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ANALISIS SENTIMEN WISATA BAHARI DI SULAWESI TENGGARA MEMANFAATKAN MEDIA SOSIAL TWITTER DENGAN MENGGUNAKAN METODE LEXICON-BASED Statiswaty Statiswaty; Rusnia Rusnia; Natalis Ransi
semanTIK Vol 3, No 2 (2017): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Sulawesi Tenggara memiliki potensi wisata bahari yang cukup besar yang masih perlu dikembangkan. Salah satu cara mengembangkannya adalah melalui analisis sentimen pada media sosial seperti Twitter. Twitter adalah sebuah media sosial yang memberikan kemudahan bagi penggunanya untuk membagi dan mengakses informasi. Pengguna jejaring sosial twitter tersebar di seluruh penjuru dunia dan diakses melalui berbagai macam perangkat teknologi. Melalui penggunaan twitter, berbagai tanggapan atau sentimen masyarakat pada suatu tempat wisata dapat diperoleh untuk mengetahui kekurangan yang dimiliki tempat wisata tersebut. Dengan demikian, berdasarkan tweet dari wisatawan, maka dapat dilakukan analisis sentimen pada wisata bahari di Sulawesi Tenggara.Untuk membangun sentiment classifier diperlukan sebuah metode di dalamnya. Metode yang digunakan dalam penelitian ini adalah Lexicon-Based yaitu metode untuk melakukan analisis sentimen yang berbasis kamus. Metode ini dapat mengidentifikasi sentimen dari setiap opinion words yang terdapat pada data tweetBerdasarkan hasil uji coba dan evaluasi yang telah dilakukan, maka sistem yang dibuat mampu memberikan informasi tentang opini positif,negatif dan netral masyarakat terhadap wisata bahari di Sulawesi Tenggara. Penelitian ini mendapatkan hasil akurasi 77,06 %. Kata Kunci—Analisis Sentimen, Lexicon-Based, Twitter, Wisata Bahari.

KLASIFIKASI JENIS PELAPORAN DI LAMAN PROPAM POLDA SULAWESI TENGGARA MENGGUNAKAN METODE ROCCHIO Muh Saiful; Natalis Ransi; Jumadil Nangi
semanTIK Vol 5, No 1 (2019): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Service is the major thing in an organization. PROPAM Polda Sultra is one of the government institutions that have utilized telecommunications technology, namely complaints or online reporting pages. This technology is used to simplify and accelerate the delivery of information from the public to PROPAM Polda Sultra either in the form of complaints or reports for police who violate. The increasing number of reports of public complaints every day resulted in many reports that have not been responded to or unread. Therefore, the need to classify complaints reports automatically is needed to make time and human resources effectively in grouping complaints reports. The research was conducted with using Text Mining, the Rocchio method and using Tf-IDF weighting.Based on the results of testing, Rocchio algorithm has a good performance for the classification of types complaint report. This is evidenced in manual testing and system testing using complain report and then classified into eighth categories of Immoral, Traffic Accident, Narcotics, Poor Service, Persecution, Threatening, Insult and Deviations in Carrying Out Tasks (Case Handling). The results of classification using 79 reports obtained 89,87% accuracy.Keywords—Service, Public Complaints, Rocchio, Text Mining, TF-IDFDOI : 10.5281/zenodo.3255093

IMPLEMENTASI TEXT MINING KLASIFIKASI SKRIPSI MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Apriliana Apriliana; Natalis Ransi; Jumadil Nangi
semanTIK Vol 3, No 2 (2017): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Pada era perkembangan teknologi saat ini, skirpsi dapat dilihat menggunakan internet seperti TAKP Teknik Informatika yang merupakan salah satu website skripsi Teknik Informatika Universitas Halu Oleo yang sering dikunjungi jika telah menyelesaikan skripsi. Kategori skripsi yang digunakan adalah tiga kategori, yaitu Rekayasa Perangkat Lunak, Komputasi berbasis jaringan, dan Komputasi Cerdas Visual, dan dimana data skripsi tersebut diambil dari situs TAKP Teknik Informatika dan Perpustakaan Prodi Teknik Informatika.Terkadang pengklasifikasian kategori skripsi masih menjadi kendala.Untuk mempermudah dalam pengklasifikasian kategori skripsi, diperlukan sebuah sistem dengan menggunakan metode text mining sebagai salah satu alternatif untuk menyelesaikannya.Berdasarkan hasil pengujian, Algoritma Naïve Bayes Classifier memiliki kinerja yang baik untuk klasifikasi skripsi. Hal ini dibuktikan pada pengujian manual dan pengujian sistem menggunakan abstrak skripsi kemudian skripsi diklasifikasikan pada 3 kategori yaitu rekayasa perangkat lunak, komputasi berbasis jaringan , dan komputasi cerdas visual. Hasil klasifikasi menggunakan 51 skripsi uji didapatkan akurasi 94,11%. Kata kunci—Skripsi, Text Mining, Naïve Bayes Classifier.

