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Journal : Infotech: Journal of Technology Information

 1 
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%.
KLASIFIKASI DATA MINING UNTUK MENENTUKAN KUALITAS UDARA DI PROVINSI DKI JAKARTA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS (K-NN) Wiranata, Ade Davy; Soleman, Soleman; Irwansyah, Irwansyah; Sudaryana, I Ketut; Rizal, Rizal
Infotech: Journal of Technology Information Vol 9, No 1 (2023): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v9i1.164

Abstract

Air plays an important role in maintaining the life of living things on earth. Metabolic processes that occur in the bodies of living things cannot take place without oxygen from the air. The air pollution problem in DKI Jakarta is very serious and can cause health problems such as irritation of the respiratory tract, respiratory diseases, and long-term health problems such as cardiovascular disease and lung cancer. Air pollution can also affect environmental quality, reduce visibility, and damage ecosystems. The purpose of this study is to determine the accuracy of classifying air quality in DKI Jakarta province. The data mining method that the author uses is the K-Nearest Neighbors (K-NN) algorithm. From the results of the evaluation process of the K-Nearest Neighbors (K-NN) algorithm using the K-5 fold that has been carried out using the RapidMiner tool, the results of K-2 fold accuracy of 73.97%, K-3 fold accuracy of 72.60%, K-4 fold accuracy of 72.60%, and K-5 fold accuracy of 75.35%.
OPTIMALISASI KLASIFIKASI UJI EMISI SEPEDA MOTOR MENGGUNAKAN ALGORITMA NAÏVE BAYES Irwansyah, Irwansyah; Dittyata, Rizki; Rizal, Rizal; Wiyono, Wiyono
Infotech: Journal of Technology Information Vol 10, No 2 (2024): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v10i2.327

