Perbandingan Pendekatan Metode Peramalan Naive Approach, Simple Moving Average dan Weighted Moving Average dalam Upaya Meningkatkan Prediksi Penjualan JNE Kopma UNY
DOI:
https://doi.org/10.30737/jatiunik.v7i2.5495Keywords:
Effectiveness, Forecasting, JNE UNY, Sales predictionAbstract
JNE Kopma UNY's logistics demand increases 2% per week, the manual courier allocation system is unable to keep up, predictions are accurate and real-time is needed. However, there is no exact accuracy for this case. The study was conducted to determine the accuracy of the smallest Mean Percentage Error (MPE) at JNE Kopma UNY by observing sales data for 2022 to predict demand. The data was analyzed using the Naive Approach, SMA and WMA methods, then measured using the MPE to determine the best forecasting method. The software used is Microsoft Excel 2016. The 3 Month (SMA) produces the highest sales prediction (Rp. 38,668,850) for January 2023 compared to Naive Approach (Rp. 35,086,330) and 3 Month WMA (Rp. 37,993,380). 3 Month SMA is proven to be superior with the lowest MPE (12.07%) and consistent performance. Naive Approach is inaccurate (MPE 20.26%) and 3 Month WMA performance is unstable (MPE 14.27%). This research recommends 3 Month SMA for JNE Kopma UNY to increase the accuracy of sales predictions and optimize stock. Opportunities for further research are open regarding the application of 3 Month SMA in various contexts.
References
J. Alfian Pradana, A. Komari, and L. Dewi Indrasari, “Studi Kelayakan Bisnis Tell Kopi Dengan Analisis Finansial,” Ind. Inov. J. Tek. Ind., vol. 10, no. 2, pp. 92–97, 2020, doi: 10.36040/industri.v10i2.2855. DOI: https://doi.org/10.36040/industri.v10i2.2855
J. A. Pradana, R. P. Dewanti, M. F. Abdulloh, and A. P. Hidayat, “Distributor Selection on the Impact of Demand for Coffee Products: AHP – Single Exponential Smoothing,” Airlangga J. Innov. Manag., vol. 3, no. 2, pp. 136–148, 2022, doi: 10.20473/ajim.v3i1.39655. DOI: https://doi.org/10.20473/ajim.v3i1.39655
R. P. Dewanti, E. Paryanto, J. A. Pradana, and C. Harsito, “Financial Feasibility of Modification Workshop Case Studies: Be-Modified,” Int. J. Sustain. Dev. Plan., vol. 17, no. 6, pp. 1865–1871, 2022, doi: 10.18280/ijsdp.170621. DOI: https://doi.org/10.18280/ijsdp.170621
M. Solgi, M. Karami, and J. Poorolajal, “Timely detection of influenza outbreaks in Iran: Evaluating the performance of the exponentially weighted moving average,” J. Infect. Public Health, vol. 11, no. 3, pp. 389–392, 2018, doi: 10.1016/j.jiph.2017.09.011. DOI: https://doi.org/10.1016/j.jiph.2017.09.011
S. Yunika and S. Sugiono, “Sistem Peramalan Menggunakan Metode Exponential Smoothing Dan Weight Moving Average Di Perusahaan Konstruksi Telekomunikasi,” Konvergensi, vol. 13, no. 2, 2019, doi: 10.30996/konv.v13i2.2756. DOI: https://doi.org/10.30996/konv.v13i2.2756
D. P. Y. Ardiana and L. H. Loekito, “Sistem Informasi Peramalan Persediaan Barang Menggunakan Metode Weighted Moving Average,” J. Teknol. Inf. dan Komput., vol. 4, no. 1, pp. 71–79, 2018, doi: 10.36002/jutik.v4i1.397. DOI: https://doi.org/10.36002/jutik.v4i1.397
