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All Journal JURNAL SISTEM INFORMASI BISNIS JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA Jurnas Nasional Teknologi dan Sistem Informasi KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Panrita Abdi - Jurnal Pengabdian pada Masyarakat RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Komputer Terapan JURNAL ILMIAH INFORMATIKA Computer Based Information System Journal JSiI (Jurnal Sistem Informasi) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Riset Informatika METIK JURNAL Jusikom: Jurnal Sistem Informasi Ilmu Komputer Zonasi: Jurnal Sistem Informasi Jurnal Informasi dan Teknologi JURSIMA (Jurnal Sistem Informasi dan Manajemen) Jurnal Tekinkom (Teknik Informasi dan Komputer) Ihsan: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Multidisiplin Indonesian Journal of Social Work Altruis: Journal of Community Services Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Tika Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Ilmiah Rehabilitasi Sosial (Rehsos) Jurnal Ilmiah Kebijakan dan Pelayanan Pekerjaan Sosial (Biyan) Jurnal Puan Indonesia Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Buana Pengabdian Golden Ratio of Data in Summary STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal Ilmiah Teknik Informatika dan Komunikasi Medani : Jurnal Pengabdian Masyarakat Jurnal Pengabdian Ibnu Sina JURSIMA Jurnal Pengabdian Barelang VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Tiyasadarma: Jurnal Pengabdian Kepada Masyarakat Journal in Teaching and Education Area Journal of Informatics and Information Security CSRID Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Jurnal SINTA: Sistem Informasi dan Teknologi Komputasi Computer & Science Industrial Engineering Journal Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK) Jurnal Ilmu Sosial dan Humaniora JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
tukino, tukino
Universitas Putera Batam
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Model Pembelajaran Inklusif Berbasis Pemberdayaan Sosial Bagi Komunitas Tuli: Studi Kasus Program Perintis PT. Kilang Pertamina International RU VI Balongan Hekmatyar, Versanudin; Mildawati, Milly; Subarkah, Ade; Kuswanda, Dede; Tukino; Wibisono, Eko Gunawan; Arsyad, Fachry; Zulkifli, Mohamad; Purnomo, Andromedo Cahyo; P, Shafira Putri Kusuma
Journal in Teaching and Education Area Vol. 2 No. 3 (2025): JITERA - Journal in Teaching and Education Area
Publisher : Yayasan Al Hidayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69673/fea1cj78

Abstract

Penelitian ini bertujuan untuk mengkaji model pembelajaran inklusif berbasis pemberdayaan sosial bagi komunitas Tuli melalui studi kasus Program PERINTIS (Pemberdayaan Inklusi Teman Istimewa) PT. Kilang Pertamina International RU VI Balongan. Program ini memadukan pelatihan barista, pendampingan humanistik, dan interaksi sosial di kedai kopi inklusif sebagai ruang belajar bersama antara masyarakat dan penyandang disabilitas rungu-wicara. Pendekatan penelitian menggunakan metode kualitatif dengan desain studi kasus. Data dikumpulkan melalui wawancara mendalam, observasi partisipatif, dan analisis dokumen, lalu dianalisis menggunakan teknik thematic analysis. Hasil penelitian menunjukkan bahwa pembelajaran melalui pengalaman nyata (learning by doing), mentoring humanistik, dan ruang sosial inklusif mampu meningkatkan kepercayaan diri, kesadaran diri, dan kemampuan sosial peserta. Ketiganya membentuk Model Pembelajaran Inklusif Berbasis Pemberdayaan Sosial, yang tidak hanya menumbuhkan keterampilan kerja, tetapi juga menciptakan transformasi psikososial dan pengakuan sosial bagi komunitas Tuli. Penelitian ini menegaskan bahwa pendidikan inklusif merupakan proses sosial yang transformatif, yang dapat tumbuh melalui kolaborasi antara dunia pendidikan, komunitas, dan sektor industri.
Seleksi Penerimaan Beasiswa Dengan Metode K-Means Clustering Menggunakan Orange Silvana Nazuah; Shofa Shofia Hilabi; Agustia Hananto; Baenil Huda; Tukino
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 8 No. 1 (2023): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v8i1.212

Abstract

Beasiswa adalah insentif keuangan yang ditawarkan oleh pemerintah, industri swasta, kedutaan ataupun Lembaga pendidikan. Proses penyeleksian penerimaan beasiswa secara tidak terintegrasi sistem butuh waktu yang lama, tidak efektif dan butuh ketelitian yang tinggi. Oleh karena itu diperlukan suatu metode untuk membantu pihak sekolah dan staf TU dalam menentukan siswa yang layak menerima beasiswa pada tahun berikutnya. Penelitian ini menggunakan metode K-Means clustering dengan tools orange data mining dan mengelompokkannya menjadi 3 cluster. Data yang digunakan adalah data sampel sebanyak 120 data yang telah direkap dari setiap program keahlian. Hasil yang diperoleh penelitian ini adalah setiap cluster akan memiliki anggota masing-masing yaitu cluster 1 dengan presentase 48% memiliki 58 anggota, cluster 2 dengan presentase 33% memiliki 39 anggota dan cluster 3 dengan presentase 19% memiliki 23 anggota. Penelitian ini bertujuan untuk mengetahui jumlah siswa yang termasuk berhak menerima beasiswa, tidak berhak menerima, dan dipertimbangkan.
Classification of Reject Patterns Based on Production Stages Using the K-Means Clustering Method Lestari, Renita; Novalia, Elfina; Tukino; Nurapriani, Fitria
Golden Ratio of Data in Summary Vol. 5 No. 4 (2025): August - October
Publisher : Manunggal Halim Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52970/grdis.v5i4.1301

