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All Journal JSM (Jurnal SIFO Mikroskil) E-Dimas: Jurnal Pengabdian kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Journal of Computer System and Informatics (JoSYC) Yayasan Cita Cendikiawan Al Khwarizmi Journal of Social Responsibility Projects by Higher Education Forum
Sio Jurnalis Pipin
Universitas Mikroskil
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Optimization of Sentiment Analysis Classification of ChatGPT on Big Data Twitter in Indonesia using BERT Sinaga, Frans Mikael; Purba, Ronsen; Pipin, Sio Jurnalis; Lestari, Wulan Sri; Winardi, Sunaryo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7861

Abstract

This research is grounded in the emergence of ChatGPT technology, supported by prior and similar studies. The urgency of the issue is highlighted by previous research indicating non-convergent classification outcomes in LSTM (Long Short-Term Memory) methods due to suboptimal hyperparameter settings and limitations in understanding text data within Big Data. The presence of ChatGPT technology brings both benefits and potential misuse, such as copyright infringement, unauthorized news extraction, and violations of accountability principles. Understanding public sentiment towards the presence of ChatGPT technology is crucial. The research aims to implement the BERT (Bidirectional Encoder Representations from Transformers) method to achieve accurate and convergent sentiment analysis classification. This study involves data preprocessing stages using Natural Language Processing (NLP) techniques. Text data, already vectorized, is classified using BERT to determine public sentiment (positive, negative, neutral) towards ChatGPT technology, ensuring greater accuracy, convergence, and contextual relevance. Performance testing of the BERT model is conducted using a Confusion Matrix. With parameters set to Max Sequence Length = 128 and Batch Size = 16, the highest classification accuracy achieved is 93.4%.
Menerapkan computational thinking dengan python pada SMA Maitreyawira Kirasan Kurniawan, Heru; Gunawan, Gunawan; Kelvin, Kelvin; Riche, Riche; Pipin, Sio Jurnalis
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 2 (2025): March
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i2.29070

Abstract

AbstrakComputational thinking adalah proses berpikir yang melibatkan penyelesaian masalah yang digambarkan ke dalam konsep dasar ilmu komputer. Kegiatan PKM ini bertujuan untuk meningkatkan kemampuan berpikir kritis dan logis serta meningkatkan kemampuan problem solving siswa dalam menyelesaikan contoh-contoh kasus selama proses pelatihan dengan cara Computational thinking. Dengan penerapan Computational Thinking, siswa dapat memahami konsep dasar kerja komputer dan menyelesaikan permasalahan berdasarkan data yang ada. SMA Swasta Maitreyawira Kisaran adalah sekolah menengah atas swasta yang berlokasi di Jalan Pramuka No.19 Kisaran, Kabupaten Asahan, Sumatera Utara. Kegiatan ini dilaksanakan dengan metode pelatihan terhadap 18 orang siswa dan 2 orang guru dalam menguasai keterampilan baru tentang berpikir secara komputasional serta pengetahuan baru tentang penerapan pemrograman dalam menyelesaikan permasalahan sederhana selama 2 hari pelatihan. Hasil pelatihan ini diukur menggunakan desain pretest-posttest yang dilakukan pada awal pelatihan dan juga diakhir pelatihan untuk melihat sejauh mana peningkatan kemampuan siswa dalam menyelesaikan masalah sederhana. Perbandingan antara hasil pra-test dan post-test menunjukkan adanya peningkatan pada pemahaman peserta didik terhadap cara berpikir komputasional (Computational Thinking) yakni dari yang sebelumnya hanya rata-rata 42% menjadi  76%. Adapun indikator yang perlu ditingkatkan seperti pehamaman terhadap konsep abstraksi dan penyelesaian masalah dalam bentuk koding python, hal ini terlihat selama proses pelatihan dimana sejumlah siswa terlihat masih bingung dalam membuat abstraksi dari masalah yang ada dan juga bagaimana menuangkannya kedalam kode program sehingga perlu dilakukan upaya lebih lanjut untuk mencapai pemahaman yang lebih komprehensif. Kata kunci: pelatihan; pemikiran; komputasional; python. AbstractComputational thinking is a thought process that involves problem-solving described within the basic concepts of computer science. This PKM activity aims to enhance students' critical and logical thinking skills, as well as improve their problem-solving abilities in addressing case examples during the training process through computational thinking. By applying Computational Thinking, students can understand the fundamental concepts of how computers work and solve problems based on available data. SMA Swasta Maitreyawira Kisaran is a private high school located at Jalan Pramuka No.19 Kisaran, Asahan Regency, North Sumatra. This activity was conducted using a training method involving 18 students and 2 teachers to master new skills in computational thinking and acquire new knowledge on the application of programming in solving simple problems over a 2-day training period. The outcomes of this training were measured using a pretest-posttest design, conducted at the beginning and end of the training, to determine the extent of the improvement in students' abilities to solve simple problems. The comparison between the pre-test and post-test results showed an improvement in the participants' understanding of computational thinking, which increased from an average of only 42% to 76%. However, certain indicators still need improvement, such as understanding the concept of abstraction and solving problems in the form of Python coding. This was evident during the training process, where some students still appeared confused about creating abstractions of existing problems and how to translate them into program code. Therefore, further efforts are needed to achieve a more comprehensive understanding. Keywords: training; thinking; computational; python.
Pengembangan Aplikasi Presensi Online Berbasis Mobile dengan Penerapan Geolocator dan Face Recognition pada CV. Global Mandiri Prasetia, Muhammad Danu; Gultom, Ahmad Taufiq; Leticia, Leticia; Damanik, Florida N.S.; Pipin, Sio Jurnalis
Jurnal Sifo Mikroskil Vol. 25 No. 1 (2024): JSM VOLUME 25 NOMOR 1 TAHUN 2024
Publisher : Fakultas Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55601/jsm.v25i1.1223