M. Hynek, J. Zvárová, D. Smetanová, D. Stejskal, and J. Kalina, “Real-time quality control of nuchal translucency measurements using the exponentially weighted moving average chart,” Taiwan. J. Obstet. Gynecol., vol. 60, no. 1, pp. 84–89, 2021, doi: 10.1016/j.tjog.2020.11.012. DOI: https://doi.org/10.1016/j.tjog.2020.11.012
N. C. Atuegwu, E. M. Mortensen, S. Krishnan-Sarin, R. C. Laubenbacher, and M. D. Litt, “Prospective predictors of electronic nicotine delivery system initiation in tobacco naive young adults: A machine learning approach,” Prev. Med. Reports, vol. 32, no. February, p. 102148, 2023, doi: 10.1016/j.pmedr.2023.102148. DOI: https://doi.org/10.1016/j.pmedr.2023.102148
I. Ilyas, F. Marisa, and D. Purnomo, “Implementasi Metode Trend Moment (Peramalan) Mahasiswa Baru Universitas Widyagama Malang,” JOINTECS (Journal Inf. Technol. Comput. Sci., vol. 3, no. 2, 2018, doi: 10.31328/jointecs.v3i2.785. DOI: https://doi.org/10.31328/jointecs.v3i2.785
J. N. A. Aziza, “Perbandingan Metode Moving Average, Single Exponential Smoothing, dan Double Exponential Smoothing Pada Peramalan Permintaan Tabung Gas LPG PT Petrogas Prima Services,” J. Teknol. dan Manaj. Ind. Terap., vol. 1, no. I, pp. 35–41, 2022, doi: 10.55826/tmit.v1ii.8. DOI: https://doi.org/10.55826/tmit.v1iI.8
E. Setyowati, “Perbandingan Metode Exponential Smoothing dan Moving Average dalam Peramalan Retribusi Pengujian Kendaraan Bermotor di Dinas Perhubungan Kota Blitar,” J. Sains Dasar, vol. 11, no. 1, pp. 35–38, 2022, doi: 10.21831/jsd.v11i1.44391. DOI: https://doi.org/10.21831/jsd.v11i1.44391
A. Zahrunnisa, R. D. Nafalana, I. A. Rosyada, and E. Widodo, “Perbandingan Metode Exponential Smoothing Dan Arima Pada Peramalan Garis Kemiskinan Provinsi Jawa Tengah,” J. Lebesgue J. Ilm. Pendidik. Mat. Mat. dan Stat., vol. 2, no. 3, pp. 300–314, 2021, doi: 10.46306/lb.v2i3.91. DOI: https://doi.org/10.46306/lb.v2i3.91
K. Khamaludin, “Peramalan Penjualan Hijab Sxproject Menggunakan Metode Moving Average Dan Exponential Smoothing,” Unistek, vol. 6, no. 2, pp. 13–16, 2019, doi: 10.33592/unistek.v6i2.249. DOI: https://doi.org/10.33592/unistek.v6i2.249
R. Kusumawati, D. Urwatul Wutsqa, and R. Subekti, “Peramalan Harga Saham Berdasarkan Jaringan Syaraf Fuzzy Elman Recurrent Dengan Optimasi Evolutif Stock Price Forecasting Based on Fuzzy Elman Recurrent Neural Networks With Evolutive Optimization,” J. Sains Dasar, vol. 7, no. 2, pp. 95–102, 2018.
S. P. Wisesa, A. S. Prayogi, and T. M. Fahrudin, “Pemodelan Dan Evaluasi Trend Forecasting Pada Kondisi Korban Kecelakaan Lalu Lintas,” J. Sist. Cerdas, vol. 01, no. 02, pp. 56–66, 2018.
S. Sekar kinasih, Arie Agoestanto, “Optimasi Parameter pada Model Exponential Smoothing Menggunakan Metode Golden Section untuk Pemilihan Model Terbaik dan Peramalan Jumlah Wisatawan Provinsi Jawa Tengah,” Unnes J. Math., vol. 7, no. 1, pp. 38–46, 2018.
