Garuda - Garba Rujukan Digital

Pengembangan Kompetensi Mahasiswa dalam Berwirausaha melalui Workshop Pemasaran Digital Berbasis AI Suseno, Pangki
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Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jrpi.v2i3.33814

The purpose of this community service activity is to improve understanding and enhance students' AI-based marketing skills. On March 22, 2025, the activity was conducted through lectures and practical sessions, along with an evaluation of students' understanding before and after the workshop. Topics covered in the workshop included understanding AI for digital marketing, market research and buyer persona analysis using AI, creating text and video content with AI, campaign optimization and data analysis with AI, and practical digital marketing with AI. The results of this PKM activity indicate that students understood the installation process; 57.9% of participants understood how to use the POM-QM software. Additionally, 70% of students understood AI for digital marketing. The evaluation results also revealed that the training helped students address product marketing issues effectively and efficiently.

Pengembangan Kompetensi Mahasiswa untuk Analisis Data Statistik dengan Aplikasi Rstudio Suseno, Pangki
Jurnal Pengabdian Masyarakat (ABDIRA) Vol 5, No 4 (2025): Abdira, Oktober
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/abdira.v5i4.944

Digital technology has brought significant changes to education, especially in statistics and data analysis. Now, data processing skills are essential for students across all disciplines. R Studio, a popular open-source software for statistical analysis, can assist with this process. This community service activity consists of a workshop on using R Studio for industrial engineering and computer science students. The workshop aims to enhance understanding of R Studio's basic concepts and practical data analysis skills. Implementation methods include lectures, hands-on practice, and pre- and post-training evaluations. The material covers an introduction to R and R Studio; installation; basic R syntax; data import and manipulation; descriptive statistical analysis; and visualization using ggplot. Results showed that all participants understood the installation process and that 70% could use R Studio for statistical analysis and develop solutions. The final evaluation revealed that the training helped students solve data problems quickly and accurately.

Pendampingan Kegiatan Implementasi Seni Mengajar Berbasis Peer Teaching di TK Al Munawar Tulungagung Dita Hendriani; Dwi Junianto; Ella Rolita Arifianti; Pangki Suseno; Yeni Roha Mahariani
Indonesia Bergerak : Jurnal Hasil Kegiatan Pengabdian Masyarakat Vol. 3 No. 4 (2025): Oktober: Indonesia Bergerak : Jurnal Hasil Kegiatan Pengabdian Masyarakat
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/inber.v3i4.1107

The peer teaching method is a strategic learning tool for creating a conducive learning environment, allowing students to play an active role and fostering connectivity between students. This method can be used as an alternative in classroom learning activities where students with the ability can act as tutors. This activity was carried out at AL Munawar Kindergarten in Tulungagung, with stages ranging from planning, training implementation, mentoring, and evaluation. The results of the community service activities were an increase in student abilities, learning outcomes, active and critical thinking skills, and communication skills. To achieve these results, strategic efforts are needed, starting from curriculum development, improving teacher competence, and providing learning facilities. Although it still has a number of weaknesses, including the difficulty of finding the right tutor who is confident and capable of mastering the material, the peer teaching method can be used as a reference for effective learning media in nurturing and developing students.

Training on Statistical Data Processing Using SPSS Application: Pelatihan Pengolahan Data Statistik Dengan Menggunakan Aplikasi SPSS Mahariani, Yeni Roha; Suseno, Pangki; Febriansyah, Muhammad Ikhwan
Mattawang: Jurnal Pengabdian Masyarakat Vol. 4 No. 4 (2023)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.mattawang2252

The Industry 4.0 era requires resources equipped with critical thinking, innovative abilities, and the capacity to address complex problems using the latest technology. Education emerges as a crucial factor in meeting Human Resources (HR) needs across various industrial sectors. Therefore, this community service activity focuses on students to enhance insights and competencies that support lectures and research projects. The training places emphasis on utilizing the Statistical Package for the Social Sciences (SPSS) as a statistical testing tool, enabling students to grasp accurate data processing. Activities encompass the introduction of basic statistical concepts, practice in data processing, statistical testing, and both descriptive and comparative analysis. The training offers additional experience, skills, and competencies, fostering participants' interaction with SPSS technology as a statistical analysis tool. Evaluation of the activities indicates a significant improvement in participants' ability to process statistical data using SPSS. AbstrakEra Industri 4.0 menuntut sumber daya yang memiliki kemampuan berpikir kritis, inovatif, dan mampu menyelesaikan masalah kompleks dengan memanfaatkan teknologi terkini. Pendidikan menjadi kunci penting dalam memenuhi kebutuhan Sumber Daya Manusia (SDM) di berbagai sektor industri. Oleh karena itu, kegiatan pengabdian ini difokuskan pada mahasiswa untuk meningkatkan wawasan dan kompetensi yang mendukung perkuliahan serta proyek penelitian. Pelatihan menitikberatkan pada penggunaan Statistical Package for the Social Sciences (SPSS) sebagai alat uji statistik, memungkinkan mahasiswa memahami pengolahan data secara tepat. Kegiatan ini mencakup pengenalan konsep dasar statistika, praktik pengolahan data, uji statistik, analisis deskriptif, asosiatif, dan komparatif. Pelatihan memberikan pengalaman, keterampilan, dan kompetensi tambahan, mendukung interaksi peserta dengan teknologi SPSS sebagai alat analisis statistik. Evaluasi kegiatan menunjukkan peningkatan signifikan dalam kemampuan peserta dalam mengolah data statistik dengan SPSS.

