Marriage is the most awaited moment for everyone. Prawdding is an important thing to do before a wedding. Because prewedding photos become the latest trend for photos that will be displayed during the wedding. But in a lot of prewedding photos brides who are not satisfied with the results of these prewedding photos. This system can facilitate the bride and groom in choosing the location of prawedding photos without the need to meet in person to consult. This decision making system is made using the Weight Product method and is made with the php programming language and MySQL database. The WP method is used to find optimal alternatives from a number of alternatives. The selection of the location of the prewedding photo uses weighting for each criterion. The bride and groom can choose the desired location based on criteria such as the number of spots, themes, location distance, number of shoots with weights determined by the user based on the level of importance. The results of this system are displaying praweding locations based on the location of prawedding photos that can be ordered by the bride and groom. The selection of prewedding photo locations can be done optimally so that the results of the decision are as expected.Keywords: Decision Support System, Prewedding Location, Product Weight

UMKM ialah kegiatan usaha kecil ekonomi rakyat yang berskala kecil dan dilindungi dari kompetisi usaha yang tak sehat dan tak setara. Wirausaha yang bergerak dibidang pertokoan memiliki prospek yang menjanjikan, karena dapat melayanin masyarakat dengan kategori ekonomi menengah kebawah dan ke atas serta bisa mempermudah masyarakat untuk berbelanja keperluan tiap hari tanpa harus belanja ke supermarket atau swalayan. Namun persediaan barang atau bahan kebutuhan yang tidak dilakukan secara optimal dapat menyebabkan kekosongan pada barang atau bahan kebutuhan tersebut. Hal tersebut juga terjadi pada toko sinar harahap yang sering mengalami kekosongan pada persediaan beberapa barang dan kebutuhan yang di cari oleh pelanggan, ini di akibatkan dari tidak adanya kebiasaan pengontrolan persediaan pada toko. Maka penelitian ini bertujuan untuk melihat barang dan kebutuhan apa saja yang dibutuhkan oleh pelanggan toko. Penelitian ini menggunakan beberapa variabel yaitu tanggal transaksi, nama produk serta jumlah penjualan/pembelian. Maka, dari hasil penelitian menggunakan algoritma apriori tersebut akan di dapat data nama barang yang paling banyak terjual untuk di jadikan sebagai antisipasi persediaan barang agar tidak mengalami kekosongan yang dapat menyebabkan pelanggan kecewa.

Indonesia is one of the countries that often experiences natural disasters, including earthquakes, floods, tsunamis, etc. All of this causes losses, both casualties, Broken, and Anguishing for the population. Based on this, this paper is proposed, which aims to predict natural disasters in the coming years in Indonesia, casualties, Broken, and their consequences. This paper is an extension of previous research, which is still an architectural model to predict Indonesia’s natural disasters and their impacts. Model 4-10-1 is the best in this study, which produces 91% accuracy. Based on this architectural model, this paper will predict natural disasters that occur and their impacts for the years to come in Indonesia. The research dataset and algorithms used remain the same, namely the natural disaster dataset for 2008-2019. Resourced from its National Emergency Management Department and the Batch Training algorithm. Specifically, the results of this proposed paper are in the form of a prediction of natural disasters that will occur, dead and disappear, injured, Anguishing and displaced, houses severely Broken, moderately Broken, lightly Broken to submerged, and Broken to facilities and infrastructure such as health facilities, facilities. worship and educational facilities.

Hasanah Vocational High School (VHS) is a school that has been accredited A Excellent. But New Student Admission (NSA) has some difficulties in knowing the potential of students who will attend school. This is due to inconsistent selection and subjective judgments. Therefore a method is needed to identify new prospective students at school. Data Mining with C4.5 Algorithm can be used to make predictions and classifications of prospective new students in school by making decision trees based on existing data and predicting new prospective students who want to go to school. Data on prospective students who register through the regular path of the 2018/2019 school year. The results obtained are variables that have the highest priority on the predictions of NSA are prospective students who test scores with high scores so the student is declared an accepted status.

Cabbage is an annual plant or more in the form of a shrub. One of the centers for cabbage production is in Simalungun Regency, Ancient District. Cabbage has good demand prospects. However, erratic weather factors and plant pests that threaten to make the quality of cabbage vegetables are not good so that the impact on farmers' income is uncertain. In determining the appropriate and unfeasible cabbage, the Datamining Method with the C4.5 Algorithm is used. The C4.5 algorithm can provide a decision tree that is easy to interpret and has good accuracy so that the results obtained are expected to be input and help the agricultural office and farmers to determine the quality of cabbage vegetables that are good according to the target market. Become a reference for further research related to the users of the C4.5 Algorithm.