Spam pada Instagram (IG) umumnya berupa komentar yang dianggap mengganggu karena tidak berhubungan dengan foto atau video yang dikomentari. Spam pada komentar dapat menyebabkan beberapa dampak negatif seperti menyulitkan untuk mengikuti diskusi pada komentar yang dipenuhi oleh komentar spam dan menyebabkan seseorang tampak populer karena jumlah komentarnya banyak walaupun pada kenyataannya lebih banyak komentar yang berupa spam. Penelitian ini mencoba untuk membangun model yang dapat melakukan identifikasi komentar spam pada IG. Komentar pada IG berbentuk teks, sehingga pada penelitian ini digunakan metode-metode pengolahan teks. Untuk identifikasi digunakan metode Support Vector Machine (SVM). Data komentar yang digunakan pada penelitian ini dikumpulkan dari komentar-komentar pada foto atau video yang dibagikan oleh aktor dan artis Indonesia yang memiliki pengikut (follower) paling banyak di IG. Dari hasil penelitian didapatkan model identifikasi komentar spam dengan metode SVM menghasilkan tingkat akurasi 78,49% yang lebih baik jika dibandingkan dengan model pembanding yang menggunakan metode NB (77,25%). Penelitian ini juga menguji beberapa proporsi data pelatihan yang berbeda-beda dan hasilnya metode SVM tetap lebih baik dibandingkan dengan metode NB. Hasil lain dari penelitian ini adalah tahap pre-processing dan stemming yang harus disesuaikan terutama untuk dukungan terhadap pengolahan karakter-karakter unicode dan simbol-simbol khusus yang banyak ditemukan pada komentar-komentar di IG.
The use of Information and Communication Technology (ICT) in agriculture has become one of the steps to improve agricultural efficiency, effectiveness, productivity, and also expected to encourage the creation of Precision Agriculture. Precision agriculture has an impact on the efficiency of operational costs to increase margins in the production of agricultural products using ICTs. One of the problems that often arise in agriculture is related to the management of agricultural land in each farmer group area. This information is closely related to the needs of agricultural production facilities and infrastructure, such as the need for fertilizers, seeds, and other resources. Web Mapping System is one of the systems to assist in land or area mapping. In this study, the Web Mapping System is expected to be used to help at agricultural land mapping, owned by farmer members of farmer groups. The developed system will store spatial data from farmland members and farmer groups. The Web Mapping System was developed using the Rapid Application Development (RAD) method, where there are several iterative processes. The result of this study is the Web Mapping System for agricultural land. With this application, farmers can find out the status of the land being cultivated or owned. In addition, the Web Mapping System can record the status of the existing land in a farmer group and the need for agricultural production facilities and infrastructure. Further, the Web Mapping System also provides information in a dashboard that can help farmer groups to manage the land owned by each farmer who is a member of the group.
The twitter provides a kind of relation between users in specific form. When someone follow others, it doesn’t mean that she/he know well about them. We have defined a friend relationship between users in twitter as connection following and follower between two users. Based on this definition we develop a system to get friends and also friends of friends relation from a specific user. We use twitter API to get following and follower list and then construct a graph that represent a social network between those users. From this graph, we analyse the centrality using SNA (Social Network Analysis) method, i.e. closeness and betweeness. We propose to use these methods in order to find out who is the most influence user in the his/her social network to spread out the tweet or information. With this system, user can know about their social network based on their friend list on twitter. Kata Kunci : Social Network Analysis, Betweenness Centrality, Closeness Centrality
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