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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Agrotek UMMat Jurnal Teknologi Informasi dan Multimedia KUBIK: Jurnal Publikasi Ilmiah Matematika Rengganis Jurnal Pengabdian Masyarakat
Dara Puspita Anggraeni, Dara Puspita
Universitas 45 Mataram Jalan Imam Bonjol, Tohpati Cakranegara Utara, Mataram - NTB
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Education Mathematics Social Sciences

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Pelatihan Penulisan Karya Tulis Ilmiah untuk Memotivasi Literasi Menulis Siswa MTsN 1 Mataram Utama, Alfian Eka; Marhani; Satriyantara, Rio; Anggraeni, Dara Puspita; Dewi, Irma Risvana
Rengganis Jurnal Pengabdian Masyarakat Vol. 3 No. 2 (2023): November 2023
Publisher : Pendidikan Matematika, FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/rengganis.v3i2.367

Abstract

Tujuan dari kegiatan pengabdian kepada masyarakat ini adalah untuk memberikan pengetahuan, pemahaman serta pengalaman untuk meningkatkan motivasi peserta didik tentang penulisan karya tulis ilmiah, karena selama ini di MTsN 1 Mataram hanya sekedar melakukan pendampingan pada saat kompetensi karya tulis ilmiah saja. Karya tulis ilmiah yang merupakan salah satu literasi menulis peserta didik merupakan keterampilan yang sangat penting diera saat ini, sehingga kampuan tersebut perlu dimiliki oleh peserta didik guna menunjang pendidikan di sekolah maupun ketika nanti melanjutkan ke jenjang perguruan tinggi. Kegiatan pelatihan ini meliputi penjelasan materi tentang kaidah-kaidah penulisan karya tulis ilmiah, cara memunculkan ide kreatif kedalam sebuah tulisan serta cara mencari sumber tulisan yang baik untuk karya tulis ilmiah. Kegiatan ini diikuti oleh 45 peserta didik dari kelas VII, VIII, dan IX MTsN 1 Mataram. Metode kegiatan ini ada tiga yaitu pra pelatihan, pelaksanaan pelatihan dan evaluasi pelatihan. Hasil yang diperoleh dari kegiatan ini menunjukkan bahwa pelatihan yang diberikan cukup memotivasi dan meningkatkan keterampilan siswa untuk menulis karya ilmiah.
Twitter Sentiment Analysis in Tourism with Polynomial Naïve Bayes Classifier Rizal, Ahmad Ashril; Nugraha, Gibran Satya; Putra, Rian Asmara; Anggraeni, Dara Puspita
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 5 No 4 (2024): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i4.478

Abstract

Lombok has become a favorited tourist destination in the world. Therefore, tourism is a mainstay sector in regional development in West Nusa Tenggara. The contribution of the tourism sector shows an increasing trend. Tourist expenditures are distributed to various sectors. The tourism sector has a positive impact on the regional economy. The local government has prepared to improve the quality and quantity of tourism in Lombok. The results of local government efforts need to be analyzed so that future policies are on target. Analysis can be done on the satisfaction of tourists who travel to Lombok. It would be very difficult to get satisfaction data from all tourists through questionnaires. But on the other hand, tourist satisfaction is usually posted on their social networks. One of the social media that is widely used by tourists is Twitter. Their tweets contain not only expressions of natural beauty but also criticism, suggestions, and complaints during their visit. In addition, the tweet data on twitter is open access. This study tries to analyze the sentiment on Twitter which contains tweets of tourists who have visited Lombok. Sentiment analysis is performed using the Polynomial Naive Bayes Classifier. Sentiment results are classified into positive and negative sentiments. The results of this sentiment are expected to help related agencies or other tourism actors to improve the quality and quantity of regional tourism. The results showed that the positive sentiment on the security factor were 50.65%, the cost 75.32%, accommodation 62.33% and the cleanness factor 77.92%.
Quadratic Spline and Heligman-Pollard Methods in The Preparation of Life Tables in Gegelang Village West Lombok Fauzi, Andri Azmul; Anggraeni, Dara Puspita; Ridwan, Lalu Muhammad
KUBIK Vol 8, No 1 (2023): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v8i1.24809

