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All Journal Jurnal Silvikultur Tropika (JST) Jurnal Teknologi Informasi dan Ilmu Komputer IJIES (International Journal of Innovation in Enterprise System)
Trisminingsih, Rina
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Energy Engineering Environmental Science Social Sciences

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Implikasi Kebijakan Kebakaran Hutan dan Lahan di Indonesia: Kebutuhan Dukungan Teknologi Syaufina, Lailan; Sitanggang, Imas Sukaesih; Purwanti, Endang Yuni; Rahmawan, Hendra; Trisminingsih, Rina; Ardiansyah, Firman; Wulandari; Albar, Israr; Krisnanto, Ferdian; Satyawan, Verda Emmelinda
Journal of Tropical Silviculture Vol. 15 No. 01 (2024): Jurnal Silvikutur Tropika
Publisher : Departemen Silvikultur, Fakultas Kehutanan dan Lingkungan, Institut Pertanian Bogor (IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j-siltrop.15.01.70-77

Abstract

Kebakaran hutan dan lahan (karhutla) merupakan isu lingkungan yang penting di kawasan Asia Tenggara, terkait dengan polusi kabut asap yang melintas batas. Pemerintah Indonesia telah mengubah paradigma dengan memprioritaskan kegiatan pencegahan kebakaran dari pemadaman sejak tahun 2016. Penelitian ini bertujuan untuk melakukan tinjauan sistematik perkembangan kebijakan terkait karhutla dan untuk mengevaluasi penggunaan aplikasi mobile dan web dari Sistem Informasi Patroli Pencegahan Karhutla (SIPP Karhutla) di wilayah Sumatera dan Kalimantan. Metode penelitian mencakup: kajian pustaka secara sistematik kebijakan karhutla di Indonesia., survei lapangan, kuesioner, dan wawancara dengan para pemadam kebakaran di tujuh provinsi di Sumatera dan Kalimantan. Kebijakan terkait karhutla mengalami peningkatan sejak tahun 2014, yang mendorong perbaikan pengendalian karhutla. Aplikasi SIPP Karhutla telah digunakan secara luas di wilayah Sumatera dan Kalimantan. Aplikasi tersebut terbukti menurunkan waktu pencatatan dan pembuatan laporan patroli secara signifikan. Aplikasi ini mendukung kegiatan patroli secara efektif dan efisien. Kata kunci: manajemen kebakaran, Sistem Informasi Patroli Pencegahan Karhutla, polusi kabut asap lintas batas
Social Media Listening pada Instagram untuk Kasus Kebakaran Hutan di Indonesia Menggunakan Graph Clustering Trisminingsih, Rina; Kurniawan, Riski Adi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 2: April 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2688.601 KB) | DOI: 10.25126/jtiik.2019621270

Abstract

Social media listening merupakan salah satu metode untuk melakukan analisis media sosial berbasis graf untuk mengidentifikasi dan menilai suatu isu yang sedang banyak dibicarakan di media sosial. Penelitian ini melakukan social media listening terkait isu kebakaran hutan dari data Instagram untuk melihat lebih dalam topik pembicaraan warganet terkait isu kebakaran hutan serta mengidentifikasi isu-isu terkait lainnya yang muncul. Pada penelitian ini dilakukan graph clustering pada data Instagram dengan perangkat Gephi sehingga menghasilkan suatu graf dengan jumlah node sebanyak 36 dengan persentase 0.68% dari jumlah node awal sebanyak 5280 dan jumlah edge sebanyak 553 dengan persentase 0.92% dari jumlah edge awal sebanyak 64969. Proses labeling hasil graph clustering menghasilkan lima kelompok hashtag yaitu kategori isu lain yang muncul terkait kasus kebakaran hutan, kategori isu yang tidak berhubungan dengan kasus kebakaran hutan, kategori hashtag terkait lokasi kasus kebakaran hutan, kategori hashtag tentang slogan yang muncul pada kasus kebakaran hutan, dan kategori hashtag yang menggambarkan isu kebakaran hutan di Indonesia. Representasi graf dan hasil labelisasi kemudian divisualisasikan dalam aplikasi berbasis web untuk memudahkan identifikasi dan penilaian topik (hashtag) terkait isu kebakaran hutan di Indonesia.  AbstractSocial media listening is a method for conducting social network analysis by identifying and collecting information that can be used as the data source in certain cases. Using social media listening, we can summarize and get pattern from certain cases, for example in this study using  forest fire case in Indonesia. This research used hashtags from Instagram as the data source and conducted an analysis to understand the social interaction inside of forest fire case. The analysis aimed to obtain information summary using graph clustering on Gephi. Graph visualization was done using two-stage processess, which are modularity and filtering. This research resulted in 36 nodes with the percentage of 0.68% from 5280 initial nodes and 553 edges with the percentage of 0.92% from 64969 initial edges. The analysis process showed five clusters that represented the information summary from the graph clustering analysis result. The formed clusters were then analyzed and visualised on a web-based application to identifiy towards the node that represented another issues which appeared in the forest fire cases in Indonesia.
Analyzing Success Factors of Enterprise Resource Planning Adoption using Analytical Hierarchy Process Hawariyuni, Weni; Sentosa, Assoc. Prof. Dr. Ilham; Gadar, Assoc. Prof. Dr. Kamisan bin; Khrisnan, Dr. K Sarojini; Fatimah, Hilmi Azmi; Trisminingsih, Rina
International Journal of Innovation in Enterprise System Vol. 2 No. 1 (2018): International Journal of Innovation in Enterprise System
Publisher : School of Industrial and System Engineering, Telkom University