Analisis Pola Transaksi dan Perilaku Pembelian Pelanggan E-Commerce Berdasarkan Karakteristik Demografis dan Waktu Transaksi Yeni Roha Mahariani; Pangki Suseno; Dwi Junianto; Nindya N. A. Brillianio
Jurnal Manajemen Bisnis Era Digital Vol. 3 No. 1 (2026): Februari : Jurnal Manajemen Bisnis Era Digital
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jumabedi.v3i1.1279

The rapid growth of e-commerce has intensified the need to understand transaction patterns and customer purchasing behavior as a foundation for strategic decision-making. This study aims to analyze e-commerce transaction patterns and customer purchasing behavior based on demographic characteristics and transaction timing. By utilizing e-commerce transaction data, this research seeks to provide a more comprehensive understanding of customers’ purchasing tendencies and the factors influencing their behavior. This study employs Exploratory Data Analysis (EDA) as the primary method to descriptively explore data characteristics through various statistical visualizations, including histograms, bar charts, line graphs, and boxplots. The analysis conducted to identify transaction trends, the distribution of purchase values, and behavioral differences across demographic groups and specific time periods. The results indicate that e-commerce transaction patterns tend to increase during certain periods, particularly in the latter part of the observation timeframe, suggesting the influence of seasonal factors and promotional strategies. The distribution of transaction values is asymmetric, with most transactions occurring in the low to medium value range, while high-value transactions are conducted by a relatively small proportion of customers. Furthermore, variations in purchasing behavior are observed across demographic groups in terms of transaction frequency and value, despite relatively balanced transaction volumes. The findings confirm that e-commerce customer purchasing behavior is influenced by a combination of temporal factors and demographic characteristics. These results are expected to serve as a basis for e-commerce practitioners in developing more targeted marketing strategies and as a reference for future research in the field of e-commerce data analytics.

A comparative analysis of the accuracy of forecasting methods in predicting strategic food production in East Java Suseno, Pangki; Junianto, Dwi; Mahariani, Yeni Roha
Priviet Social Sciences Journal Vol. 6 No. 2 (2026): February 2026
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v6i2.1285

Food security is one of the main pillars of sustainable national development, especially in East Java, a region that contributes significantly to the national rice production. However, data from 2016 to 2024 show a downward trend in rice production. This contrasts with the relatively stable consumption demand and poses a risk to future food stability. This study aims to predict future food needs and determine the most accurate forecasting method by comparing the naive method, moving average, single exponential smoothing (SES), and double exponential smoothing (DES) methods. The research data includes annual rice production and consumption volumes in East Java over a nine-year period. We evaluated the forecasting accuracy using the mean absolute deviation (MAD), mean squared error (MSE), and mean absolute percentage error (MAPE). The results of the analysis show that the double exponential smoothing method (with α = 0.9 and β = 0.1) provides the best performance, with the lowest error rate (MAPE) of 1.020%. This value is much more accurate than those of the naive method (6.397%), moving average method (6.359%), and single exponential smoothing method (6.530%), which are less responsive to downward trends in the data. Therefore, the DES method is recommended as the most appropriate forecasting model to assist the government of East Java with strategic planning and food security policies.

A comparative analysis of the accuracy of forecasting methods in predicting strategic food production in East Java Pangki Suseno; Dwi Junianto; Yeni Roha Mahariani
Priviet Social Sciences Journal Vol. 6 No. 2 (2026): February 2026
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v6i2.1285

Food security is one of the main pillars of sustainable national development, especially in East Java, a region that contributes significantly to the national rice production. However, data from 2016 to 2024 show a downward trend in rice production. This contrasts with the relatively stable consumption demand and poses a risk to future food stability. This study aims to predict future food needs and determine the most accurate forecasting method by comparing the naive method, moving average, single exponential smoothing (SES), and double exponential smoothing (DES) methods. The research data includes annual rice production and consumption volumes in East Java over a nine-year period. We evaluated the forecasting accuracy using the mean absolute deviation (MAD), mean squared error (MSE), and mean absolute percentage error (MAPE). The results of the analysis show that the double exponential smoothing method (with α = 0.9 and β = 0.1) provides the best performance, with the lowest error rate (MAPE) of 1.020%. This value is much more accurate than those of the naive method (6.397%), moving average method (6.359%), and single exponential smoothing method (6.530%), which are less responsive to downward trends in the data. Therefore, the DES method is recommended as the most appropriate forecasting model to assist the government of East Java with strategic planning and food security policies.

