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All Journal Jurnal Sistem Komputer dan Informatika (JSON) Journal of Data Mining and Information Systems
Poernomo, Moyo Hady
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Computer Science & IT Control & Systems Engineering

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Prediksi Pembelian Barang Pada Distributor Lampu Menggunakan Metode Apriori pada PT. XYZ Damanik, Rudolfo Rizki; Poernomo, Moyo Hady
JDMIS: Journal of Data Mining and Information Systems Vol. 1 No. 1 (2023): February 2023
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v1i1.1500

Abstract

Apriori is an algorithm that is widely used to determine the pattern of relationships between products that are often bought together in a store. This Apriori algorithm will be suitable to be applied in the field of determining strategy or promotion. PT. XYZ is one of the Lighting Distributor Companies. One of the problems of the company is the imbalance of stock in the warehouse. So, the purpose of this research is to obtain product purchase predictions from suppliers to maintain stock balance with product solds to customers. The object of this research is the application of apriori algorithm. This research data is in the form of sales transaction data at PT. XYZ. Data analysis using RapidMiner Software by determining the valure of support and confidence. The analysis shows that there are 22 Association Rules with a minimum support 20% and a minimum confidence 50%. This information is excpected to help the company in developing a product purchasing strategy from the supplier.
Sistem Pendukung Keputusan Seleksi Data Terpadu Kesejahteraan Sosial Menggunakan Metode K-Means dan SAW Praningki, Tutus; Poernomo, Moyo Hady; Suban, Ignasius Boli
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6845

Abstract

Indonesia as a developing country cannot be free from problems related to poverty, Some people still have income that is not sufficient for a decent life. The Indonesian government has several programs that are useful for reducing poverty, namely the Bantuan Pangan Non Tunai (BPNT) atau Program Keluarga Harapan (PKH). Often in the process of distributing aid there are obstacles or problems, the obstacle that often arises is determining the right family to receive assistance. Sub-districts or villages are at the forefront of the data collection process and selection for recommendation into the Data Terpadu Kesejahteraan Sosial (DTKS). This research aims to develop an application product that can help the Ngronggo Kediri sub-district to accurately determine which families are entitled to assistance. The K-Means and SAW methods are used to determine which families are included in the DTKS. The K-Means method is used for the clustering process and SAW is used for the weighting process. The final weight shows that the highest recommended family weight is 91,2%, and the lowest is 51.4%.
Co-Authors Damanik, Rudolfo Rizki Suban, Ignasius Boli