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Journal : Journal Of Artificial Intelligence And Software Engineering

Workshop Management Application Design At Pt Abc Using Rational Unified Process Method Markopa, Andre; Rais, Falatehan; Dafid, Dafid
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6468

Abstract

Proses bisnis yang berjalan pada PT ABC saat ini masih memiliki kekurangan yang dapat menghambat berjalannya proses bisnis dan pengambilan keputusan. Oleh karena itu, perancangan aplikasi ini dilakukan dengan bertujuan untuk membantu proses pencatatan dan perhitungan laporan serta transaksi agar pencatatan serta perhitungan laporan harian dan bulanan menjadi lebih cepat dan efisien serta tidak rentan terhadap kesalahan. Metode Pengembangan yang digunakan pada perancangan ini adalah metode RUP (Rational Unified Process), yang dimana prosesnya memiliki empat tahap utama yaitu inception, elaboration, construction, dan transition. Perancangan ini menghasilkan sebuah aplikasi manajemen bengkel yang dapat membantu proses pencatatan dan perhitungan laporan serta transaksi agar pencatatan serta perhitungan laporan harian dan bulanan menjadi lebih cepat, efisien dan tidak rentan terhadap kesalahan.
Application of K-Means Clustering Algorithm for Disease Grouping at Blessing Dental Care Clinic Fransiska, Cintiya Aulya; Dafid, Dafid
Journal of Artificial Intelligence and Software Engineering Vol 5, No 3 (2025): September
Publisher : Politeknik Negeri Lhokseumawe

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

Abstract

Blessing Dental Care Clinic is a clinic that provides dental practice services and general practitioner practices located in Palembang. This clinic offers general care and dental care managed by experienced doctors in their fields. The focus of the data used is medical record data, especially from general practice. Grouping large data into several groups based on similar pattern characteristics by utilizing the K-Means Clustering algorithm in CRISP-DM data mining was chosen to be more effective in handling various complaints of various diseases through the Clustering process. The results showed that the form of cluster 1 was 220 dominant data in the respiratory disease category, cluster 2 was 335 dominant data in the cardiovascular disease category, cluster 3 was 584 dominant data in the cardiovascular disease category, cluster 4 was 363 dominant data in respiratory disease, cluster 5 was 70 dominant data in respiratory disease, cluster 6 was 254 dominant data in cardiovascular disease and cluster 7 was 165 dominant data in ENT disease. In cluster 7 with an SSE value of 3189.16, the decrease is getting smaller and the spread pattern is starting to be optimal with a tendency for the pattern to be more spread out.