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All Journal Journal of Data Insights LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics
Burhanuddin Izzul Salam
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Computer Science & IT Mathematics

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CLUSTERING MODEL K-MEANS PADA KASUS ANGKA PUTUS SEKOLAH TINGKATAN SEKOLAH DASAR DI PROVINSI JAWA TENGAH Laila Khoirun Nisa; Tari Fitri Ningsih; Burhanuddin Izzul Salam; Fauzi, Fatkhurokhman; Eny Winaryati
LogicLink Vol. 1 No. 1, June 2024
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v1i1.7793

Abstract

Basic education aims to equip children with the basic skills they need to navigate their lives as individuals, elements of society, elements of citizens and also as human beings, and prepare them for higher education in the future. The case of dropping out of school seems to be a problem that cannot be overcome. The impact of dropping out of school if not managed properly will certainly be detrimental, including having an impact on the quality of resources in the future. Therefore, it is necessary to take action to reduce the dropout rate at the elementary school level. This research was conducted using the K-Means clustering algorithm to find out which districts/cities in Central Java have high, medium, and low dropout rates. The results of clustering using the K-Means algorithm through 3 methods obtained an optimal K value of 3, therefore 3 clusters were formed from all 35 regencies/cities in Central Java, cluster 1 with a tendency for high elementary school dropout rates to be 14 regencies/cities, cluster 2 with a moderate trend of dropout rates from elementary school there are 15 regencies/cities, and cluster 3 with a low trend of dropout rates from elementary school there are 6 regencies/cities.
Forecasting the Price of Curly Red Chilies in Malang Regency With Using the ARIMA Method: Peramalan Harga Cabai Merah Keriting Di Kabupaten Malang Dengan Menggunakan Metode ARIMA Nur Hanifah Ibrahim; Burhanuddin Izzul Salam; Indah Mafaati Nur
Journal of Data Insights Vol 3 No 2 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i2.303

Abstract

CChile is one of the hultikura plants that grows abundantly in Indonesia. In Indonesia, chilies are widely used as a cooking spice, making them a household staple. The increasing need for chilies (during the holidays) causes the demand for chilies to also increase. The increase in chile prices which is not directly proportional to chile production causes price changes. To maintain optimal availability of chilies, forecasting is needed to help make decisions and develop policies. One method that can be used for forecasting is the Autoregressive Integrated Moving Average (ARIMA) method. Based on the analysis results obtained, the best ARIMA model used in this research is the ARIMA model (0, 1, 0) which produces the smallest AIC value and MAPE of 2.664656%, the accuracy value is less than 10% which means that the forecasting ability with the ARIMA (0, 1, 0) model is very good.
Co-Authors Eny Winaryati Fauzi, Fatkhurokhman Indah Mafaati Nur Laila Khoirun Nisa Nur Hanifah Ibrahim Tari Fitri Ningsih