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All Journal Natural Science: Journal of Science and Technology Jurnal Pendidikan Jasmani, Olahraga dan Kesehatan Jurnal Pendidikan Bahasa Jepang Undiksha KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063 Electronic Journal of Graph Theory and Applications (EJGTA) Tadris: Jurnal keguruan dan Ilmu Tarbiyah Journal of the Indonesian Mathematical Society JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vygotsky: Jurnal Pendidikan Matematika dan Matematika InPrime: Indonesian Journal Of Pure And Applied Mathematics Parameter: Journal of Statistics Fraktal: Jurnal Matematika dan Pendidikan Matematika Arus Jurnal Sosial dan Humaniora Almufi Jurnal Pengabdian kepada Masyarakat Sulawesi Tenggara Educational Journal Journal Of Human And Education (JAHE) Journal of Advanced Sciences and Mathematics Education Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka
I Wayan Sudarsana
Universitas Tadulako
Religion Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Physics Social Sciences Other

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Forecasting Of Crude Palm Oil By Using Fuzzy Time Series Method (Study Case : PT. Buana Mudantara Plantation) Rasna; Sudarsana, I Wayan; Lusiyanti, Desy
Parameter: Journal of Statistics Vol. 1 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (765.159 KB) | DOI: 10.22487/27765660.2021.v1.i1.15442

Abstract

PT. Buana Mudantara is a company engaged in palm oil production. The production of oil palm at this company varies every period, so the problem that often occurs is insufficient supply and demand. Therefore, it is necessary to forecast future oil palm production. The method used in this research is the Fuzzy Time Series method which has advantages, among others, that the calculation process does not require a complicated system, so it is easier to develop and can solve the problem of forecasting historical data in the form of linguistic values. This method provides a level of accuracy calculated using the MAPE (Mean Absolute Percentage Error) of . The results show that the forecasting of the amount of oil palm production in November 2019 - March 2020 is respectively ton, ton, ton, tons and tons
Implementation of Etlingera Elatior for Unique Branding of Central Sulawesi Batik Motif Ikram; Abdi; Mutmainna, Nurul; Khasmawati, Julia; Wahyuli, Diana; Sudarsana, I Wayan; Junaidi
Parameter: Journal of Statistics Vol. 2 No. 3 (2022)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2022.v2.i3.16240

Abstract

Batik is the art work of the Indonesian people which is a cultural heritage from their ancestors which has become one of the world's recognized cultural heritages. Batik itself has a variety of patterns that are influenced by the customs of the local community and contains deep meaning and philosophy. Endemic flora and fauna are often used as patterns for batik motifs. In the process of forming batik motifs, mathematical knowledge is often required which sometimes appears naturally. Mathematics that is closely related to culture is called ethnomathematics as a branch of mathematics. Ethnomathematics can be used in forming batik patterns, especially fractal forms. A fractal shape is an object that appears to have a symmetric self-resemblance to one another when viewed at a certain scale and is the smallest part of the overall structure of the object. The purpose of this research is to make fractals of local batik motifs from Central Sulawesi using the endemic plant of Bunga Katimong (Etlingera Elatior) with the help of the j-Batik application so that new motifs are obtained to add to the diversity of existing batik motifs. The new batik motifs produced in this research are Katimong, Kantan, Kincung and Honje.
Pengaruh Motivasi Kerja, Kompensasi dan Kepuasan Kerja terhadap Kinerja Karyawan Pada Pt. Geo Gea Mineralindo Sudarsana, I Wayan; Marsalena, Nindi Ade
Arus Jurnal Sosial dan Humaniora Vol 5 No 2: Agustus (2025)
Publisher : Arden Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57250/ajsh.v5i2.1614