Abstract

Dense urban areas with high levels of industrial and transportation activity result in increased air pollutant emissions that threaten air quality and the health of their residents. The issue is the lack of utilization and optimization of motorcycle emission test classification through a machine learning approach. This research aims to utilize motorcycle emission test data and to determine the accuracy, precision, and recall results of the naive Bayes algorithm. The number of datasets used by the researchers is 2409 data points. Based on this data, it is divided into two parts: training data consisting of 1927 data points (80%) and testing data consisting of 482 data points (20%). The results of the motorcycle emission test data can be utilized for classification optimization, and the naive Bayes algorithm can be applied to classify and analyze the accuracy, precision, and recall results of the motorcycle emission test data. The accuracy result is 91.49%, the precision result for the pass classification is 93.72%, and the precision result for the fail classification is 83%, while the recall result for the pass classification is 95.47% and the recall result for the fail classification is 77.57%.      ABSTRAK Daerah perkotaan yang padat penduduk dengan tingkat aktivitas industri dan transportasi yang tinggi mengakibatkan peningkatan emisi polutan udara yang mengancam kualitas udara dan kesehatan warganya. Permasalahan belum  adanya pemanfaatan dan optimalisasi klasifikasi uji emisi sepeda motor melalui pendekatan machine learning. Penelitian ini bertujuan untuk memanfaatkan data uji emisi sepeda motor dan untuk mengetahui  hasil akurasi, presisi, dan recall dari algoritma naïve bayes. Adapun jumlah dataset yang peneliti gunakan sebanyak 2409 data. Berdasarkan data tersebut dibagi menjadi dua yaitu data training sebanyak 1927 data (80%) dan data testing sebanyak 482 data (20%). Hasil penelitian data uji emisi sepeda motor dapat dimanfaatkan untuk optimalisasi klasifikasi dan algoritma naïve bayes dapat diterapkan dalam mengklasifikasi dan menganalisis hasil akurasi, presisi, dan recall dari data uji emisi sepeda motor. Adapun hasil akurasinya sebesar sebesar 91,49%, hasil precision klasifikasi lulus sebesar 93,72% dan hasil precision klasifikasi tidak lulus sebesar 83%, dan hasil recall klasifikasi lulus sebesar 95,47% dan hasil recall klasifikasi tidak lulus sebesar 77,57%.
Co-Authors Abdul Rahim Abdullah, Bustami Abdurahman, Irfan Acip, Acip Ade Davy Wiranata Aditya, Rahul Afif, Muhammad Athallah Agustina, Agnes Ahistasari, Asih Ahmad Muhtadi Akadji, Irfan Akbar, Anugrah Trial Ali Djamhuri Alimin Alimin, Alimin Amir, Pahriadi Amran, Elsa Fitri Anani, Siske Andi Nur Fadillah, Andi Nur Anggraini Anggraini Angraini, Merie Satya Anita, Rini Aprilliani, Nur Ariani, Komang Dewi Aris Munandar Aris Susanto Asaroh, Yunia Asmadi asmadi Asriani Asriani, Asriani Asrul Sani Aswandi, Sakti Azahra, Zainab Aziza, Wahyuni Aziza, Wahyuni Aziza Azizah Azizah Azzahra, Dea Basira, Gusmiatni Dediyana Bau Ratu Bimantara, Willy Bin. M Gagaramusu, Yusdin Burhanis, Burhanis Bustami Bustami Damayanti, Alfina Daris Salam, Asep Lukman Darmawansyah, Tely Darmulia, Darmulia Dasuki, Ahmad Daswati Daswati David David Desfitri, Annisa Desy Rahmawati Anwar Dhevy Puswiartika Diana, Diana Utami Arif Dina Utami Dittyata, Rizki Djuraid, Djuraid Edriayani, Novi Edy Fachrial Edy Karno, Edy Efie Fadjrijah Eka, Efie Fadjrijah Eko Riswanto, Eko Elfadhli Elfadhli, Elfadhli Eliyani Eliyani Ely Ibrahim Endang Widyawatiningrum, Endang Fadlisyah Fadlisyah Fahlefi, Rizal Fahrauk, M. Fajriana, Fajriana Faradilla, Aulia Fasli, Muhammad Fauzul, Ahmad Filiansi, Mutmoza Fioni, Fioni Firman Firman Gagaramusu, Yusdin Bin M. Gatot Siswo Hutomo Habiba, Muh. Syahrir Hafinuddin Hafinuddin Hafiyyan, Qalbi Hajri, Siti Hamdhana, Defry Hanafie, Ahmad Hanifa, Lia Hanisu, Hanisu Hanna