M. Mirdaolivia and A. Amelia, “Metode Exponential Smoothing Untuk Forecasting Jumlah Penduduk Miskin Di Kota Langsa,” J. Gamma-Pi, vol. 3, no. 1, pp. 47–52, 2021, doi: 10.33059/jgp.v3i1.3771. DOI: https://doi.org/10.33059/jgp.v3i1.3771
I. W. Prananto, T. Pamungkas, and R. Hidayat, “Implementation of forecasting methods to determine teaching and learning model policies during a pandemic in border areas,” J. Penelit. Ilmu Pendidik., vol. 16, no. 1, pp. 35–46, 2023, doi: 10.21831/jpipfip.v16i1.52573. DOI: https://doi.org/10.21831/jpipfip.v16i1.52573
M. A. Ardhirakmanto, S. Rahayuningsih, and A. Komari, “Pengendalian Persediaan Bahan Baku Pada Industri Tenun Ikat ‘Medali Mas’ Kediri,” JURMATIS J. Ilm. Mhs. Tek. Ind., vol. 2, no. 2, p. 75, 2020, doi: 10.30737/jurmatis.v2i2.949. DOI: https://doi.org/10.30737/jurmatis.v2i2.949
B. Aprillia, A. E. Nugraha, and D. Herwanto, “Pengendalian Persediaan Bahan Baku Dengan Metode Economic Order Quantity (EOQ) Multi Item Pada Rumah Makan,” JURMATIS (Jurnal Manaj. Teknol. dan Tek. Ind., vol. 4, no. 2, p. 137, 2022, doi: 10.30737/jurmatis.v4i2.2165. DOI: https://doi.org/10.30737/jurmatis.v4i2.2165
D. Junaidi and I. Mas’ud, “PENERAPAN METODE FORECASTING DALAM PERENCANAAN PRODUKSI BAKPIA DENGAN MENGGUNAKAN SOFTWARE POM GUNA MEMENUHI PERMINTAAN KONSUMEN,” J. Knowl. Ind. Eng., no. 1, pp. 121–128, 2018.
T. A. Tistiawan and T. D. Andini, “Pemanfaatan Metode Triple Exponential Smoothing Dalam Peramalan Penjualan Pada Pt.Dinamika Daya Segara Malang,” J. Ilm. Teknol. Inf. Asia, vol. 13, no. 1, p. 69, 2019, doi: 10.32815/jitika.v13i1.345. DOI: https://doi.org/10.32815/jitika.v13i1.345
S. Andreassen, A. Zalounina, M. Paul, L. Sanden, and L. Leibovici, “Interpretative reading of the antibiogram – a semi-naïve Bayesian approach,” Artif. Intell. Med., vol. 65, no. 3, pp. 209–217, 2015, doi: 10.1016/j.artmed.2015.08.004. DOI: https://doi.org/10.1016/j.artmed.2015.08.004
S. Sutrisman, H. Syafwan, and R. Rohminatin, “Implementation of Trend Moment Method in Forecasting Regional Income,” Build. Informatics, Technol. Sci., vol. 4, no. 2, pp. 749–758, 2022, doi: 10.47065/bits.v4i2.2090. DOI: https://doi.org/10.47065/bits.v4i2.2090
S. Yrarrazaval, I. Cartajena, L. Borrero, and D. Salazar, “Identifying non-anthropogenic accumulation in zooarchaeological assemblages using naive Bayesian classifier: A trace-oriented actualistic taphonomic approach in the hyperarid coasts of the Atacama desert,” Quat. Sci. Adv., vol. 13, no. November 2023, p. 100143, 2024, doi: 10.1016/j.qsa.2023.100143. DOI: https://doi.org/10.1016/j.qsa.2023.100143
M. H. Lubis, A. A. Tanjung, and D. Martina, “Forecasting Untuk Produksi Batik Dengan Single Moving Average,” J. Tek., vol. 2, no. 2, p. 29, 2022, doi: 10.54314/teknisi.v2i2.963. DOI: https://doi.org/10.54314/teknisi.v2i2.963
