Article Per Year (5 Year)
p-Index From 2021 - 2026
0.983
P-Index
This Author published in this journals
All Journal Jurnal Manajemen dan Organisasi TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Scan : Jurnal Teknologi Informasi dan Komunikasi Journal of Information Systems Engineering and Business Intelligence Jurnal Informatika dan Multimedia Jurnal Komputer Terapan Darmabakti Cendekia: Journal of Community Service and Engagements Jurnal Layanan Masyarakat (Journal of Public Service) Jurnal Dinamika Sosial Ekonomi Jurnal Informatika dan Multimedia
Tesa Eranti Putri
Universitas Airlangga
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Engineering Environmental Science Library & Information Science Public Health Social Sciences Other

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 12 Documents
Search

 1   2 
TERM WEIGHTING BASED ON INDEX OF GENRE FOR WEB PAGE GENRE CLASSIFICATION Sugiyanto, Sugiyanto; Rozi, Nanang Fakhrur; Putri, Tesa Eranti; Arifin, Agus Zainal
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 12, No 1, Januari 2014
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (402.086 KB) | DOI: 10.12962/j24068535.v12i1.a43

Abstract

Automating the identification of the genre of web pages becomes an important area in web pages classification, as it can be used to improve the quality of the web search result and to reduce search time. To index the terms used in classification, generally the selected type of weighting is the document-based TF-IDF. However, this method does not consider genre, whereas web page documents have a type of categorization called genre. With the existence of genre, the term appearing often in a genre should be more significant in document indexing compared to the term appearing frequently in many genres despites its high TF-IDF value. We proposed a new weighting method for web page documents indexing called inverse genre frequency (IGF). This method is based on genre, a manual categorization done semantically from previous research. Experimental results show that the term weighting based on index of genre (TF-IGF) performed better compared to term weighting based on index of document (TF-IDF), with the highest value of accuracy, precision, recall, and F-measure in case of excluding the genre-specific keywords were 78%, 80.2%, 78%, and 77.4% respectively, and in case of including the genre-specific keywords were 78.9%, 78.7%, 78.9%, and 78.1% respectively.
Pengelompokan Dokumen Berita Berbahasa Indonesia Menggunakan Reduksi FiturInformation Gain dan Singular Value Decomposition dalam Fuzzy C-MeansClustering Sari, Yuita Arum; Putri, Tesa Eranti; Hapsani, Anggi Gustiningsih
Jurnal Informatika dan Multimedia Vol 10 No 1 (2018): Jurnal Volume 10, No.1 (2018)
Publisher : Teknik Informatika Politeknik Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Koran dan berita online merupakan media informasi digital saat ini yang proses pembaruan informasinya sangat mudah dan fleksibel. Kemudahan ini memungkinkan penulis berita untuk mengunggah informasi baru di waktu kapanpun dan dimanapun. Hal ini menyebabkan data dokumen berita sangat banyak dan tidak teratur sehingga perlu dilakukan pengelompokan berita sesuai dengan kontennya. Pengelompokanberita sesuai content dapat membantu pembaca untuk membaca berita dengan topiktertentu sesuai dengan minatnya. Proses pengelompokan informasi berita diimplementasikan denganbeberapa tahap, yaitu preprocessing dan pengelompokan dokumen. Preprocessing dilakukan dengan mengimplementasikan metode kombinasi reduksi fitur Document Frequency (DF) dan Information Gain (IG) Thresholding dalamSingular Value Decomposition (SVD). Algoritme SVD dipilih karena memiliki kemampuan untuk melakukan dekomposisi pada matriks dokumen-term, sehingga diperoleh matriks yang masih menyimpan informasi penting dengan ukuran dimensi yang lebih kecil.Pada tahap pengelompokan dokumen berita dilakukandengan algoritme Fuzzy C-Means. Hasil uji coba akurasipengelompokan dokumen berita menunjukkan bahwa pengelompokan yang dilakukan memberikan hasil pengkategorian yang cukup akurat dengan tingkat akurasi rata-rata 74,5 % (IG threshold 0.5, k = 5). Hal tersebut menunjukkan bahwa pengelompokan dokumen menggunakan IG dan SVD dengan FUZZY C-MEANS adalah sesuai dengan kebutuhan.
HIERARCHICAL MULTI-VIEWPOINT SELF ORGANIZING MAP PADA PENGELOMPOKAN PENGGUNA UNTUK MENGETAHUI PROFIL UNDUH DI LINGKUNGAN KAMPUS Putri, Tesa Eranti; Fatichah, Chastine; Purwitasari, Diana
SCAN - Jurnal Teknologi Informasi dan Komunikasi Vol 9, No 3 (2014)
Publisher : Universitas Pembangunan Nasional "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/scan.v9i3.860

