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PERANCANGAN SISTEM E-VOTING UNTUK PEMILIHAN KETUA OSIS SMP NEGERI 10 PEKANBARU Syam, Febrizal Alfarasy; Darmayunata, Yuvi; Afriansyah, Afriansyah
ZONAsi: Jurnal Sistem Informasi Vol 1 No 2 (2019): Publikasi Artikel ZONAsi : Jurnal Sistem Informasi, September 2019
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v1i2.2809

Abstract

SMP Negeri 10 Pekanbaru setiap tahunnya melakukan pemilihan Ketua OSIS. Proses pemilihan Ketua OSIS SMP Negeri 10 Pekanbaru dilakukan dengan cara voting oleh seluruh siswa secara langsung. Namun voting yang dilakukan masih secara konvensional yaitu pemilihan masih menggunakan kertas sebagai sarana untuk pemilih menentukan pilihannya dan dalam perhitungan suara hasil pemilihan juga dilakukan secara manual, sehingga akan memerlukan biaya yang besar dan waktu yang cukup lama untuk mengetahui hasilnya. Pemanfaatan sistem e-voting, merupakan solusi yang diberikan penulis untuk meyelesaikan masalah tersebut. Pada tahap analisa dan perancangan penulis menggunakan metode pendekatan Object Oriented  Analysis  and  Design (OOAD). Sedangkan pemodelan sistem menggunakan pendekatan UML (Unified Modelling Language). Hasil dari penelitian ini diharapankan dapat menyelesaikan masalah-masalah tentang proses pemilihan Ketua OSIS SMP Negeri 10 Pekanbaru sehingga dapat dilaksanakan secara efektif, efisien, cepat dan transparan
The Influence of Quality Assurance and Knowledge Management on Higher Education Accreditation Performance Febriadi, Bayu; Putra, Pandu Pratama; Syam, Febrizal Alfarasy
IJISTECH (International Journal of Information System and Technology) Vol 8, No 1 (2024): The June edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i1.348

Abstract

With the issuance of Permendikbud No 53 Tahun 2023 concerning the accreditation transformation mechanism and Quality Assurance System for higher education, it is hoped that existing study programs at state universities and private universities can adjust the direction of accreditation performance policies and Higher Education Performance Indicators. Lancang Kuning University currently has 32 study programs consisting of 11 new study programs that still have accreditation with minimum scores. So it is hoped that the study program will respond well to higher education accreditation performance. This is in line with the expectations of Lancang Kuning University to ensure a culture of quality in achieving the vision and mission of higher education. The method used in this research is quantitative by determining Quality Assurance and Knowledge Management variables in influencing the accreditation performance of universities and study programs. Quality Assurance 0.790 coefficient influences accreditation performance and Knowledge Management influence 0.778 coefficient influences the accreditation performance of Lancang Kuning University.
The Influence of Quality Assurance and Knowledge Management on Higher Education Accreditation Performance Febriadi, Bayu; Putra, Pandu Pratama; Syam, Febrizal Alfarasy
IJISTECH (International Journal of Information System and Technology) Vol 8, No 1 (2024): The June edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i1.348

Abstract

With the issuance of Permendikbud No 53 Tahun 2023 concerning the accreditation transformation mechanism and Quality Assurance System for higher education, it is hoped that existing study programs at state universities and private universities can adjust the direction of accreditation performance policies and Higher Education Performance Indicators. Lancang Kuning University currently has 32 study programs consisting of 11 new study programs that still have accreditation with minimum scores. So it is hoped that the study program will respond well to higher education accreditation performance. This is in line with the expectations of Lancang Kuning University to ensure a culture of quality in achieving the vision and mission of higher education. The method used in this research is quantitative by determining Quality Assurance and Knowledge Management variables in influencing the accreditation performance of universities and study programs. Quality Assurance 0.790 coefficient influences accreditation performance and Knowledge Management influence 0.778 coefficient influences the accreditation performance of Lancang Kuning University.
Clustering Of Library’s Patron Behavior Using Machine Learning Monika, Winda; Nasution, Arbi Haza; Syam, Febrizal Alfarasy; Wijesundara, Chiranthi
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 16 No. 1 (2025): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v16i1.19680

Abstract

Libraries collect a lot of important transaction data, but they rarely use this information to improve how consumers interact with them. This work tries to bridge this gap by offering a novel use of machine learning to analyze and classify library patron behavior. Customers were categorized based on their age range, checkouts, and renewals using the KMeans clustering technique. Dimensionality reduction methods like PCA and t-SNE were used to visually clarify the generated patterns. Our research revealed three different user groups: Rare Borrowers, who typically make 5.4 checkouts and 2.0 renewals; Occasional Borrowers, who typically make 20.8 checkouts and 7.1 renewals; and Frequent Borrowers, who often make 50.3 checkouts and 15.4 renewals. The clustering model performed quite well, as evidenced by its Calinski-Harabasz Index of 320.12, Davies-Bouldin Index of 0.45, and Silhouette Score of 0.62. Beyond these metrics, the study’s novelty lies in its practical implications—offering libraries a data-driven framework to tailor services, improve user satisfaction, and optimize resource allocation. This study highlights the transformative potential of machine learning in library science offering a data-driven framework for libraries to personalize services, optimize book recommendations, and enhance outreach efforts based on patron behavior. By segmenting users, libraries can better allocate resources and improve user experience. Limitation of this study lies on the data bias which may affect generalizability due to demographic differences across libraries. Additionally, KMeans clustering assumes predefined clusters, which may not fully capture nuanced behaviors.
Rancang Bangun Sistem Pelayanan Publik Pada Polsek Padang Barat Berbasis Web Dengan Php Dan Database Mysql Hadi, Abrar; Putra, Pandu Pratama; Syam, Febrizal Alfarasy; Febriadi, Bayu
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 5, No 1 (2023): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v5i1.275

Abstract

Police in the SPKT (Integrated Police Service Center) have a function that serves complaints from people who are involved in criminal acts, namely reports of fraud, robbery, embezzlement, robbery, loss of valuables, and so on. Due to complaints from the public at this time, the community needs fast service at the SPKT section. Because SPKT is the spearhead of the police service in providing services to the community to improve and facilitate the services needed by software. At the West Padang Police, if the community makes a complaint or request to the SPKT (Integrated Police Service Center), officers still use a conventional or un-computerized system the weakness of this system is that it is very possible that during the process there is an error in recording, inaccurate reports made, delays in finding the required data STTLP (Police Report Receipt), the officer must rewrite the book for archiving, then if the public makes a second request the officer must rewrite the applicant's data because it takes a long time to search for data.