Abstract

In this paper, we conduct research by compiling an abridged life table using the graduation method based on real data obtained at Gegelang Village, West Lombok. The graduation methods used in this study included quadratic spline and Heligman-Pollard. Based on the results, a special case of A was chosen as a method used to make a rough life table before graduation. After the graduation process, it was found that the Heligman-Pollard method was the most suitable. This is based on the chart produced using this method, which is monotonous in nature and does not fluctuate like other graduation methods. In addition, the life expectancy obtained at 65.72 years is close to West Lombok's life expectancy based on 2015.
Human Development Index Forecasting with Moving Average, Simple Exponential Smoothing and Naïve Method Anggraeni, Dara Puspita; Sutrasni, Ni Komang
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 8, No 2 (2023): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v8i2.20705

Abstract

The purpose of this research is to forecast the Human Development Index (HDI) using the moving average (MA) method, the simple exponential smoothing method and the naïve method. The region forecasted for its HDI is North Lombok Regency, for which it has the lowest HDI in West Nusa Tenggara, Indonesia. The data used for this research is the HDI from 2010 to 2022. The selection of these methods is due to the limited amount of data and the popularity of MA, SES, and Naïve method in the world of forecasting until this day. The results of this research is the MA method which consists of MA MA3, SMA MA5, WMA MA3, WMA MA5, EMA MA3, EMA MA5, and SES tested value α=0.1 and α=0.9 and Naïve method have a high degree of accuracy that can be seen in the Mean Absolute Percentage Error (MAPE) value which is below 10%. However, the chosen method is the best method with the smallest MAPE which is Naïve method with MAPE 1.32% where MAPE is below 10% indicating that the model used is Highly accurate and the result of North Lombok Regency HDI in 2023 is 65.7 which means that the HDI in North Lombok Regency has not changed. HDI in North Lombok Regency stay on middle level
Tomato plant production in NTB per year using Single Exponential Smoothing (SES) Method Putri, Dwi Noorma; Febrilia, Baiq Rika Ayu; Anggraeni, Dara Puspita
Jurnal Agrotek Ummat Vol 10, No 4 (2023): Jurnal Agrotek Ummat
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jau.v10i4.19244

Abstract

Tomatoes are one of the horticultural crops that many people use for consumption in everyday life. Because tThe demand for tomatoes is quite large, but sometimes the availability is too little or too much, it is necessary to study the changing trends or movements in tomato production each year. This research aims to predict tomato plant production in West Nusa Tenggara (NTB) Province, using the Single Exponential Smoothing (SES) method by observing several α values. The best α value is selected by looking at the smallest MAPE (Mean Absolute Percentation Error), MAD (Mean Absolute Deviation) and MES (Mean Square Error).Those value values  is considered to give the best model.The data was taken from BPS from year 2011 to 2022This research aims to predict tomato plant production in West Nusa Tenggara (NTB) Province using the Single Exponential Smoothing (SES) method by observing several α values. The research object taken in this research is data on the number of tomato plant production from 2011 to 2022 in West Nusa Tenggara (NTB) Province. The research object taken in this research is data on the number of tomato plant production from 2011 to 2022 in West Nusa Tenggara (NTB) Province.  Data was analyzed manually using Microsoft Excel. The best α value is selected by looking at the smallest MAPE (Mean Absolute Percentation Error), MAD (Mean Absolute Deviation) and MES (Mean Square Error) values. The research results show that the value α =0,1 is the α value with the smallest MAPE, MAD and MES values. Therefore, for tomato production data from 2011 to 2022 in NTB Province, the best forecasting model using the SES method is given by α =0,1.
Co-Authors Dewi, Irma Risvana Fauzi, Andri Azmul Febrilia, Baiq Rika Ayu Marhani Nugraha, Gibran Satya Putra, Rian Asmara Putri, Dwi Noorma Ridwan, Lalu Muhammad Rio Satriyantara Rizal, Ahmad Ashril Sutrasni, Ni Komang Utama, Alfian Eka