Sari Widya Kusuma, Hanna Sari Widya Hanzala, Nasri Hariansyah, Hariansyah Hariawan, Hamdan Harjaty, Erny Harni, Harni Hasan Hasan Hasdin Hasdin Haslindah, Andi Hasymi, Liana Fitriani Hedi, Hedi Helyanto, Helyanto Herlina Herlina Herning Indriastuti Hidasari, Fitriana Puspa Himmatul Ulya Himyar Pasrizal Hiola, Kalsum Hj. Widayati Pujiastuti Huber Yaspin Tandi I Ketut Sudaryana, I Ketut Idham Azwar Idrus, Rini Angriani Igo B.D, Abdullah ikhwan Arief Purnama Ikram, La Ode Muhamad ikramina, Ikramina Ilham, Muh Imran Imran Indah Sari, chitra Intan Purnama Sari Irene anggraini Irsanty Collein Irwansyah Irwansyah Isma Tjangkana Isnayanti, Andi Nur Isriany Ismail Izhar, Muhammad Jayanto, Imam Johan, T. M. Joni Guci, Ammar Abdullah Judijanto, Loso Julianti, Nengsih Kadek Hariana Kaimudin, Syawal Alfikry Kalsum Kalsum Karim Karim, Karim Khainir Akbar, Khainir Khairi, Khairil Faizal Khairul Umam Kiki Achmad Rizki Kusuma Dewi, Ratih Puspita La Ode Muhammad Elwan La Ode Turi La Rudi Lagut, Lagut Lapasere, Sisriawan Lapasere, Sisriawan Lapasere Lestari, Meri Nur Lestari, Nova Hermina Liana Liana Lidya Rosnita Lister, I Nyoman Ehrich Lutfi Uluelang, Muhammad M, Tupan Tri Marlion, Farid Ahmad Martanto . Marwah, Sri Aryas Masdiana Masdiana Masdiana Masdiana Maulana, Mirga Maulana Mawarni Mawarni Ma’ruf, Fatmah Melasari, Wulan Panduwi Mirawati Mirawati Misnah Misnah Mohammad Arief Nur Wahyudien Mondo, Ariamin Mubarak, Muh. Husni Muhamad Yusuf, SE., M.Si. Muhammad Aqil Muhammad Ilham Muharrom, Wahedi Mukhlasin Mukhlasin, Mukhlasin Mulia, Linda Sr Mulyasari, Tira Endang Munason, Munason Munirul Ula Muslem R, Imam Nanik Hindaryatiningsih Napu, Iin Angraen Nasrullah Nasrullah Natsir, Ramdhani M Natzir, Andi Wirandani Neli, Neli Nengsih, Ifelda Nernawani, Nernawani Nia, Murni Nofrivul, Nofrivul Noviana, Firta Nur Afni Nurdin, Mochamad Nurfaidah Nurfaidah Nurhadianto Nurhadianto, Nurhadianto Nurhalisa, Nurhalisa Nurhamima, Nurhamima Nurhasnah Nurhasnah Nurkarimah, Rahmawati Nursakinah, Nursakinah Nurul Mardiati Nuzammil, Muzammil Nuzmerini Rauf Orlando, Ray Pahriadi, Pahriadi Pembudi, Endi Perangin Angin, Imanuel Kemenangenta Pitojo Tri Juwono Pratama, Ryan A. Pratama, Ryan Andhika Purnama, Ihkwan Arief Purwoko, Agus Pusaka, Semerdanta Putri, Suci Mulia Rabihati, Etty Rahim, Febria Rahmadani, Fadel Rahmat Firdaus Rahmawan, Adi Penata Rahmawati, Rahmawati Ramadhayanti, Ghita Ramdani, Mumammad Ramly, Ramly Randy Setiawan, Randy rasiwan, rasiwan Rauf, Nuzmerini Reski, Indah Anjar Riyanto Haribowo Rizal, Togimin Rizki Suwanda Rusfiandi, wandi Ryanti, Eva Safitri, Valia Said Fadlan Anshari Sakinah Sakinah Salsabila, Nindia Sami’an, Sami’an Saputra, Dodiek Rara Saputra, Megi Sari, chitra Sari, Chitra Indah Sarpawi, Sarpawi Sasongko, Hartanto Wahyu Sefriyana, Sefriyana Setiawan, Wa Ode Nining Setiayawan, Wa Ode Nining Setiyawan, Wa Ode Nining Setyarandini, Venia Shafiyyah, Salwa Salsabillah Shobirin, Khairulis Siti Masitoh Kartikawati Sitti Husna Noviana Djou Soleman, Soleman Sovyan Arifin, Muhammad Sri Wahyuni Sucianti, Riska Sudiah, Lismawati Sugiaman, Vinna Kurniwati Suhroji Adha Sukandar, Elin Y. Sukmawati Sukmawati Surahman Surahman Surahman Wilade Susetyo, Berlian Sutjiatmo, Afifah B Syafyudin, Buyung Adnan Syamsinah Syamsinah, Syamsinah Tajuddin, Tamrin tamala, ovin Tendri, Tendri Thalib, Azizah Togimin, Togimin Topuha, Oktaviani Karolina Ujang Suryadi Unton, Ali Rahmat Utomo, Satrio Wahdah, Ghoriqna Fibahril WAHYU WIDOWATI Wali, Silvia Agnesi Waly, Silvia Agnesi WARDHANI, FATIMAH SETIA Wati, Wija Widi Nopiardo Widjaya, Rendi Widya Kusuma, Hanna Sari Widya Kusuma Wiyono wiyono Wolingalo, Anggita Frestianingsih YAAKOB, MOHD FAIZ MOHD Yandra, Alfi Yanthi Yanthi Yassin, Muhammad Yesy Afrillia Yosevien Yosevien Yudhistira Arie Wijaya Yulieti P., Ratu Miki Yun Ratna Lagandesa Yunus, Sitti Rahma Zainuddin, Zainuddin Zaitun Zaitun Zetria, Fauza Dwi Zumrah, Zumrah