Abstract

Penelitian ini bertujuan untuk menguji dan menganalisis pengaruh motivasi kerja, kompensasi, dan kepuasan kerja terhadap kinerja karyawan di PT. Geo Gea Mineralindo. Penelitian ini menggunakan pendekatan kuantitatif. Populasi dalam penelitian ini adalah 35 karyawan PT. Geo Gea Mineralindo. Analisis yang digunakan adalah analisis regresi linier berganda dengan menggunakan SPSS 27. Hasil penelitian menunjukkan bahwa (1) motivasi kerja, kompensasi, dan kepuasan kerja berpengaruh positif dan signifikan terhadap kinerja karyawan, (2) motivasi kerja berpengaruh positif dan signifikan terhadap kinerja karyawan, (3) kompensasi berpengaruh positif tetapi tidak signifikan terhadap kinerja karyawan, dan (4) kepuasan kerja berpengaruh positif dan signifikan terhadap kinerja karyawan.
A Study on Sentiment Analysis of Public Response to The New Fuel Price Policy In 2022: A Support Vector Machine Approach Putri, Niluh Putu Aprillia Puspitadewi Sudarsana; Angreni, Dwi Shinta; Sudarsana, I Wayan
InPrime: Indonesian Journal of Pure and Applied Mathematics Vol. 7 No. 1 (2025)
Publisher : Department of Mathematics, Faculty of Sciences and Technology, UIN Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/2twt5d12

Abstract

The Indonesian government's decision to raise fuel prices in 2022, following a global surge in crude oil prices, triggered widespread public debate. Understanding public sentiment toward such policy decisions is essential for determining the appropriate timing of implementation while minimizing negative reactions. This study aims to classify public sentiment regarding the fuel price hike using the Support Vector Machine (SVM) algorithm. Data were collected from Twitter through web scraping using the SNScrape library in Python. A total of 3,000 tweets were gathered and underwent preprocessing steps such as case folding, tokenization, stopword removal, and stemming. The classification model was built in Google Colab using the SVM algorithm to categorize tweets as positive (+) or negative (–). Model performance was evaluated using a confusion matrix, achieving an accuracy of 81.0%. The results showed that 63.6% of public responses were negative, while 36.4% were positive. Additionally, it was observed that the accuracy converged to 81.1% as the number of training iterations increased. The findings were presented through word clouds and pie charts to enhance interpretability, and a simple graphical user interface (GUI) was developed for user interaction. The study indicates that the government’s repeated delays in implementing the price adjustment may have reflected sensitivity to public sentiment. This research demonstrates the potential of sentiment classification as a tool for evidence-based policymaking, offering insights into the social dynamics surrounding policy changes. Future research could expand by incorporating multi-class sentiment categories or real-time data for dynamic policy evaluation. Keywords: Fuel price; Public opinion; Sentiment analysis; Social media; SVM.   Abstrak Keputusan pemerintah Indonesia untuk menaikkan harga bahan bakar minyak pada tahun 2022 dan disusul oleh lonjakan harga minyak mentah global, memicu perdebatan publik yang meluas. Memahami sentimen publik terhadap keputusan kebijakan tersebut sangat penting untuk menentukan waktu implementasi yang tepat untuk meminimalkan reaksi negatif. Penelitian ini bertujuan untuk mengklasifikasikan sentimen publik terhadap kenaikan harga bahan bakar minyak menggunakan algoritma Support Vector Machine (SVM). Data dikumpulkan dari Twitter melalui web scraping menggunakan pustaka SNScrape dalam bahasa Python. Sebanyak 3.000 tweet dikumpulkan dan dilakukan tahap praproses seperti case folding, tokenization, stopword removal, dan stemming. Model klasifikasi dibangun di Google Colab menggunakan algoritma SVM untuk mengkategorikan tweet sebagai positif (+) atau negatif (–). Kinerja model dievaluasi menggunakan matriks confusion dan mencapai akurasi 81,0%. Hasil penelitian menunjukkan bahwa 63,6% tanggapan publik bersifat negatif, sedangkan 36,4% bersifat positif. Selain itu, akurasi konvergen menjadi 81,1% seiring dengan peningkatan jumlah iterasi pelatihan. Temuan tersebut disajikan melalui word cloud dan diagram pai untuk meningkatkan interpretabilitas, dan graphical user interface (GUI) sederhana dikembangkan untuk interaksi pengguna. Studi ini menunjukkan bahwa penundaan berulang pemerintah dalam menerapkan penyesuaian harga mungkin mencerminkan kepekaan terhadap sentimen publik. Penelitian ini menunjukkan potensi klasifikasi sentimen sebagai alat untuk pembuatan kebijakan berbasis bukti, yang menawarkan wawasan tentang dinamika sosial seputar perubahan kebijakan. Penelitian di masa mendatang dapat diperluas dengan menggabungkan kategori sentimen multikelas atau data waktu nyata untuk evaluasi kebijakan yang dinamis. Kata Kunci: Bahan bakar; Opini public; Analisis sentiment; Mesia social; SVM. 2020MSC: 62H30, 91D30.
PEMBERDAYAAN SISWA SMA MELALUI PENGOLAHAN POPCORN KELOR DAN STIK KELOR DENGAN DIGITAL BRANDING UNTUK MENINGKATKAN KEWIRAUSAHAAN DAN PEMASARAN PRODUK LOKAL Handris, Handris; Naim, Ifin; Mariani, Mariani; Lajaria, Ridha Taurisma; Suprianto, Ghalib; Patulak, Lucia Evianti; Sudarsana, I Wayan
Jurnal Pengabdian Masyarakat Sabangka Vol 4 No 06 (2025): Jurnal Pengabdian Masyarakat Sabangka
Publisher : Pusat Studi Ekonomi, Publikasi Ilmiah dan Pengembangan SDM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62668/sabangka.v4i06.1884

