The rejection on ratification of the revision of Indonesian Code Law or known as RKUHP and Corruption Law raises several opinions from various perspectives in social media. Twitter as one of many platforms affected, has more than 19.5 million users in Indonesia. Twitter is one of many social media in Indonesia where people can share their views, arguments, information, and opinions from all points of view. Since Twitter has a great diversity of users, it needs a system which is designed to determine the opinion tendency towards the problems or objects. The purpose of this study is to analyze the sentiment of Twitter users' tweets to reject the revision of the Law whether they have positive or negative sentiments using the Agglomerative Hierarchical Clustering method. The data that being used in this study were obtained from the results of crawling tweets based on hashtag (#) (#ReformasiDikorupsi). The next stage is pre-processing which consists of case folding, tokenizing, cleansing, sanitizing, and stemming. The extraction features Opinion words and Term Frequency (TF) which performs the process automatically. In the clustering stage, two clusters use three approaches; single linkage, complete linkage and average linkage. In the accuracy calculation phase, the writer uses the error ratio, confusion matrix, and silhouette coefficient. Therefore, the results are quite good. From 2408 tweets, the highest accuracy results are 61.6%.

Abstrak - Bermain game tidak hanya mendapatkan kesenangan semata namun dapat dipakai sebagai salah satu metode untuk pembentukan karakter, dan pembelajaran anak usia dini. Perkembangan game saat ini memang sangat pesat, berawal dari game konsol seperti (Game boy, SEGA, PS 1, PS 2, Xbox 360), hingga muncul game dengan sistem android. Banyaknya game yang beredar pada masyarakat menimbulkan masalah, terutama dalam pemilihan game dengan kriteria dan kebutuhan yang tepat untuk anak usia dini. Pemilihan sebuah game untuk anak usia dini dapat dilihat dari spesifikasi, jumlah pemain, harga, dan jenis gamenya. Mengkombinasikan semua hal tersebut bukanlah hal yang mudah, apalagi banyaknya game yang muncul saat ini membutuhkan waktu yang lama untuk menemukan game yang sesuai. Perancangan aplikasi Sistem Pendukung Keputusan (SPK) pemilihan game android untuk anak usia dini ini menggunakan metode Technique for Order Preference by Similiarty to Ideal Solution (TOPSIS) berdasarkan beberapa kriteria yaitu rating game, tanggal rilis, jumlah download, harga item termurah, dan ukuran download. Aplikasi yang dirancang bertujuan untuk membantu pemain memilih game dengan tepat dan cepat. Hasil rancangan aplikasi ini diharapkan dapat membantu para pengguna khususnya orang tua untuk memilih game terbaik untuk anak-anak mereka. Diharapkan hasil rancangan ini kemudian akan dilanjutkan dengan membangun aplikasi SPK sehingga dapat bermanfaat untuk para pencinta game   Kata kunci : Anak, android, game, SPK, Topsis.

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At educational institutions, especially at University, writing scientific papers is a skill that must be possessed by academics such as educators and students. However, writing scientific papers is not easy, there are many provisions and rules that need to be fulfilled. Several studies show that there are still many academics who make mistakes in writing their scientific papers. Some of the mistakes made include punctuation errors, typographic writing errors and the use of non-standard words in Indonesian. Researchers in Indonesia have developed various spelling error detection applications in Indonesian-language scientific papers. This study tries to analyze the development of an application framework for detecting Indonesian spelling errors from various assessment indicators. This study tries to compare the application framework for detecting spelling errors between other studies with proposed application that named KEBI 1.0 Checker. KEBI 1.0 Checker as a spelling error detection application has 3 main features, namely detecting errors in the use of punctuation marks, writing typography, and using non-standard words in accordance with the standards of the Big Indonesian Dictionary and the General Guidelines for Indonesian Spelling. In addition, this study tries to objectively examine the complexity of the features, advantages and disadvantages, methods and the level of accuracy of each application. The results of the analysis show that KEBI 1.0 Checker has the completeness of features, fast computation time, easy application access, and an attractive user interface. However, it is still necessary to improve the precision in correcting spelling errors in typographic words.

To prepare for the wedding, it takes energy and enough time for the program to work as it wishes. The dream of having a beautiful and exciting wedding is every couple's dream. Surabaya was one of the towns with the heavy population. Surabaya was one of the towns with the heavy population. Such conditions are problematic because if couples who are going to celebrate the wedding don't have enough land to host a wedding venue in Surabaya. Gathering information regarding a wedding venue takes a long time. On the question of obtaining it, a wedding venue customization system was developed to make it easier for the tenants to select the appropriate venue. One algorithm that can be used to make recommendations with multiple criteria and alternatives is Technique For Order of Preference by Similarity to Ideal Solusition (TOPSIS). TOPSIS is an algorithm with the highest alternative proceeds to have the shortest distance from the ideal positive solution and the farthest from the negative ideal solution to the criteria used by wedding venue elections to include rent costs, the sum of housing, facilities and the exact distance from the tenants' location to the building. To design this recommendation system, SDLC development methods are used that have grooves of grooves at every step made. Results obtained through two testing stages are functional and non-functional testing. At functional testing were black box testing techniques and 100% obtained results. Non-functional testing is done to shift from system recommendation output to manual calculating output. Results derived from non-functional testing by 100%.