Abstrak Desa Lepak merupakan desa yang berada di pulau Lombok Nusa Tenggara Barat dengan angka penduduk miskin cukup tinggi. Penelitian ini bertujuan untuk mengklasifikasi masyarakat di desa Lepak Kecamatan Sakra Timur Kabupaten Lombok Timur. Teknik pengumpulan data dilakukan dengan teknik studi dokumen. Teknik analisis data pada penelitian ini menggunakan metode Naïve Bayes Classifier, yang merupakan salah satu teknik pengklasifikasian dalam data mining. Berdasarkan hasil pengujian confusion matrix diperoleh klasifikasi masyarakat miskin di desa Lepak yang memang miskin adalah 148 record dari 156 record yang artinya terdapat 8 record yang error dimana ia lebih mirip dengan yang tidak miskin. Sedangkan untuk masyarakat tidak miskin terdapat 110 record dari 111 record yang memang tidak miskin dan sisanya 1 record error yang lebih mirip dengan miskin. Keakuratan data testing dalam memprediksi hasil klasifikasi yang menunjukkan masyarakat miskin dan tidak miskin dapat dilihat dari nilai acurasy yaitu sebesar 96.63% yang artinya termasuk dalam kategori good. Berdasarkan penelitian ini menunjukkan bahwa klasifikasi kelas untuk masyarakat desa Lepak adalah kelas dengan masyarakat miskin.

Indonesia is an equatorial country that has abundant natural wealth from the seabed to the top of the mountains, the beauty of the country of Indonesia also lies in the mountains that it has in various provinces, for example in the province of West Nusa Tenggara known for its beautiful mountain, namely Rinjani. The increase in outdoor activities has attracted many people to open outdoor shops in the West Nusa Tenggara region. Sales transaction data in outdoor stores can be processed into information that can be profitable for the store itself. Using a market basket analysis method to see the association (rules) between a number of sales attributes. The purpose of this study is to determine the pattern of relationships in the transactions that occur. The data used is the transaction data of outdoor goods. The analysis used is the Association Rules with the Apriori algorithm and the frequent pattern growth (FP-growth) algorithm. The results of this study are formed 10 rules in the Apriori algorithm and 4 rules in the FP-Growth algorithm. The relationship pattern or association rule that is formed is in the item "if a consumer buys a portable stove, it is possible that portable gas will also be purchased" at the strength level of the rules with a minimum support of 0.296 and confidence 0.774 at Apriori and 0.296 and 0.750 at FP-Growth.

This study aims to examine and analyze the effect of job satisfaction on organizational citizenship behavior, both on the direct and indirect effect on employees of favehotel Ahmad Yani Banjarmasin. This study uses an explanatory research method with a quantitative approach. The data analysis method used is descriptive analysis and path analysis. The study population was all employees of favehotel ahmad yani Banjarmasin and a sample of 67 respondents. The results of this study indicate that Job Satisfaction has a significant effect on Organizational Citizenship Behavior with a path coefficient value of 0.604. Organizational Citizenship Behavior has a significant effect on employee performance with a path coefficient value of 0.320. Job Satisfaction has a significant effect on Employee Performance with a path coefficient value of 0.280. Organizational Citizenship Behavior does not mediate job satisfaction on employee performance with a direct effect value that is greater than the indirect effect.

The aim of the research was to determine the effect of learning models on mathematics learning achievement viewed from students independence learning. The learning models compared were cooperative learning model of TAI GNT, cooperative learning model of TAI, and conventional model. The type of the research was a quasi-experimental research. The population was the tenth grade students of senior high school at East Lombok. The results of this research are as follows. (1) In each level of independence learning (high, medium, and low), TAI GNT model gives better mathematics learning achievement than TAI and conventional model, besides, TAI model gives better mathematic learning achievement than conventional model. (2) In each learning models (TAI GNT, TAI and conventional), the students with high independence learning have better mathematics learning achievement than the students with medium and low independence learning, and the students with medium independence learning have the same mathematics learning achievement as the students with low independence learning.

Seaweeds are marine macro algae that can be found attach to the bottom shallow coastal waters with subsrate as attached media. There are three major groups of seaweeds namely brown algae (Phaeophyta), red (Rhodophyta) and green (Chlorophyta). Sargassum sp is one of brown algae which mostly found in the Lhok Bubon Coastal West of Aceh. Recently, exploration of marine macroalgae as bioactive sources was investigated. Seaweed contains bioactive compound which can serve as a defense from ultraviolet radiation that caused hyperpigmentation effect. The aiming of this study is to analyse the tyrosinase inhibitory activity of Sargassum sp extract from Lhok Bubon Coastal Area, West of Aceh. The results shown that the methanol extract of Sargassum sp possess phytochemical properties such as fenol, alkaloid and triterpenoid. Tyrosinase inhibitory activity of Sargassum sp methanol extract  is the best extract which can be inhibit  monophenolase with  IC50 : 1111.49 µg/ml and IC50 = 1582.31 µg/ml in diphenolase pathway with kojic acid as positive control. Moreover, etyl asetate and n-hexane extract have no activity of tyrosinase inhibitor. Therefore, new finding of tyrosinase inhibitor agent from marine macroalgae Sargassum sp give the fruitfull information for cosmeceutical industry.Keywords : Lhok Bubon, Brown Algae, Sargassum sp, Tyrosinase Inhibitor