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This research was conducted by prediction of safety stock using Fuzzy Time Series (FTS) and technology of Radio Frequency Identification (RFID) for stock control at Vendor Managed Inventory (VMI). Well-controlled stock influenced company revenue and minimized cost. It discussed about information system of safety stock prediction developed through programming language of PHP. Input data consisted of demand got from automatic, online and real time acquisition using technology of RFID, then, sent to server and stored at online database. Furthermore, data of acquisition result was predicted by using algorithm of FTS applying universe of discourse defining and fuzzy sets determination. Fuzzy set result was continued to division process of universe of discourse in order to be to final step. Prediction result was displayed at information system dashboard developed. By using 60 data from demand data, prediction score was 450.331 and safety stock was 135.535. Prediction result was done by error deviation validation using Mean Square Percent Error of 15%. It proved that FTS was good enough in predicting demand and safety stock for stock control. For deeper analysis, researchers used data of demand and universe of discourse U varying at FTS to get various result based on test data used.

Penelitian yang Telah dilakukan dengan melakukan Peramalan Penjualan dengan menerapkan metode double exponential smoothing untuk peramalan terhada penjualan cat dinding pada Toko Material Bangunan (TB) Enggal Jaya Jombang. TB Enggal Jaya merupakan Toko yang bergerak dibidang penjualan material bahan baku dan alat – alat bangunan diantaranya dalah Cat dindning. Banyak varian merk cat dinding yang dijual, akan tetapi peneliti mengambil objek dan sampel cat dinding dengan merk Nippon Paint. Permintaan Cat Nippon sangat tinggi dan mengalami fluktuatif yang sangat bagus seperti terdapat pada grafik penjualan tertinggi adalah cat Nippon paint di tiap bulannya. Begitu juga dengan cat merk lain seperti Jotun, catylac, avitex meskipun hasil penjualan lebih rendah namun tetap mengalami perubahan. Perubahan kebutuhan permintaan menjadikan jumlah persedian cat yang harus disiapkan perusahaan menjadi ketidakpastian. Berbagai jenis dan merk cat yang bervariasi mempersulit pemilik usaha dalam manajemen persediaan cat. Penelitian ini memiliki tujuan membuat sistem informasi bisnis yang dapat menunjang TB.Enggal Jaya untuk melakukan peramalan jumlah cat Nippon paint yang akan dijual di bulan berikutnya, serta dapat mengetahui tingkat akurasi yang diperoleh dari penerapan Double Exponential Smoothing untuk memproyeksikan jumlah permintaan cat Nippon paint pada TB.Enggal Jaya. Metode Double Exponential Smoothing diapaki untuk memproyeksikan jumlah penjualan cat Nippon paint setiap bulannya dengan hasil rata-rata PE sebesar 0,14%. Berdasarkan perhitungan diperoleh hasil Double Exponential untuk peramalan penentuan penjualan cat Nippon paint diperoleh 0,14% dari rata-rata PE yang dihasilkan dan paling efektif dengan persentase yaitu 0,02% dan rata-rata tingkat error dengan nilai sebesar 0,14 % serta hasil persentase tingkat akurasi menggunakan Double Exponential Smoothing memperoleh rata-rata nilai akurasi kurang dari satu. Sehingga dapat disimpulkan proyeksi penjualan cat Nippon paint menggunakan metode ini sangat akurat

The production time optimization study used the Campbell Dudek smith (CDS) algorithm in the production process scheduling aimed at makespan optimization for engine operation to produce 12-size pan products, 14-size griddle, 16-size griddle, 18-size griddle, and 20-size griddle. The method applied by the Campbell Dudek and Smith (CDS) algorithm, CDS is a method used in flowshop-type scheduling developed from Johnson's rule that is able to minimize makespan 2 machines arranged in series. The CDS method is very suitable for production characters who apply the machine sequence to the production process. CDS produces several iterations that have makespan values, from the few iterations the most minimum makespan value is obtained to determine the order of products to be produced. This research produces an application that can schedule products to be produced by the machine automatically. From the results of testing with a total production of 12 pieces on each product with repetitions of 6 times, the minimum makespan value is 210.12 minutes with a work order of 20, grid 18, griddle 16, griddle 14, and griddle 12. Accuracy of results Application testing showed 99.99% for the first time and 99.96% for the second time when compared to manual calculations.

This study discusses the production planning system and scheduling shallots planting patterns using fuzzy time series and linear programming methods. In this study fuzzy time series to predict the number of requests and the results of predictions from fuzzy time series methods become one of the variables in the calculation of linear programming. Using supporting variables, demand data, production data, employment data, land area data, production profit data, data on the number of seedlings and planting time data are indicators used in processing the system. The system provides recommendations for cropping patterns and the number of seeds that must be planted in one period. The age of harvesting onions is ± 3-4 months from the planting process, the number of planting seeds is adjusted to the number of requests that have been predicted by using fuzzy time series and cropping pattern calculation process is carried out using linear programming. The results of this system are recommendations for farmers to plant seedlings, planting schedules, and harvest schedules to meet market demand.