Damerau-Levenshtein Distance menentukan jarak atau jumlah minimum operasi yang dibutuhkan untuk mengubah satu string menjadi string lain, di mana operasi yang digunakan untuk menentukan tingkat kemiripian antar String adalah insertion, deletion, substitution dan transposition. Algoritma ini sendiri dapat juga digunakan untuk mengoreksi kesalahan kata. Namun, Algoritma Damerau-Levenshtein Distance mempunyai kelemahan, yaitu waktu pemrosesan yang lama. Pada perhitungan jarak antara dua string dengan algoritma Damerau-Levenshtein, setiap huruf dari kedua string akan dibandingkan dengan membuat matriks distance. Karena Kamus Bahasa Indonesia memiliki lebih dari 30.000 kata dasar, operasi perhitungan jarak akan dilakukan lebih dari 30.000 kali untuk setiap kesalahan. Penelitian ini mengusulkan peningkatan untuk mempersingkat waktu pemrosesan algoritma Damerau-Levenshtein dengan mengurangi baris dan kolom matriks distance. Hasil akhir yang diharapkan dari penelitian ini adalah waktu pemrosesan menjadi lebih cepat tanpa harus mengorbankan akurasi.

Public awareness regarding the environment that comes from waste management still requires special attention. Garbage is often an environmental problem not only in urban areas, but also in rural areas. Therefore, it is necessary to carry out mentoring activities in the form of intense socialization to increase understanding of waste management and utilization from various parties, including universities. The Action Movement for the Environment (GAUL) was one of the programs that aims to increase citizen understanding in waste management, and also involve the community directly in managing waste that can be recycled (re-use). Through the methods of observation, socialization, and participatory action, it is able to raise awareness and increase citizen understanding.

Most Muslims in Indonesia believe that the 'habaib' (the plural of the word 'habib') have a lineage from the Prophet Muhammad SAW, so their existence must be glorified and respected. Television media responded to this in various ways. The careers of the Habib expanded not only in the field of Islamic da'wah but also in politics, as shown by figures such as Habib Rizieq Shihab and the former organization he led, the Islamic Defenders Front (FPI). Television media highlighted the political roles of these habibs with various news constructions. The purpose of this study is to analyze the perspective of television media in framing news about the figure of Habib Rizieq Shihab and claims to be descendants of the Prophet Muhammad SAW and to find a model for framing television media in reporting about 'Habib' in the perspective of claiming descendants of the Prophet Muhammad SAW. This research uses the constructivism paradigm with qualitative research method with framing analysis approach. Namely through data collection techniques through several news broadcasts on three television media, interviews, and observations. The results of this study conclude that every television media report that reports about Islamic figures of Arab descent in Indonesia always brings up models and perspectives of news about the object being reported. The many roles of Habib such as Habib Rizieq Shihab are viewed with different perspectives by the news television media. Some Indonesian citizens of Arab descent who are predicated as 'habib' provide different perspectives for television coverage such as KompasTV, MetroTV, and TVOne. The television media KompasTV and MetroTV do not always agree that their reporting about the activities of the 'habaib' is related to the lineage of descendants of the Prophet Muhammad SAW.

One of the tasks in the field of marketing finance is to analyze customer data to find out which customers have the potential to do credit again. The method used to analyze customer data is by classifying all customers who have completed their credit installments into marketing targets, so this method causes high operational marketing costs. Therefore this research was conducted to help solve the above problems by designing a data mining application that serves to predict the criteria of credit customers with the potential to lend (credit) to Mega Auto Finance. The Mega Auto finance Fund Section located in Kotim Regency is a place chosen by researchers as a case study, assuming the Mega Auto finance Fund Section has experienced the same problems as described above. Data mining techniques that are applied to the application built is a classification while the classification method used is the Decision Tree (decision tree). While the algorithm used as a decision tree forming algorithm is the C4.5 Algorithm. The data processed in this study is the installment data of Mega Auto finance loan customers in July 2018 in Microsoft Excel format. The results of this study are an application that can facilitate the Mega Auto finance Funds Section in obtaining credit marketing targets in the future