Pendampingan dan Pelatihan Operasional Mill Station Smart Distributed Control Sytem di PG Prima Alam Gemilang Pangki Suseno; Dwi Junianto; Ela Rolita Arifianti; Yeni Roha Mahariani
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 2 (2026): Mei
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/90zykj35

Pabrik Gula Prima Alam Gemilang telah mengadopsi teknologi Smart Distrubuted Control Sytem berbasis Smart Mill System untuk meningkatkan stabilitas proses, keandalan peralatan, dan optimalisasi ekstraksi nira. Namun, kompleksitas sistem menimbulkan tantangan berupa belum meratanya kompetensi operator dalam memahami prosedur operasional, sistem interlock, pengaturan parameter, serta penanganan gangguan. Kegiatan pendampingan ini dilakukan sebagai upaya peningkatan kapasitas sumber daya manusia agar mampu mengoperasikan sistem secara efektif dan sesuai standar operasional prosedur. Tujuan kegiatan adalah memastikan keseragaman kemampuan operator, meningkatkan pemahaman terhadap fitur sistem, serta meminimalkan potensi gangguan proses giling. Metode yang digunakan meliputi penyusunan materi berbasis buku manual, pemaparan materi di kelas, praktik langsung di lapangan, observasi kinerja, serta pemberian umpan balik. Hasil pendampingan menunjukkan peningkatan kompetensi operator dalam menjalankan operasional mesin secara mandiri sesuai SOP. Indikator keberhasilan terlihat dari ketepatan pengaturan parameter dan kemampuan identifikasi gangguan yang kini dilakukan tanpa kesalahan prosedur, sesuai dengan standar instruction manual perusahaan. Secara keseluruhan, pendampingan ini berkontribusi terhadap peningkatan kesiapan operasional dan mendukung keberlangsungan proses produksi yang lebih stabil dan efisien. Kedepannya metode pelatihan sejenis dapat dilakukan secara internal berbasis metode peer teaching dan problem based learning.

PERBANDINGAN METODE PERAMALAN BERDASARKAN TINGKAT AKURASI UNTUK MEMPREDIKSI PRODUKSI BAWANG MERAH DI KABUPATEN NGANJUK Dwi Junianto; Pangki Suseno; Yeni Roha Mahariani
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.7738

Penelitian ini bertujuan melakukan pendugaan atau perkiraan tentang kuantitas produksi bawang merah di Kabupaten Nganjuk. Produk holtikultura tersebut bernilai ekonomis tinggi yang sejalan pada jumlah permintaan konsumen cenderung mengalami peningkatan tiap tahunnya. Kaidah pengkajian memanfaatkan data sekunder deret waktu yang diimplementasikan dengan beragam variasi metode peramalan yaitu MA, WMA, SES dan DES. Hasil peramalan yang paling adaptif akan dibandingkan pada tingkat akurasi nilai-nilai MAD, MSE dan MAPE untuk memproyeksikan dugaan estimasi di periode yang akan datang. Berdasarkan bukti empiris tersebut ditemukan bahwa penerapam metode DES pada α =0,4 terbaik karena mampu membuktikan tingkat kesalahannya terkecil. Nilai-nilai tersebut antara lain MAD = 10.938,40, MSE = 148.101.915,75 dan MAPE = 7,44%. Hal ini didukung pada metode DES mampu menyesuaikan pada pola data yang mengandung unsur tren.

CRICKET PRODUCTION FORECASTING USING THE MOVING AVERAGE METHOD Pangki Suseno; Dwi Junianto; Farid Sukmana; Bian Dwi Pamungkas
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.7066

Cricket production in Indonesia has promising business potential, particularly in rural areas. However, production variability is often a major challenge for farmers to maintain economic stability. Therefore, production forecasting methods are needed for better management. This study aims to predict cricket production using Moving Average (MA) and Weighted Moving Average (WMA) methods and compare their accuracy. The research was conducted in Rejotangan District, Tulungagung, using 12 weeks of cricket production data from May to August 2024. The accuracy of the method was measured using Mean Absolute Deviation (MAD), Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). From this research, the best model that can be used to predict the amount of cricket production is the Weighted Moving Average (WMA) model with n = 4 with the lowest prediction accuracy value (MAD, MSE and MAPE) of 16.05, 514.513 and 10.985% respectively. From the forecasting results, the total production of crickets in the existing farm for one period ahead with the WMA model n = 4 is 150.9 kg.

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