L. Pasca Riani and M. R. Afandi, “Forecasting Demand Produk Batik Di Tengah Pandemi Covid-19 Studi Pada Usaha Batik Fendy, Klaten,” J. Nusant. Apl. Manaj. Bisnis, vol. 5, no. 2, pp. 122–132, 2020, doi: 10.29407/nusamba.v5i2.14441. DOI: https://doi.org/10.29407/nusamba.v5i2.14441
J. E. Rah, D. Shin, and G. Y. Kim, “Feasibility Study of a Moving Centerline Exponentially Weighted Moving Average Control Chart to Detect Real Warning for Daily Output QA in Proton,” Int. J. Radiat. Oncol., vol. 99, no. 2, p. E713, 2017, doi: 10.1016/j.ijrobp.2017.06.2318. DOI: https://doi.org/10.1016/j.ijrobp.2017.06.2318
A. Maboudi Reveshti, E. Khosravirad, A. K. Rouzbahani, S. K. Fariman, H. Najafi, and A. Peivandizadeh, “Energy consumption prediction in an office building by examining occupancy rates and weather parameters using the moving average method and artificial neural network,” Heliyon, vol. 10, no. 4, p. e25307, 2024, doi: 10.1016/j.heliyon.2024.e25307. DOI: https://doi.org/10.1016/j.heliyon.2024.e25307
A. D. Iskandar and S. Sutrisno, “Efisiensi Persediaan Material dengan Metode Activity Based Costing pada PT. XYZ,” JURMATIS (Jurnal Manaj. Teknol. dan Tek. Ind., vol. 5, no. 1, p. 1, 2023, doi: 10.30737/jurmatis.v5i1.2198. DOI: https://doi.org/10.30737/jurmatis.v5i1.2198
K. Nakade and Y. Aniyama, “Bullwhip effect of weighted moving average forecast under stochastic lead time,” IFAC-PapersOnLine, vol. 52, no. 13, pp. 1277–1282, 2019, doi: 10.1016/j.ifacol.2019.11.374. DOI: https://doi.org/10.1016/j.ifacol.2019.11.374
R. Karmakar, S. Chatterjee, D. Datta, and D. Chakraborty, “Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019,” Syst. Soft Comput., vol. 6, no. May 2023, p. 200067, 2024, doi: 10.1016/j.sasc.2023.200067. DOI: https://doi.org/10.1016/j.sasc.2023.200067
A. Adam, “Aplikasi Pendaftaran Mahasiswa Baru Menggunakan Metode Forecasting,” JEKIN - J. Tek. Inform., vol. 2, no. 1, pp. 9–15, 2022, doi: 10.58794/jekin.v2i1.92. DOI: https://doi.org/10.58794/jekin.v2i1.92
A. Alviyanur, “Analisis Perencanaan Produksi Menggunakan Metode Forecasting,” J. Indones. Sos. Teknol., vol. 3, no. 3, pp. 426–437, 2022, doi: 10.36418/jist.v3i3.387. DOI: https://doi.org/10.36418/jist.v3i3.387
D. R. Darmawan, T. Aspiranti, and N. Koesdiningsih, “Analisis Peramalan Penjualan dengan Menggunakan Metode Single Moving Average, Weighted Moving Average dan Exponential Smoothing Sebagai Dasar Perencanaan Produksi Polo Shirt Pria (Studi Kasus pada PT. Amanah Garment Bandung),” Pros. Manaj., pp. 703–708, 2017, [Online]. Available: https://karyailmiah.unisba.ac.id/index.php/manajemen/article/view/7187.