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

Abstract

Successful Enterprise Resorce Planning ERP system adoption in the company is one of the keys for the continuity of the company's business. On ERP adoption, there a lot of financials, time and human resources are invested on ERP adoption, so there must be an evaluation of ERP system to assess whether the ERP system adoption is successful or not. Some models have been developed by some researchers to assess the evaluation of ERP success. Each model has important factors used to assess the success of ERP. This study analyzes several factors that measure ERP success derived from several ERP success models to identify the important degree of each factor. The method used in this research is Analytical Hierarchy Process (AHP) with the assessment data obtained from 3 experts who have the competence and experience regarding ERP system. The results of this study found that the benefit of use, organizational impact, and user satisfaction are the 3 main subfactors with the highest important degree values. Keywords—Analytical Hierarchy Process, ERP success factors, ERP success model
Towards Modelling Trust in Voice at Zero Acquaintance Fatimah, Hilmi Azmi; Trisminingsih, Rina; Ooi Yee Hui, Deborah; lutfi, Syaheerah Lebai; Mohamed, Ahmad Sufril Azlan; Akhtar, Zahid
International Journal of Innovation in Enterprise System Vol. 3 No. 2 (2019): International Journal of Innovation in Enterprise System
Publisher : School of Industrial and System Engineering, Telkom University

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

Abstract

Trust is essential in many human relationships, especially where there is an element of inter-dependency. However, humans tend to make quick judgements about trusting other individuals, even those met at zero acquaintance. Past studies have shown the significance of voice in perceived trustworthiness, but research associating trustworthiness and different vocal features such as speech rate and fundamental frequency (f0) has yet to yield consistent results. Therefore, this paper proposes a method to investigate 1) the association between trustworthiness and different vocal features, 2) the vocal characteristics that Malaysian ethnic groups base their judgement of trustworthiness on and 3) building a neural network model that predicts the degree of trustworthiness in a human voice. In the method proposed, a reliable set of audio clips will be obtained and analyzed with SoundGen to determine the acoustical characteristics. Then the audio clips will be distributed to a large group of untrained respondents to rate their degree of trust in the speakers of each audio clip. The participants will be able to choose from 30 sets of audio clips which will consist of 6 audio clips each. The acoustic characteristics will be analyzed and com-pared with the ratings to determine if there are any correlations between the acoustic characteristic and the trustworthiness ratings. After that, a neural network model will be built based on the collected data. The neural network model will be able to predict the trustworthiness of a person’s voice. Keywords—prosody, trust, voice, vocal cues, zero acquaintance.
Co-Authors Akhtar, Zahid Albar, Israr Fatimah, Hilmi Azmi Firman Ardiansyah Gadar, Assoc. Prof. Dr. Kamisan bin Hendra Rahmawan Hendra Rahmawan Imas Sukaesih Sitanggang Khrisnan, Dr. K Sarojini Krisnanto, Ferdian Kurniawan, Riski Adi Lailan Syaufina lutfi, Syaheerah Lebai Mohamed, Ahmad Sufril Azlan Ooi Yee Hui, Deborah Purwanti, Endang Yuni Satyawan, Verda Emmelinda Sentosa, Assoc. Prof. Dr. Ilham Weni Hawariyuni, Weni WULANDARI