Abstract

Abstrak. Fasilitas internet kampus terkadang disalahgunakan untuk mengunduh data yang tidakterkait akademis, sehingga mengganggu pengguna yang memerlukan internet untuk kepentinganakademis. Guna memonitor pengunduhan di kampus, diperlukan profil unduh. Profil dapat dibentukdari pengelompokan pengguna. Penelitian ini mengajukan pemodelan untuk pengelompokanpengguna berupa Self Organizing Map hierarchical multi-viewpoint. Pengelompokan dilakukanberdasarkan jumlah transaksinya, dilihat dari banyak viewpoint. Setiap viewpoint membentuk petatersendiri, disusun berjenjang (hierarchical), kemudian dilatih menggunakan gabungan fiturviewpoint sekarang dengan viewpoint di bawahnya. Pengujian dilakukan dengan analisis manualhasil pengelompokan. Dari pengujian, diperoleh fitur viewpoint yang memberikan gambaran profilunduh yang paling jelas dan lengkap adalah domain email.Kata kunci. profil unduh, pengelompokan pengguna, web usage mining, Self Organizing MapHierarchical Multi-viewpoint
Short-term photovoltaics power forecasting using Jordan recurrent neural network in Surabaya Aji Akbar Firdaus; Riky Tri Yunardi; Eva Inaiyah Agustin; Tesa Eranti Putri; Dimas Okky Anggriawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14816

Abstract

Photovoltaic (PV) is a renewable electric energy generator that utilizes solar energy. PV is very suitable to be developed in Surabaya, Indonesia. Because Indonesia is located around the equator which has 2 seasons, namely the rainy season and the dry season. The dry season in Indonesia occurs in April to September. The power generated by PV is highly dependent on temperature and solar radiation. Therefore, accurate forecasting of short-term PV power is important for system reliability and large-scale PV development to overcome the power generated by intermittent PV. This paper proposes the Jordan recurrent neural network (JRNN) to predict short-term PV power based on temperature and solar radiation. JRNN is the development of artificial neural networks (ANN) that have feedback at each output of each layer. The samples of temperature and solar radiation were obtained from April until September in Surabaya. From the results of the training simulation, the mean square error (MSE) and mean absolute percentage error (MAPE) values were obtained at 1.3311 and 34.8820, respectively. The results of testing simulation, MSE and MAPE values were obtained at 0.9858 and 1.3311, with a time of 4.591204. The forecasting has minimized significant errors and short processing times.
Short-Term Forecasting of Electricity Consumption Revenue on Java-Bali Electricity System using Jordan Recurrent Neural Network Tesa Eranti Putri; Aji Akbar Firdaus; Wilda Imama Sabilla
Journal of Information Systems Engineering and Business Intelligence Vol. 4 No. 2 (2018): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1369.973 KB) | DOI: 10.20473/jisebi.4.2.96-105

Abstract

Depending on the day and time, electricity consumption tends to fluctuate and directly affects the amount of gained revenue for the company. To anticipate future economic change and to avoid losses in calculating the company’s revenue, it is essential to forecast electricity consumption revenue as accurate as possible. In this paper, Jordan Recurrent Neural Network (JRNN) was used to do short term forecasting of the electricity consumption revenue from Java-Bali 500 kVA electricity system. Seven JRNN models were trained using electricity consumption revenue between January-March 2012 to predict the revenue of the first week of April 2012. As performance comparators, seven traditional feed forward Artificial Neural Network (ANN) models were also constructed. The forecasting results were as expected for both models, where both producing steady repeating pattern for weekdays, but failed quite poorly to predict the weekends’ revenue. This suggests that in Indonesia, weekends’ electricity consumption revenue has different characteristics than weekdays. Evaluation of the prediction result was carried out using Sum of Square Error (SSE) and Mean Square Error (MSE). The evaluation showed that JRNN produced smaller SSE and MSE values than traditional feed forward ANN, thus JRNN could predict the electricity consumption revenue of Java-Bali electricity system more accurately.
Prediksi Ketepatan Waktu Lulus Mahasiswa dengan k-Nearest Neighbor dan Naïve Bayes Classifier Wilda Imama Sabilla; Tesa Eranti Putri
Jurnal Komputer Terapan  Vol. 3 No. 2 (2017): Jurnal Komputer Terapan November 2017
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (309.758 KB)