S. Wardani, S. Rahayuningsih, and A. Komari, “Analisis Pengendalian Ketersediaan Bahan Baku Di PT. Akasha Wira Internasional, Tbk Menggunakan Metode EOQ,” JURMATIS J. Ilm. Mhs. Tek. Ind., vol. 2, no. 1, p. 22, 2020, doi: 10.30737/jurmatis.v2i1.860. DOI: https://doi.org/10.30737/jurmatis.v2i1.860
N. K. Wardani, M. R. Afandi, and L. P. Riani, “Analisis Forecasting Demand Dengan Metode Linear Exponential Smoothing (Studi Pada: Produk Batik Fendy, Klaten),” J. Ekon. dan Pendidik., vol. 16, no. 2, pp. 81–89, 2020, doi: 10.21831/jep.v16i2.33714. DOI: https://doi.org/10.21831/jep.v16i2.33714
C. J. Anderson et al., “A novel naïve Bayes approach to identifying grooming behaviors in the force-plate actometric platform,” J. Neurosci. Methods, vol. 403, no. November 2023, p. 110026, 2024, doi: 10.1016/j.jneumeth.2023.110026. DOI: https://doi.org/10.1016/j.jneumeth.2023.110026
U. Khair, H. Fahmi, S. Al Hakim, and R. Rahim, “Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error,” 2017, doi: 10.1088/1742-6596/930/1/012002. DOI: https://doi.org/10.1088/1742-6596/930/1/012002
S. Alviana and B. Kurniawan, “Analisis Data Penerimaan Mahasiswa Baru Untuk Meningkatkan Potensi Pemasaran Universitas Menggunakan Business Intelligence (Studi Kasus Universitas XYZ),” Infotronik J. Teknol. Inf. dan Elektron., vol. 4, no. 1, p. 10, 2019, doi: 10.32897/infotronik.2019.4.1.170. DOI: https://doi.org/10.32897/infotronik.2019.4.1.170
U. Ejder and S. A. Özel, “A novel distance-based moving average model for improvement in the predictive accuracy of financial time series,” Borsa Istanbul Rev., vol. 24, no. 2, pp. 376–397, 2024, doi: 10.1016/j.bir.2024.01.011. DOI: https://doi.org/10.1016/j.bir.2024.01.011
H. Katz, K. T. Brusch, and R. E. Weiss, “A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times,” Int. J. Forecast., no. xxxx, 2024, doi: 10.1016/j.ijforecast.2024.01.004. DOI: https://doi.org/10.1016/j.ijforecast.2024.01.004
R. D. Rincón, W. Palacios, and H. O. Paipa, “Comparison of statistical forecasting techniques for Colombian coffee demand in South Korea,” J. Phys. Conf. Ser., vol. 1448, no. 1, 2020, doi: 10.1088/1742-6596/1448/1/012023. DOI: https://doi.org/10.1088/1742-6596/1448/1/012023
N. Aini, S. Sinurat, and S. A. Hutabarat, “Penerapan Metode Simple Moving Average Untuk Memprediksi Hasil Laba Laundry Karpet Pada CV. Homecare,” JURIKOM (Jurnal Ris. Komputer), vol. 5, no. 2, pp. 167–175, 2018, [Online]. Available: http://ejurnal.stmik-budidarma.ac.id/index.php/jurikom/article/view/656.
M. M. Ali, M. Z. Babai, J. E. Boylan, and A. A. Syntetos, “On the use of Simple Moving Averages for supply chains where information is not shared,” IFAC-PapersOnLine, vol. 28, no. 3, pp. 1756–1761, 2015, doi: 10.1016/j.ifacol.2015.06.340. DOI: https://doi.org/10.1016/j.ifacol.2015.06.340
I. Darwati and R. Y. Hayuningtyas, “Metode Simple Moving Average dan Weighted Moving Average Dalam Memprediksi Produksi Beras,” EVOLUSI J. Sains dan Manaj., vol. 11, no. 2, pp. 34–41, 2023, doi: 10.31294/evolusi.v11i2.17267. DOI: https://doi.org/10.31294/evolusi.v11i2.17267
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