Abstract

Di era digital saat ini, keefektifan sistem presensi online berbasis mobile menjadi krusial bagi perusahaan dalam meningkatkan efisiensi dan akurasi pengelolaan kehadiran karyawan. CV. Global Mandiri, sebuah perusahaan penyedia barang dan jasa di Medan, menghadapi tantangan dalam sistem presensi konvensionalnya yang rentan terhadap kecurangan dan inefisiensi. Untuk mengatasi masalah ini, penelitian ini bertujuan untuk mengembangkan aplikasi presensi online yang mengintegrasikan teknologi geolocator dan Face Recognition, pada platform berbasis mobile. Penelitian ini menggunakan pendekatan System Development Life Cycle (SDLC) dengan metode Waterfall, meliputi tahapan pengumpulan data, analisis proses, analisis kebutuhan, perancangan, dan implementasi. Analisis proses dilakukan melalui wawancara terstruktur dengan pemilik perusahaan, bagian kepegawaian, dan karyawan, serta menggunakan activity diagram dan fish bone untuk mengidentifikasi masalah dalam sistem presensi yang ada. Hasil pengembangan aplikasi menunjukkan bahwa aplikasi presensi online dengan integrasi geolocator dan pengenalan wajah berhasil meningkatkan efisiensi pencatatan kehadiran karyawan dan mengurangi potensi kecurangan. Aplikasi ini memungkinkan karyawan untuk melakukan presensi di lokasi kerja dengan validasi lokasi dan identitas secara akurat, serta menghasilkan laporan kehadiran secara otomatis. Implementasi teknologi ini di CV. Global Mandiri berkontribusi pada peningkatan akurasi dan keandalan data kehadiran karyawan, yang merupakan langkah penting dalam menjaga integritas sistem presensi perusahaan.
Pelatihan Pengembangan Aplikasi Mobile Menggunakan Flutter pada SMAS Wiyata Dharma Halim, Apriyanto; Pipin, Sio Jurnalis; Tanti, Tanti
Journal of Social Responsibility Projects by Higher Education Forum Vol 4 No 3 (2024): Maret 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jrespro.v4i3.4551

Abstract

SMAS Wiyata Dharma is a school in the city of Medan and has been established since November 14 1985. This school is located on Jalan Wahidin No. 31 Medan, North Sumatra Province. This school has currently received an A accreditation rating. This school generally not only provides educational curriculum lessons but also provides learning related to computer science which can help students prepare themselves for the outside world. One of the lessons in computer science, namely mobile apps and the most widely used programming language is the Flutter programming language developed by Google. Through collaboration with Mikroskil University, SMAS Wiyata Dharma students are equipped with the ability to create mobile applications using Flutter in collaboration. This training activity lasted for 2 days and was carried out in the Mikroskil University computer laboratory. During this training activity, students were given pre-test questions, material and case studies, as well as post-tests and feedback at the end of the training. From the results of the pre-test and post-test, it can be seen that there is an increase in students' understanding of the results of the service carried out and from the feedback that has been shared with students, it can be seen that all students agree that the training carried out is in line with the students' expectations.
Pelatihan Pembuatan Konten Pembelajaran Berbasis Video pada SMA Methodist 6 Sinaga, Frans Mikael; Irviantina, Syanti; Pipin, Sio Jurnalis
Journal of Social Responsibility Projects by Higher Education Forum Vol 4 No 3 (2024): Maret 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jrespro.v4i3.4588