Abstract

Salah satu aspek pengukuran kualitas dalam evaluasi keberhasilan penyelenggaraan pendidikan tinggi adalah ketepatan lulus mahasiswa. Jumlah prosentase mahasiswa yang lulus tepat waktu menjadi indikator keberhasilan pelaksanaan proses belajar mengajar di suatu program studi. Penelitian ini menawarkan penggunaan metode penggalian data untuk memprediksi waktu lulus mahasiswa menggunakan dua metode yaitu k-Nearest Neighbour dan Naïve Bayes Classifier. Hasil dari penelitian ini berupa sistem yang dapat memprediksi ketepatan waktu lulus. Uji coba dilakukan dengan menggunakan data lulusan mahasiswa D3 Sistem Informasi Universitas Airlangga. Hasil uji coba menunjukkan bahwa metode k-Nearest Neighbor menghasilkan akurasi lebih tinggi dibandingkan dengan Naïve Bayes Classifier. Akurasi tertinggi diperoleh dengan menggunakan metode k-Nearest Neighbor yaitu sebesar 98.7%. Oleh karena itu dapat disimpulkan bahwa sistem yang dibangun pada penelitian ini mampu memprediksi ketepatan waktu lulus dengan akurasi cukup tinggi.
Pengelompokan Dokumen Berita Berbahasa Indonesia Menggunakan Reduksi FiturInformation Gain dan Singular Value Decomposition dalam Fuzzy C-MeansClustering Tesa Eranti Putri; Yuita Arum Sari; Anggi Gustiningsih Hapsani
Jurnal Informatika dan Multimedia Vol. 10 No. 1 (2018): Jurnal Informatika dan Multimedia
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jim.v10i1.598

Abstract

Koran dan berita online merupakan media informasi digital saat ini yang proses pembaruan informasinya sangat mudah dan fleksibel. Kemudahan ini memungkinkan penulis berita untuk mengunggah informasi baru di waktu kapanpun dan dimanapun. Hal ini menyebabkan data dokumen berita sangat banyak dan tidak teratur sehingga perlu dilakukan pengelompokan berita sesuai dengan kontennya. Pengelompokanberita sesuai content dapat membantu pembaca untuk membaca berita dengan topiktertentu sesuai dengan minatnya. Proses pengelompokan informasi berita diimplementasikan denganbeberapa tahap, yaitu preprocessing dan pengelompokan dokumen. Preprocessing dilakukan dengan mengimplementasikan metode kombinasi reduksi fitur Document Frequency (DF) dan Information Gain (IG) Thresholding dalamSingular Value Decomposition (SVD). Algoritme SVD dipilih karena memiliki kemampuan untuk melakukan dekomposisi pada matriks dokumen-term, sehingga diperoleh matriks yang masih menyimpan informasi penting dengan ukuran dimensi yang lebih kecil.Pada tahap pengelompokan dokumen berita dilakukandengan algoritme Fuzzy C-Means. Hasil uji coba akurasipengelompokan dokumen berita menunjukkan bahwa pengelompokan yang dilakukan memberikan hasil pengkategorian yang cukup akurat dengan tingkat akurasi rata-rata 74,5 % (IG threshold 0.5, k = 5). Hal tersebut menunjukkan bahwa pengelompokan dokumen menggunakan IG dan SVD dengan FUZZY C-MEANS adalah sesuai dengan kebutuhan.
WEBSITE ONLINE PORTAL DESIGN OF SAJEN VILLAGE, PACET, MOJOKERTO Alifian Sukma; Rachman Sinatriya Marjianto; Tesa Eranti Putri
Jurnal Layanan Masyarakat Vol. 7 No. 1 (2023): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jlm.v7i1.2023.82-90

Abstract

Perkembangan teknologi yang semakin pesat memungkinkan untuk memperoleh berbagai macam informasi dimanapun dan kapanpun ia berada. Hal tersebut tentu sangat mempengaruhi pola konsumsi masyarakat baik di Indonesia maupun dunia. Indonesia sebagai salah satu negara berkembang dengan potensinya sebagai salah satu destinasi wisata baik lokal maupun mancanegara, tentu sangat bergantung dengan pola konsumsi yang ada pada era informasi saat ini. Fenomena konsumtif di era informasi ini sangat berpotensi dalam meningkatkan performa dari adanya potensi objek wisata di suatu wilayah. Berdasarkan latar belakang masalah tersebut melalui pemanfaatan teknologi informasi dan pelatihan teknis diharapkan mampu meningkatkan potensi Desa Sajen sebagai salah satu obyek pariwisata di Jawa Timur, Indonesia. Desa Sajen sendiri memiliki potensi dalam pariwisata yang didukung selain dari sumber daya alamnya, juga didukung dengan potensi-potensi kerajinan dari sumber daya manusia yang ada dan tinggal di Desa Sajen tersebut. Melalui pengabdian masyarakat ini, selain menunjang potensi pariwisata Desa Sajen melalui platform teknologi informasi, juga didukung dengan diadakannya pelatihan teknis mengenai pengelolaan teknologi informasi dan pemasarannya kepada warga Desa Sajen untuk dapat memaksimalkan potensi pariwisata Desa Sajen tersebut. Melalui Prodi D-3 Sistem Informasi mengembangkan sebuah portal online desa sebagai bentuk peningkatan exposure dari informasi dan potensi desa Sajen kepada masyarakat Indonesia.
Evaluation of Inventory Accounting Information Systems Using Pieces Method: A Study on SIMEDi’s Application Sauri, Sofyan; Firmandani, Wahyu; Suteja, Diana; Puspitasari, Leny; Putri, Tesa Eranti; Eriani, Izmi Dwira
Jurnal Manajemen dan Organisasi Vol. 15 No. 4 (2024): Jurnal Manajemen dan Organisasi
Publisher : IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmo.v15i4.60622