PENERAPAN METODE REGRESI POLINOMIAL ORDE n PADA PENGEMBANGAN APLIKASI INVENTORY (STUDI KASUS PT. LANDIPO NIAGA RAYA) Fitria Rihin Uyun; La Ode Muh. Golok Jaya; Natalis Ransi
semanTIK Vol 5, No 1 (2019): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Inventory or inventory management system is one of the problems often faced by the distributor company. Processing and analyzing data on the sale of goods at the company is very important to get an overview and information about inventory data in the coming period by using sales data in the previous period, then an application or system is made with the Data Mining field with one of its predictions with using the Polynomial Regression method. This system predicts by selecting products, orders and periods with prediction results of 324,076 for Indomie Goreng Spesial Jumbo products. After making a prediction, a forecasting test is carried out by calculating the error value and relative errors with the result of error value = 2,595 and relative error = 1.82%.Keywords— Forecasting, Polynomial Regression, InventoryDOI : 10.5281/zenodo.3255112

APLIKASI PENGAMANAN FILE BERTIPE *.PDF PADA VIDEO *.MP4 MENGGUNAKAN KRIPTOGRAFI VERNAM CIPHER DAN STEGANOGRAFI END of FILE Mulatifa Laliha; Sutardi Sutardi; Natalis Ransi
semanTIK Vol 5, No 1 (2019): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Security and confidentiality of messages in the communication process between the sender and receiver is an important thing that must be maintained so that the message would be difficult if not known by unauthorized parties. Cryptography Vernam Cipher is symmetric cryptography that used one time for a message and not reused. Steganography End of File (EoF) is one technique to insert data at the end of the file. Combine Vernam Cipher cryptography and EoF steganography on this research with a case study how the implementation of the security of *.pdf files on *.mp4 video. Based on the test results of *.pdf file encryption and steganography in video *.mp4 successfully performed on the size of small file size for use Vernam Cipher cryptography, plaintext length, and key length must be the same length, so that for large files will take a long time. The results of stegano show that the video files look like the original video can be viewed directly without that already is inserted in the video *.pdf, for EoF does not affect the quality of the video. It is concluded that the incorporation of Vernam Cipher Cryptography and EoF steganography successfully, where the process of implementing the algorithms when combined requires an average time of 65 seconds on the side Vernam Cipher cryptographic application due to the type of encryption key length is equal to the length of the plaintext. Keywords—End of File, Cryptography, Steganography, Vernam CipherDOI : 10.5281/zenodo.3253459

APLIKASI DAERAH RAWAN PENYAKIT MENGGUNAKAN ALGORITMA COMPLETE LINKAGE CLUSTERING Uun Amalia Ramadhani; Natalis Ransi; Jumadil Nangi
semanTIK Vol 5, No 1 (2019): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Kendari City Health Office is a group that has one task to control the spread of a certain particular disease. To carry out its duties and functions, ideally, the Health Office must have the ability to divide areas that are vulnerable and not prone to disease. To facilitate the dividing, this study was made which aims to build an application that is implemented using the complete-linkage clustering method by forming clusters of data on the number of cases of the disease in 10 sub-districts in Kendari City in 2012 to 2016. Identified diseases are DHF, Diarrhea, and TB. Algorithm Complete Linkage Clustering is a group analysis method that attempts to build a hierarchy of data groups, grouping data with two or more objects that have the closest similarity, then proceed to another object that has a second closeness. The results showed that the areas prone to DHF were Kadia and Wua-Wua sub-districts with an index value of 47.80. Areas that are prone to Diarrhea disease are Puuwatu sub-district with an index value of 1181.40, area which is susceptible to TB disease is West Kendari sub-district with an index value of 92.40. The system can group and map disease-prone areas in the city of Kendari, using Complete Linkage Clustering.Keywords—Complete-Linkage Clustering, Health Service, Dengue Fever, Diarrhea, Tuberculosis (TBC) DOI : 10.5281/zenodo.3183951

PENERAPAN OPERASI HIMPUNAN DAN FUNGSI AGREGASI PADA PERANCANGAN BASIS DATA ALUMNI UNIVERSITAS HALU OLEO Aswani Aswani; Natalis Ransi; Rahmat Ramadhan
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Halu Oleo University is building an integrated university database with a centralized database system. One of the data that is integrated is the alumni database. The alumni database can be designed using a relational database system. According to [1] the relational database can be an alternative because it has the advantage of storage capacity. Some basic mathematical theories such as set operations can be used to design and develop a database. Furthermore, the agreement function can be used to retrieve information from a database. In this research will be done on the database design alumni of Halu Oleo University by applying the approach of set operation and aggregation function.Keywords— Set Operation, Aggregation Function, Alumni DatabaseDOI : 10.5281/zenodo.1343370

IMPLEMENTASI METODE TREND PROJECTION DENGAN ALGORITMA TREND LEAST SQUARE PADA SISTEM INVENTORY BARANG La Sufu; Bambang Pramono; Natalis Ransi
semanTIK Vol 6, No 1 (2020): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Permasalahan yang terjadi di PT. Pinus Merah Abadi Kendari pada kegiatan persediaan barang adalah jumlah barang yang harus di pesan ke pabrik tidak menentu karena ketidakpastian informasi barang yang tersedia digudang. Oleh karena itu, PT. Pinus Merah Abadi Kendari memerlukan suatu alat bantu berupa perangkat lunak atau sistem yang dapat membantu memudahkan dan memaksimalkan kinerja pegawai administrasi gudang atau manajer perusahaan dalam meramalkan atau memprediksi jumlah barang yang harus di pesan ke pabrik untuk periode berikutnya. Untuk memudahkan dalam memprediksi persediaan barang tersebut maka dibuat penelitian yang bertujuan untuk membangun sebuah sistem yang dapat memprediksi penjualan barang dengan cara mengimplementasikan metode Trend Projection.Trend Projection merupakan metode peramalan yang digunakan untuk melihat trend dari data deret waktu yang diketahui melalui persamaan Trend Least Square. Data yang digunakan merupakan data penjualan barang PT. Pinus Merah Abadi Kendari. Jenis produk yang digunakan Nabati RCE 8-gram yaitu penjualan dari Bulan Januari 2016 sampai Desember 2018. Berdasarkan hasil analisis dan pengujian sistem, maka sistem ini dapat meramalkan penjualan produk nabati dibulan tertentu dengan syarat data yang digunakan minimal tiga periode.Kata kunci; Trend Projection, Trend Least Square, Persediaan Barang

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