M, Tupan Tri
Unknown Affiliation

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

PENERAPAN DATA MINING UNTUK MEMPREDIKSI STOK OBAT MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS DI APOTEK KLINIK PRATAMA YAKRIJA Hariansyah, Hariansyah; Rizal, Rizal; M, Tupan Tri; Orlando, Ray
Infotech: Journal of Technology Information Vol 10, No 1 (2024): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v10i1.274

Abstract

Pharmacies and drug stores are places where consumers can buy medicine. Pharmacies usually have licensed pharmacists who provide advice on medication use, provide consultation services, and fill prescriptions. Drug stores generally provide over-the-counter medicines without a prescription. The drug sales industry refers to the economic sector related to the production, distribution, and sale of drugs. Pratama Yakrija Clinic Pharmacy is located at Jalan Anggrek Rosliana VII No. D24, Kemanggisan, Palmerah District, West Jakarta City. It is a clinical pharmacy that serves various drug and health product needs for patients. As an active pharmacy, Pratama Yakrija Clinical Pharmacy aims to improve service to patients and efficiency in managing drug supplies. Drug sales in pharmacies are often influenced by various factors, such as seasons, health trends, promotions, and changes in consumer behavior. The problem at the Yakrija clinic is that the supply of medicines that are needed by the community are often empty, while medicines that are less needed are in abundance in the warehouse. The unavailability of the medicine needed certainly disappointed the people who at that time really needed the medicine. Meanwhile, an abundance of drugs that are not needed will cause losses because the drugs have expired due to being stored in the warehouse for too long. The aim of the research is to predict the stock of selling and unselling drugs and to determine the level of accuracy of the K-Nearest Neighbors algorithm in predicting drug stock at the Pratama Yakrija clinic pharmacy. The author uses the K-Nearest Neighbors algorithm in this research. By using accurate predictions, Pratama Yakrija Clinical Pharmacy can identify drug sales trends and patterns, and plan more effective marketing strategies. Pharmacies can also avoid losses caused by unsold stock or shortages of drugs that customers are interested in. The research results of the K-Nearest Neighbors algorithm can be used to predict selling and unsold drug stocks and the accuracy level of the K-Nearest Neighbors algorithm is 91.08%.ABSTRAKApotek dan toko obat merupakan tempat-tempat di mana konsumen dapat membeli obat. Apotek biasanya memiliki apoteker yang berlisensi yang memberikan nasihat mengenai penggunaan obat, menjalankan layanan konsultasi, dan mengisi resep obat. Toko obat umumnya menyediakan obat-obatan yang dijual bebas tanpa resep. Industri penjualan obat merujuk pada sektor ekonomi yang terkait dengan produksi, distribusi, dan penjualan obat. Apotek Klinik Pratama Yakrija beralamat di Jalan Anggrek Rosliana VII No. D24, Kemanggisan, Kecamatan Palmerah, Kota Jakarta Barat. Merupakan sebuah apotek klinik yang melayani berbagai kebutuhan obat dan produk kesehatan bagi pasien. Sebagai apotek yang aktif, Apotek Klinik Pratama Yakrija memiliki tujuan untuk meningkatkan pelayanan kepada pasien dan efisiensi dalam pengelolaan persediaan obat. Penjualan obat di apotek seringkali dipengaruhi oleh berbagai faktor, seperti musim, tren kesehatan, promosi, dan perubahan perilaku konsumen. Permasalahan yang ada pada klinik yakrija adalah persediaan obat yang sedang dibutuhkan oleh masyarakat seringkali stoknya kosong sedangkan obat yang kurang dibutuhkan justru stoknya melimpah di gudang. Ketidaktersediaan obat yang dibutuhkan, tentunya membuat kecewa masyarakat yang saat itu sedang sangat membutuhkan obat tersebut. Sedangkan melimpahnya obat yang kurang dibutuhkan akan menimbulkan kerugian karena obat sudah kadaluwarsa akibat terlalu lama tersimpan di gudang. Tujuan penelitian adalah untuk memprediksi stok obat laku dan tidak laku dan untuk mengetahui tingkat akurasi algoritma K-Nearest Neighbors dalam memprediksi stok obat pada apotek klinik pratama yakrija. Algoritma K-Nearest Neighbors yang penulis gunakan pada penelitian ini. Dengan menggunakan prediksi yang akurat, Apotek Klinik Pratama Yakrija dapat mengidentifikasi tren dan pola penjualan obat, serta merencanakan strategi pemasaran yang lebih efektif. Apotek juga dapat menghindari kerugian yang disebabkan oleh stok yang tidak terjual atau kekurangan obat yang diminati oleh pelanggan. Hasil Penelitian algoritma K-Nearest Neighbors dapat digunakan Untuk memprediksi stok obat laku dan tidak laku dan tingkat akurasi algoritma K-Nearest Neighbors adalah sebesar 91,08%.
KOMPARASI ALGORITMA DECISION TREE, NAIVE BAYES DAN K-NEAREST NEIGHBOR UNTUK MENENTUKAN KUALITAS UDARA DI PROVINSI DKI JAKARTA Irwansyah, Irwansyah; Wiranata, Ade Davy; M, Tupan Tri
Infotech: Journal of Technology Information Vol 9, No 2 (2023): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v9i2.203

Abstract

Air quality in DKI Jakarta Province refers to the state and cleanliness of the air in the area at a given time. The type and concentration of air pollutants are among the indicators used to assess air quality. DKI Jakarta's air pollution is severe, causing respiratory irritation, respiratory illnesses, and long-term health issues such as cardiovascular disease and lung cancer. Air pollution can also harm the environment by limiting visibility and harming ecosystems. The problem with the research is that no appropriate and relevant features for predicting air quality were used. The goal of this study is to identify and compare algorithms with the highest accuracy between decision trees. In determining air quality, naive Bayes and k-nearest neighbor are used. According to the findings of the K-5fold evaluation process performed with the RapidMiner tool, the accuracy of the Decision Tree algorithm was 95.89%, the accuracy of the Nave Bayes algorithm was 93.15%, and the accuracy of the K-NN algorithm was 91.78%. Based on these findings, the decision tree method has the greatest or best accuracy when compared to the Nave Bayes and K-NN algorithms.
REGULA FORENSICS FACE SDK SEBAGAI SISTEM ABSENSI BERBASIS PENGENALAN WAJAH PADA PLATFORM ANDROID Widjaya, Rendi; Irwansyah, Irwansyah; Rizal, Rizal; Budiyantara, Agus; M, Tupan Tri
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.554

Abstract

Attendance is one of the important activities in organizational management, especially in the fields of education and business. Until now, attendance systems are still mostly done manually with signatures or ID cards. However, these methods are prone to fraud, such as buddy punching or data manipulation. This study aims to develop a facial recognition-based attendance system on the Android platform using Regula Forensics Face SDK. Test results at thresholds of 70%, 85%, and 90% show that the 85% threshold provides the best compromise, with a False Acceptance Rate (FAR) of 0% and a False Rejection Rate (FRR) of 14.3%. In conclusion, a facial recognition-based attendance system can be implemented on the Android platform using the Regula Forensics Face SDK. This technology has been proven to improve security and efficiency in Android attendance systems. In addition, this technology offers an accurate, fast, and secure biometric solution through flexible integration with Flutter. Despite technical and licensing limitations, this technology is still feasible for implementation in modern attendance systems.