Abstract

This study aims to evaluate the SIMEDi inventory accounting information system in Perumda Perkebunan Kahyangan Jember. The method used in this study is a case study with a PIECES analysis approach. Data collection techniques were carried out by conducting interviews with the board of directors and staff who have access to SIMEDi. The PIECES approach involves six evaluation variables, namely performance, information, economic, control and security, efficiency and service. The results of the evaluation showed that SIMEDi meets the six PIECES variables, namely: all SIMEDi features have been running well (performance variables), the information produced by SIMEDi has met reliable input process output (information variables), the benefits generated from the implementation of SIMEDi are greater than the costs incurred (economic variables), SIMEDi has provided adequate system control to maintain the reliability of the information produced (control and security variables), SIMEDI makes inventory management at Perumda Kahyangan more efficient (efficiency variables), and SIMEDi is very user friendly and easy to operate (service variables). The SIMEDi Inventory Accounting Information System provides convenience and reliability for Perumda Perkebunan Kahyangan in managing inventory, especially for making appropriate and accurate decisions.
Enhancing Agricultural Industry's Performance Through Web-Based Inventory Accounting Information System Development Firmandani, Wahyu; Eriani, Izmi Dwira; Putri, Tesa Eranti; Sauri, Sofyan; Puspitasari, Leny
Jurnal Dinamika Sosial Ekonomi Vol. 25 No. 2 (2024): Jurnal Dinamika Sosial Ekonomi
Publisher : Agribusiness Department, Faculty of Agriculture, UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/jdse.v25i2.13834

Abstract

Perumda Perkebunan Kahyangan, which is one of the industries in the plantation sector, is experiencing difficulties in managing plantation commodity inventory, this is because recording is still done manually. The research aims to develop a webbased inventory accounting information system called SIMEDi which is in accordance with the needs of Perumda Perkebunan Kahyangan. The method used in this research is a case study faced by Perumda Perkebunan Kahyangan regarding inventory management which is still done manually, which has an impact on company performance. Meanwhile, the method used to develop web-based SIMEDi applications is the agile method, which allows the development process to be carried out simultaneously to produce quality applications that suit user needs through the stages of planning, analysis, design, implementation, testing, deploy and maintenance. This research produces a SIMEDi inventory accounting information system that has functions and features that accommodate adequate inventory management for companies including plantation and warehouse stock initiation transactions, harvest, internal procurement, external procurement, production, sales, plantation and warehouse stock adjustments and price input. acquisition. This application also helps top management not only know the amount of inventory held at each plantation and warehouse location, but also the profits and costs of each inventory sold. The SIMEDi application provides data and information support that is precise, accurate and can be accessed in real time via the website, so that companies are able to meet market needs well.
Co-Authors Agus Zainal Arifin Agustin, Eva Inaiyah Alifian Sukma, Alifian Anggi Gustiningsih Hapsani Anugrah, Esti Putri Arifianto, Deny Chastine Fatichah Diana Purwitasari Diana Suteja Dimas Okky Anggriawan Dyah Puspitasari Srirahayu, Dyah Puspitasari Elsyea Adia Tunggadewi Eriani, Izmi Dwira Firdaus, Aji Akbar Hapsani, Anggi Gustiningsih Nahdliyah, Sisca Dina Nur Nanang Fakhrur Rozi Prihasty, Wilda Puspitasari, Leny Rachman Sinatriya Marjianto Septriana, Maya Sofyan Sauri, Sofyan Sugiyanto, Sugiyanto Tiara Kusumaningtiyas, Tiara Wahyu Firmandani Wardhana, Ananthyo Whisnu Wilda Imama Sabilla Yuita Arum Sari Yunardi, Riky Tri