained for the type of treatment with a minimum confidence = 70%, the first confidence value is 63% if the customer chooses to wash (shampoo), the customer chooses scissors, the second the confidence value is 100%, if the customer chooses to blow then chooses also cut, and the third confidence value is 86% if the customer chooses creambath then the customer chooses to cut too. Meanwhile at the shop clothes determining the frequency pattern of types of clothes with a minimum value of confidence = 70% so that the results include if a customer buys a veil, the customer buys a robe with a confidence value of 71.43% and if a customer buys khimar then the customer will also buy a robe with a confidence value of 78, 57%. With these results salon and clothing store owners can determine marketing strategies by providing the right product and service recommendations to customers.
Co-Authors -, Rasim ., Rasim Ade Iriani Adi Setiawan Agung Nugroho Agung Nugroho Agus Hidayat Agus Hidayat Aida Fitriyani, Aida Ajif Yunizar Pratama Yusuf Alexander, Allan D Alexander, Allan D. Alhillah, Yumaris Alfi Andi Lawrence Hutahaean, Johanes Andi Rahman Andri Fajriya Andry Fadjriya Annisa Oktavianti Hermadi Aprilyana, Dhea Putri Asep R. Hamdani Asep Ramdhani M Asep Ramdhani Mahbub Atika , Prima Dina Dimas Abimanyu Prasetyo Dwi Budi Srisulistiowati Dwipa Handayani Eka Nur A’ini Endang Retnoningsih Enggar Putera, dkk, Diaz Faisal Adi Saputra Fajar Mukharom Fathurrazi, Ahmad Febry Sandrian Sagala Fefbiansyah Hasibuan Galih Apriansha Pradana Hadi Kusmara Hamdani, Asep R. Hendarman Lubis Herlawati Herlawati Hindriyanto Dwi Purnomo Ikhsan Romli Ilham Rizky Widianto Irwan Sembiring Ismaniah, Ismaniah Iwan Setyawan Joni Warta Joni Warta Joniwarta Joniwarta Jumi Saroh Hidayat Kapriadi, Engkap Karyaningsih, Dentik Khoirunnisaa, Nabiilah Kustanto , Prio Lestari, Tyastuti Sri Lubis, Hendarman M. Fadhli Nursal Mahbub, Asep Ramdhani Mayadi Mayadi Meutia, Kardinah Indrianna Mugiarso Mugiarso, Mugiarso Muhammad Khaerudin Noe’man,, Achmad Nurjeli Nurjeli Pradana , Galih Apriansha Prima Dina Atika Purnomo, Rakhmat Rahmadya Trias Handayanto Rakhmat Purnomo Rasim Rejeki , Sri Retnoningsih , Endang Rinaldi Tunnisia Ritzkal, Ritzkal Sagala, Febry Sandrian Saputra , Faisal Adi Silvi - Siti Setiawati SITI SETIAWATI Siti Setiawati Siti Setiawati, Andika Yusuf Hidayat Sri Lestari, Tyastuti Sri Rejeki Sudiantini, Dian Sulistiyo, Dwi Suryadi Syahbaniar Rofiah Tb Ai Munandar, Tb Ai Theopillus J. H. Wellem Tri Dharma Putra Tri Dharma Putra Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Widianto, Ilham Rizky Wiyanto Wiyanto