Abstract

This activity aims to provide an understanding of business development based on marketing strategies. Marketing strategy is a crucial aspect for Moringa Popcorn and Moringa Stick producers to achieve business goals, especially in the face of competition. Business development requires the implementation of a marketing mix encompassing Product, Price, Promotion, and Place/Distribution. These four elements play a role in directing marketing activities to be more effective and increase product competitiveness. This community service activity was conducted at SMAN 20 South Konawe, Southeast Sulawesi Province, over two months through outreach and workshops. Participants included 25 teachers and students, supported by 7 university students and 10 lecturers from the Faculty of Economics and Business. The methods used included participatory learning, mentoring, and hands-on practice. Evaluation results showed a positive response from participants. They considered the marketing strategy material, covering product, price, distribution, and promotion, very useful and able to increase motivation in developing the business and supporting family economic growth.
Tracing how students make sense of convergent sequences through their preferred mathematical representations: A phenomenological exploration Nursupiamin; Rochaminah, Sutji; Pathuddin; Sukayasa; Sudarsana, I Wayan
Journal of Advanced Sciences and Mathematics Education Vol. 5 No. 2 (2025): Journal of Advanced Sciences and Mathematics Education
Publisher : CV. FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/jasme.v5i2.886

Abstract

Background: Many students struggle to understand convergent sequences when they depend on only one form of mathematical representation, which limits how they interpret the idea of a sequence approaching its limit. Aim: This study explores how students who naturally rely on symbolic, visual, or verbal representations experience the process of solving convergent sequence problems. The goal is to understand how they construct meaning, the strategies they choose, and the points at which they feel uncertain when shifting between different modes of representation. Method: A descriptive phenomenological approach was used with seven participants selected through AHP–TOPSIS classification of Dominant Mathematical Representations. Data were gathered from written work, observations, and individual interviews, then analyzed using Colaizzi’s stages. Themes were refined through triangulation to ensure consistency and credibility. Results: Symbolic-oriented students tended to rely on procedural steps and showed little inclination to move beyond formulas. Students who preferred visual thinking used sketches to build intuition but hesitated when expressing their ideas in symbolic form. Those with a verbal orientation explained their reasoning narratively yet were less confident when formal notation was required. Across all participants, shifts between representations occurred rarely, and emotional responses—such as hesitation or relief—often accompanied these moments. Conclusion: The findings indicate that students’ understanding of convergence is shaped strongly by the representational mode they depend on. This limited flexibility suggests the need for instructional approaches that actively support transitions between symbolic, visual, and verbal representations so students can develop a more connected and meaningful understanding of convergent sequences
Representational Transition Patterns of Pre-service Teachers in Solving Convergent Sequence Problems Nursupiamin; Rochaminah, Sutji; Sudarsana, I Wayan
Tadris: Jurnal Keguruan dan Ilmu Tarbiyah Vol 10 No 2 (2025): Tadris: Jurnal Keguruan dan Ilmu Tarbiyah
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/tadris.v10i1.28603