Abstract

The use of information technology to support the teaching and learning process is considered important and necessary. It is not only the educators or teachers who are demanded to have the ability to use and utilize information technology, but students as well, in order to meet digital literacy competencies and be able to compete globally. At Swasta Methodist 6 High School, community service activities are carried out with the aim of improving students understanding in creating learning content using Canva and Wondershare Filmora tools. The availability of good facilities and infrastructure at school greatly assists students in utilizing technology to support the learning process. This activity was carried out for 2 days in the school's laboratory, and was attended by 43 students. The evaluation conducted with a pre-test and post-test showed an increase of 80% in the post-test for questions related to the use of Canva tools, and an increase of 60% in the post-test for questions related to the use of Wondershare Filmora tools.
Optimalisasi Keterampilan Multimedia Video Pembelajaran melalui Pelatihan Teknik Editing dan Pengambilan Gambar di SMA Sutomo 1 Medan Pipin, Sio Jurnalis; Enjelin, Enjelin; Limbong, Ricky Paian
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 15, No 4 (2024): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v15i4.18687

Abstract

Pentingnya literasi multimedia dalam editing dan pengambilan video kini menjadi salah satu kebutuhan utama, terutama dalam konteks pendidikan modern. SMA Sutomo 1 Medan menghadapi tantangan dalam mengintegrasikan keterampilan ini ke dalam proses pembelajaran di kelas dan media promosi, mengingat keterbatasan akses terhadap pelatihan dan peralatan yang memadai. Kegiatan pengabdian kepada masyarakat (PkM) ini bertujuan meningkatkan kemampuan siswa dalam editing video dan pengambilan gambar menggunakan teknologi terkini. Melalui metode pelatihan yang menggabungkan teori dan praktik, siswa diajarkan menggunakan perangkat lunak Adobe Premiere untuk editing dan pengambilan gambar melalui smartphone. Hasilnya, 25 siswa yang mengikuti pelatihan menunjukkan peningkatan yang signifikan dalam pemahaman dan keterampilannya, dengan sebagian besar mencapai tingkat penguasaan yang diharapkan. Sebelum pelatihan, hasil pre-test menunjukkan bahwa rata-rata hanya 58% siswa yang memiliki pemahaman dasar tentang editing video dan pengambilan gambar. Setelah mengikuti serangkaian pelatihan yang mencakup penggunaan Adobe Premiere untuk editing dan pengambilan gambar, hasil post-test menunjukkan peningkatan yang signifikan. Skor rata-rata siswa meningkat menjadi 80 dari skala 100, dengan rata-rata 90% siswa menunjukkan pemahaman yang baik tentang konsep dan praktik editing video serta pengambilan gambar. Ini menunjukkan peningkatan pemahaman sebesar 50% dari baseline awal dan peningkatan skor rata-rata sebesar 30 poin.
Analyzing Sentiment with Self-Organizing Map and Long Short-Term Memory Algorithms Frans Mikael Sinaga; Sio Jurnalis Pipin; Sunaryo Winardi; Karina Mannita Tarigan; Ananda Putra Brahmana
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.3332

