Intisari — Saat ini masyarakat Indonesia cenderung sering melakukan pemborosan pada penggunaan listrik. Di sisi lain energi listrik di Indonesia mayoritas dihasilkan dari pembangkit listrik tenaga uap, yang membutuhkan bahan bakar dari sumber daya alam yang tidak dapat diperbaharui. Sehingga tingginya permintaan dan kejadian pemborosan dalam penggunaan listrik dapat meningkatkan konsumsi sumber daya alam serta polusi udara. Maka dari itu, dalam penelitian ini diusulkan sebuah solusi melalui sistem peringatan dini yang dapat menumbuhkan kesadaran masyarakat untuk melakukan penghematan dalam penggunaan listrik. Sistem ini membutuhkan data masukan berupa jumlah pemakaian listrik dalam 6 bulan terakhir, yang selanjutnya akan dibentuk pola penggunaan listrik dari setiap pengguna menggunakan analisis regresi linier. Selanjutnya dari pola yang diperoleh, diambil informasi pemakaian listrik perhari untuk dijadikan ambang batas pada pemberian peringatan pemborosan yang diprediksi akan terjadi. Sedangkan untuk penyebaran informasi ke pengguna tentang prediksi pemborosan, sistem ini menggunakan fasilitas SMS Gateway. Hasil penelitian ini adalah sistem yang dapat memberikan peringatan kepada pengguna jika penggunaan listriknya sudah melebihi ambang batas tertentu.Kata kunci — Sistem peringatan dini, pemborosan penggunaan listrik, analisis regresi linier, sms gateway. Abstract — Nowadays almost Indonesian people get inefficient management on the electricity usage. While,  Indonesia is still use steam power plant to produce the electricity power, which require fuel from non-renewable natural resouces. So the highness of demand and the occurrence of inefficiency from the electricity usage may increase the consumption of natural resource and the air pollution. Therefore, a solution through an early warning system are proposed in this study, that would increase awareness of the people to use the electricity power become more efficient. This system require the data of electricity usage from each customers in the last 6 months, that will be generated the electricity usage trend from each customers using linear regression analysis. Furthermore from the trend data obtained, the daily electricity usage information will be taken to use as a threshold for giving the inefficiency warnings from electricity usage that will occur from the available prediction. Moreover, in this study also use SMS Gateway for send the information of inefficiency electricity usage prediction automatically to each customers. Finally, the experimental result from this study is the system that can provide a warning to customers if their electricity usage run over the certain thresholds.Keywords— Early warning system, inefficient of electricity usage, linear regression analysis, sms gateway.

The changes in lifestyle of the global society in the era of digital world development have made the smartphone technology penetration to rise continually. This condition can increase business opportunities, especially e-commerce activities that utilize technology and the internet in terms of promotions and transactions. The efficiency and effectiveness is an interesting focus that is discussed in this issue. For example, in services or products searching for a wedding where many customers still feel difficult and need a long time to find the desired things. The existence of a recommendation system also has not been able to help, especially for users who are newly registered to the system. This is because most of them will provide recommendations based on a history of user activity. Therefore, this study applies the content-boosted collaborative filtering (CBCF) method to improve the ability of the recommendation system in providing recommendations for weddings, especially for a new user. The obtained results are then compared with two commonly used methods, content-based recommendations (CB) and collaborative filtering (CF). Based on the experimental results, it can be concluded that CBCF can maintain the quality of good recommendations for long registered users with an accuracy of 84% and also can provide recommendations for new users with an accuracy of 54% which is cannot be solved by CB or CF methods.Key Word: digital businesses, wedding vendors/organizers, recommendation system, content-boosted collaborative filtering  AbstrakPerubahan pola kehidupan masyarakat global pada era perkembangan dunia digital membuat penetrasi dari teknologi telepon pintar terus menaik. Kondisi ini dapat meningkatkan kesempatan bisnis khususnya kegiatan jual beli yang memanfaatkan teknologi dan internet dalam hal promosi dan transaksi. Efisiensi dan efektifitas proses menjadi fokus yang terus menarik dibahas dalam hal ini. Sebagai contoh, pada pencarian layanan atau produk untuk pernikahan yang mana banyak pelanggan masih merasakan kesulitan dan membutuhkan waktu yang lama untuk mencari sesuatu yang diinginkannya. Keberadaan sistem rekomendasi juga belum bisa membantu terlebih bagi pengguna yang baru terdaftar pada sistem. Hal ini dikarenakan kebanyakan sistem akan memberikan rekomendasi berdasarkan rekam jejak aktifitas pengguna. Maka itu, pada penelitian ini diusulkan penerapan metode content-boosted collaborative filtering (CBCF) untuk meningkatkan kemampuan sistem rekomendasi dalam pemberian rekomendasi untuk acara pernikahan, khususnya pada pengguna baru. Hasil yang diperoleh selanjutnya dibandingkan dengan dua metode yang umum digunakan yaitu content based recommendation (CB) dan collaborative filtering (CF). Berdasarkan hasil penelitian yang diperoleh, dapat disimpulkan bahwa CBCF dapat mempertahankan kualitas pemberian rekomendasi yang baik untuk pengguna lama dengan akurasi sebesar 84% serta mampu memberikan rekomendasi untuk pengguna baru dengan akurasi 54% yang mana kondisi ini tidak bisa diselesaikan oleh metode CB ataupun CF.Kata Kunci: bisnis digital, penyedia jasa acara pernikahan, sistem rekomendasi, content-boosted collaborative filtering

The utilization of smartphones that grow continuously is as a result of the changing lifestyle from the peoples in the growing digital world era. This condition can be seen on the large penetration of smartphones in half of the world society. The high smartphones utilization can increase the chance of many businesses, especially in online businesses that are used for promotions and transactions. The efficient and effective process become the main issues in technology development. One example is to meet the needs of wedding services in online business, which most users still have difficulties or need more time in finding the product as desired. Therefore, a recommendation system concept is applied in this research that is able to help the process of product promotion or searching specifically related to new products and involve new users. The content-boosted collaborative filtering method is used in these systems that is implement two previous methods, namely content-based that is used to form a full product rating matrix by a user, while collaborative filtering is used to make recommendations. Based on the experimental results that the system can recommend with 69% accuracy and helpful especially for newly added items or newly registered users.

VRP is a common problem that occurred in logistics, including determination a route of products from the source to the destination. VRPTW is variation of VRP that use routing concepts in the serving process at the certain time interval. Recently, many methods are used to solve this optimization problem, for example ACO. LTKC-ACO was developed to improve the ACO solutions that apply LTKC to obtain a number of classes that are considered as the candidate list in ACO. Local Search is also used to avoid ACO getting stuck in the local optimum. In this study, two types of LTKC-ACO are developed that’s related to time windows parameter usage in clustering. The experimental result of 56 Solomon’s datasets showed that LTKC-ACO can improve the ACO solutions on 73,21% of datasets and can out performed then the other methods, especially on the datasets that have longer scheduling of service time.