Pengendalian Harga Komoditas Pangan Menggunakan Diagram CUSUM Data Depth Mahalanobis - Nadia Nur Azizah; Suwanda Suwanda (Jurnal Riset Statistika, 2026)
Abstract. Food commodity prices in Indonesia tend to fluctuate, influenced by imbalances between supply and demand, climate conditions, government policies, and market dynamics. This food price instability directly impacts inflation, public purchasing power, and national food security. Therefore, an effective price monitoring method capable of detecting changes early is needed. This study aims to monitor the price stability of nine major food commodities: medium-sized rice, chicken, beef, chicken eggs, shallots, garlic, red chilies, cayenne peppers, and granulated sugar from January 2019 to December 2024. The method used is the Mahalanobis Data Depth-based CUSUM control chart, which was chosen because it is robust to outliers and able to handle multivariate data that does not meet the assumption of normality. While CUSUM is effective in detecting small shifts cumulatively. The results show that cayenne pepper and red chilies have the highest average prices and fluctuations, while medium-sized rice and granulated sugar are relatively stable. The Mardia test indicates that the data is not multivariately normally distributed. The Mahalanobis CUSUM Data Depth control chart detected an out-of-control condition starting from the 17th period, namely May 2020. Abstrak. Harga komoditas pangan di Indonesia cenderung mengalami fluktuasi yang dipengaruhi oleh ketidakseimbangan antara permintaan dan penawaran, kondisi iklim, kebijakan pemerintah, serta dinamika pasar. Ketidakstabilan harga pangan tersebut berdampak langsung terhadap inflasi, daya beli masyarakat dan ketahanan pangan nasional, sehingga diperlukan metode pemantauan harga yang efektif dan mampu mendeteksi perubahan secara dini. Penelitian ini bertujuan untuk memantau kestabilan harga sembilan komoditas pangan utama, yaitu beras medium, daging ayam, daging sapi, telur ayam, bawang merah, bawang putih, cabai merah, cabai rawit, dan gula pasir pada periode Januari 2019 hingga Desember 2024. Metode yang digunakan adalah diagram kendali CUSUM berbasis Mahalanobis Data Depth, yang dipilih karena bersifat robust terhadap pencilan serta mampu menangani data multivariat yang tidak memenuhi asumsi normalitas, sementara CUSUM efektif dalam mendeteksi pergeseran kecil secara akumulatif. Hasil penelitian menunjukkan bahwa cabai rawit dan cabai merah memiliki rata-rata harga dan fluktuasi tertinggi, sedangkan beras medium dan gula pasir relatif stabil. Uji Mardia menunjukkan data tidak berdistribusi normal multivariat. Diagram kendali CUSUM Data Depth Mahalanobis mendeteksi kondisi tidak terkendali mulai periode ke-17, yaitu Mei 2020.