Abstract

This study investigates the representational transition patterns of pre-service teachers in solving convergent-sequence problems, with a focus on how they utilize symbolic, visual, and verbal representations. Using a qualitative phenomenological design, seven pre-service mathematics teachers were purposively selected based on their dominant representation modes (symbolic, visual, verbal). Participants solved a convergent-sequence task, and their problem-solving processes were analyzed using a modified Colaizzi method, with triangulation ensuring the validity of the findings. Three key patterns emerged: a stagnant reliance on a single representation mode (symbolic or verbal), a linear transition from visual to symbolic forms, and a complementary use of symbolic and verbal representations. No cyclic or complex transition patterns were identified, indicating limited representational fluency. The findings highlight the dominance of symbolic representations among pre-service teachers, with some exhibiting limited representational flexibility. The study suggests that fostering representational fluency, where students can effectively transition between different forms, is crucial for deeper conceptual understanding, especially in abstract topics like convergent sequences. Pedagogically, the study underscores the importance of instructional strategies that encourage the integration and transition across symbolic, visual, and verbal representations. This research contributes to the understanding of representational transition patterns in real analysis, an area often underexplored in mathematics education, and offers insights for improving teacher preparation programs.
Co-Authors Abdi Abdul Mahatir Najar Agusman Sahari Al Fajri, Iman Andi Hendra Anita Ahmad Kasim Ayu Lestari D Farhamsa, D Desy Lusiyanti Dwi Shinta Angreni Erwanda, Muhammad Tegar Faisal Susanto Farih, Muhamad Fitria Fitria Habibi Habibi Handris, Handris Hayyan Ahmad Ulul Albab Hervisari, Hervisari Huzaimah Huzaimah I Gede Mahendra Darmawiguna I Made Gede Sunarya Ikram Indalestari, Wa Ode Dien Ismail, M S Ismiyanti, Ismiyanti Jaenuddin, Arsyad Junaidi Junaidi Kadek Eva Krishna Adnyani Khasmawati, Julia Kristiana Wijaya Mariani Mariani Marsalena, Nindi Ade Marsalena, Nindy Ade Merdekawati, Dian Ayu Muhammad Rivai Mutmainna, Nurul Naim, Ifin Ni Nengah Suartini, Ni Nengah Noviana Noviana Nur Aisyah Nurainun Nurainun Nurhayati, Listi Nursupiamin Nursupiamin, Nursupiamin Nurul Arifin Pathuddin Patulak, Lucia Evianti Putri, Niluh Putu Aprillia Puspitadewi Sudarsana Raiza, Raiza Rajuddin, Wa Ode Nursaadha Rasna Resnawati Ridha Taurisma Lajaria Rina Ratianingsih Rita, Wa Rita, Wa Ade Rizki Amalia S Fatimah, S S Slamin Selvy Musdalifah Suhartien, Inten Sukayasa Sulistiawati Mendi Sultan Andhika Suprianto, Ghalib Sutji Rochaminah Talaba, Djeliyana Titop, Herman Wahyuli, Diana Wahyuningsi, Sri Wati, Kristin Lita Yesi, Indah