Abstract

This research delves into the impact of Chat Generative Pre-trained Transformer, one of Open Artificial Intelligence Generative Pretrained Transformer models. This model underwent extensive training on a vast corpus of internet text to gain insights into the mechanics of human language and its role in forming phrases, sentences, and paragraphs. The urgency of this inquiry arises from Chat Generative Pre-trained Transformer emergence, which has stirred significant debate and captured widespread attention in both research and educational circles. Since its debut in November 2022, Chat Generative Pre-trained Transformer has demonstrated substantial potential across numerous domains. However, concerns voiced on Twitter have centered on potential negative consequences, such as increasedforgery and misinformation. Consequently, understanding public sentiment toward Chat Generative Pre-trained Transformer technology through sentiment analysis has become crucial. The research’s primary objective is to conduct Sentiment Analysis Classification of Chat Generative Pre-trained Transformer regarding public opinions on Twitter in Indonesia. This goal involves quantifying and categorizing public sentiment from Twitter’s vast data pool into three clusters: positive, negative, or neutral. In the data clustering stage, the Self-Organizing Map technique is used. After the text data has been weighted and clustered, the next step involves using the classification technique with LongShort-Term Memory to determine the public sentiment outcomes resulting from the presence of Chat Generative Pre-trained Transformer technology. Rigorous testing has demonstrated the robust performance of the model, with optimal parameters: relu activation function, som size of 5, num epoch som and num epoch lstm both at 128, yielding an impressive 95.07% accuracy rate.
Implementasi smart learning menggunakan ChatGPT pada SMAS Bodhicitta Medan Irpan Adiputra Pardosi; Hardy Hardy; Sio Jurnalis Pipin; Tanti Tanti; William William
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 2 (2024): June
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i2.22549

Abstract

AbstrakKegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk memberikan pelatihan kepada 27 guru dan 18 siswa di SMAS Bodhicitta Medan tentang implementasi Smart Learning menggunakan ChatGPT, dengan fokus pada personalisasi pengalaman belajar dan integrasi teknologi berbasis artificial intelligence (AI) pada pembelajaran. Metode pelaksanaan meliputi identifikasi kebutuhan, perencanaan dan desain pelatihan, pelaksanaan pelatihan, serta monitoring dan evaluasi melalui pre-test dan post-test. Hasil pra-test menunjukkan bahwa sebelum pelatihan, pemahaman siswa dan guru tentang smart learning dan penggunaan ChatGPT masih terbatas. Namun, hasil post-test menunjukkan peningkatan signifikan dalam pemahaman dan penerimaan terhadap integrasi ChatGPT dalam pembelajaran. Survei penerimaan mengindikasikan bahwa 82% siswa dan 78% guru merasa penggunaan ChatGPT efektif dan memenuhi kebutuhan pembelajaran. Meskipun beberapa responden menyatakan kurang efektif dalam penggunaan teknologi AI dalam pembalajaran, namun tingkat penerimaan yang tinggi menunjukkan respons positif terhadap penggunaan teknologi AI dalam kelas, menandakan pentingnya adaptasi metode pembelajaran yang inovatif. Kegiatan ini berhasil meningkatkan kualitas pembelajaran dan mendorong integrasi teknologi canggih dalam pendidikan. Kata kunci: ChatGPT; smart learning;  artificial intelligence, pelatihan. Abstract This community service activity aims to provide training to 27 teachers and 18 students at SMAS Bodhicitta Medan on the implementation of Smart Learning using ChatGPT, with a focus on personalising the learning experience and integrating artificial intelligence (AI)-based technology in learning. The implementation method includes needs identification, training planning and design, training implementation, and monitoring and evaluation through pre-test and post-test. The pre-test results showed that before the training, students' and teachers' understanding of smart learning and the use of ChatGPT was still limited. However, the post-test results showed a significant increase in understanding and acceptance of ChatGPT integration in learning. The acceptance survey indicated that 82% of students and 78% of teachers felt the use of ChatGPT was effective and fulfilled the learning needs. Although some respondents expressed a lack of effectiveness in the use of AI technology in teaching, the high level of acceptance indicates a positive response to the use of AI technology in the classroom, signalling the importance of adapting innovative learning methods. This activity successfully improved the quality of learning and encouraged the integration of advanced technology in education. Keywords: chatgpt; smart learning;  artificial intelligence; training.
Co-Authors Ananda Putra Brahmana Apriyanto Halim Carles Juliandy Christofer Jaya Zebua Damanik, Florida N.S. David David Enjelin, Enjelin Fadia C. Damanik Felix Felix Florida N.S. Damanik Gultom, Ahmad Taufiq Gunawan Gunawan Hardy Hardy Heru Kurniawan Heru Kurniawan Irpan Pardosi Jeslim, Jeslim Jordan, Alvito Karina Mannita Tarigan Kelvin Kelvin Leticia, Leticia Manurung, Stieven B.L. Muhammad Noor Hakim Octa Vi Yanti Siahaan Prasetia, Muhammad Danu Riche Riche Ricky Paian Limbong Ronsen Purba Ronsen Purba Sinaga, Frans Mikael Sunaryo Winardi Syanti Irviantina Tanti Tanti Tanti Thiyara Al-Mawaddah William William Winardi, Sunaryo Wulan Sri Lestari