Determination of reorder point aims to meet the safety stock. This is a central parameter of inventory control. This study aims to find reorder point based on goods classification and safe stock. This approach is implemented in retail information systems that have been running. The information system has about 15.000 active items with the number of sales transactions around 1.100 per day. The problem in determining the reorder point is the unavailability of the safe stock reference. Lack of safe stock information triggered the ordering goods error. This error causes over stock. It can increase the potential of expired goods. In this study the researcher classifies the goods and determines the amount of safe stock to control the inventory. We used ABC analysis method for goods classification. It divides the group of goods into A, B, C, and D. The amount of safe stock is determined based on the goods sale’s history using Min Max Analysis method. Classification result is used to determine the limits on the inventory of allowed items to be ordered. Limitation safety stock amount refers to the limits from the min max method result. While, testing is done by comparing cost before and after implementation of this method.

Comfortable room is one of the services that must be provided by STMIK STIKOM Indonesia campus to students. This research designed a room monitoring tool based on ESP-12E in STMIK STIKOM Indonesia. The room monitor is designed using a DHT22 sensor to measure temperature and humidity and the BH1750 sensor to measure light intensity. The tool also includes features a 16x2 I2C LCD to display measurement results. Testing is done by testing the layout circuit on the PCB and observing the measurement of temperature, humidity, and light intensity on the LCD. The test results of all layout circuits are functioning properly, and the measurement results can appear on the 16x2 I2C LCD.

Penggunaan internet pada sektor pariwisata dapat mempermudah seseorang dalam memperoleh informasi mengenai suatu tempat wisata. Ubud menjadi salah satu destinasi wisata favorit di Kabupaten Gianyar, Provinsi Bali menawarkan berbagai macam jenis wisata yang salah satunya yaitu villa sebagai akomodasi para wisatawan. Informasi mengenai opini wisatawan terhadap Ubud pada Google Maps, dapat menjadi bahan evaluasi untuk mempertahankan citra positif pariwisata Ubud. Pada penelitian ini akan dilakukan analisa text mining dengan analisa sentimen villa di Ubud berdasarkan data opini pada Google Maps menggunakan metode Naive Bayes, Decision Tree, dan k-NN menggunakan aplikasi RapidMiner. Adapun hasil pengujian dari 2894 data yang dibagi menjadi 2024 data training dan 867 data uji. Penggunaan SMOTE up-sampling digunakan untuk menyamakan jumlah data yang tidak seimbang. Hasil analisa menunjukkan bahwa metode k-NN lebih unggul dalam menganalisis sentimen dengan prediksi sentimen 526 positif, 233 netral, 72 negatif. Performance confusion matrix menunjukkan bahwa metode k-NN unggul dengan akurasi 91.26%, precision 92.97%, recall 91.26%, dan overall performance 91.83%.

No abstract