Abstract

This study aims to classify reject patterns in the production process using the K-Means Clustering method. The dataset consists of 870 records collected from the production line, containing information such as product name, reject type, process stage, and production quantity. Through a data mining approach, data preprocessing steps such as cleaning, encoding, and normalization were performed prior to the clustering process. The Elbow Method indicated that the optimal number of clusters is three. Each cluster exhibits distinct characteristics: light rejects with small quantities in early stages, heavy rejects with large quantities, and moderate rejects with random distribution. These findings are expected to assist management in formulating more targeted strategies for process improvement and quality control. By identifying common reject patterns within each cluster, companies can adopt a more proactive approach to minimizing production defects and enhancing overall operational efficiency.
Penerapan Metode Multi Factor Evaluation Process Dalam Penilaian Kinerja Karyawan Bagian Produksi CNC Muhamad Bayu Aditya Pratama; Tukino; Huda, Baenil; Hilabi, Shofa Shofiah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 5 (2024): April 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i5.1785

Abstract

Reflecting on the problems that have occurred previously due to the company's lack of managing its human resources properly, causing chaos in the production department. This problem arises because in the company there are too many PKWT (Specified Time Work Agreement) employees working, causing instability in the production line. When PKWT's work period was about to end, many prospective replacement employees resigned during the training stage because they could not stand the pressure of working in hot room temperatures in making wheel rims. This causes the company to have to look for other candidates which will take many time, while production must continue as usual. Of course, this will have a negative impact on the company if it continues in the future. Therefore, good human resource management is needed to ensure that the Company's goals are achieved efficiently and effectively. One of the things that must be done in managing human resources is monitoring and viewing employee performance. Because by knowing the performance of the Company's employees, you can ensure that tasks are carried out to predetermined standards and achieve optimal results. Employee performance assessments are carried out in the CNC section, especially on production results. This assessment aims to assess employee performance objectively and fairly, so that it can be used as an evaluation for decision making such as contract extensions, the appointment of permanent employees, promotions, and others. This performance assessment can certainly really help companies manage their human resources and reduce the impact of company losses in the future. Apart from that, this assessment is very important for a company to ensure the creation of a good quality product. The author uses a computerized system using Python and the Multi Factor Evaluation Process method to evaluate employee performance. The reason the author uses this method is because of its ability to make precise judgments based on predetermined criteria values. The data in this research is CNC production data recorded for one month. By assessing 46 employees based on data on Total Production, OK Goods (according to SOP), and Reject Goods (Not Good). The results of implementing MFEP in this performance assessment produced the highest score of 9.2 while the lowest score was 3.0.
SISTEM REKOMENDASI BUKU DENGAN METODE K-NEAREST NEIGHBOR (K-NN) PADA GRAMEDIA Dharmawan, Hafizh; Tukino; Shofiah Hilabi, Shofa; Karniawulan, Ismi
ZONAsi: Jurnal Sistem Informasi Vol. 5 No. 1 (2023): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode Januari 2023
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v5i1.12203

Abstract

Sistem rekomendasi merupakan cara yang efektif untuk membantu pengguna mencari buku yang sesuai dengan preferensinya. Sistem ini menggunakan algoritma K-Nearest Neighbor Ball tree untuk mengidentifikasi buku yang paling mirip dengan buku yang dipilih oleh pengguna dan merekomendasikan buku tersebut kepada pengguna. Metode K-Nearest Neighbor Ball tree membutuhkan banyak data untuk menghasilkan hasil yang akurat. Data ini mencakup informasi tentang buku-buku toko buku Gramedia, seperti judul, peringkat, pengarang, kategori, dan lain-lain. Sistem ini menggunakan metode K-Nearest Neighbor Ball tree dengan Google Colab untuk mengklasifikasikan dataset buku dan membuat rekomendasi berdasarkan minat pengguna. Hasilnya adalah rekomendasi buku dengan uji presisi 80% yang menunjukkan bahwa sistem ini efektif dalam menyarankan buku yang sesuai dengan minat pengguna.
MENDORONG PERTUMBUHAN UMKM MELALUI PLATFORM DIGITAL Baenil Huda; Tukino
JURNAL BUANA PENGABDIAN Vol. 5 No. 2 (2023): JURNAL BUANA PENGABDIAN
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/jurnalbuanapengabdian.v5i2.5791

Abstract

Pertumbuhan Usaha Mikro, Kecil, dan Menengah (UMKM) telah menjadi fokus utama dalam upaya meningkatkan ekonomi lokal dan nasional. Di era digital yang terus berkembang, transformasi digital menjadi kunci penting dalam mendorong pertumbuhan UMKM. Artikel ini mengulas peran penting platform digital dalam mengakselerasi pertumbuhan UMKM dengan menjelajahi cara-cara di mana transformasi digital melalui platform-platform ini dapat memberikan manfaat signifikan. Artikel ini juga membahas tantangan yang mungkin timbul selama proses transformasi digital UMKM dan merumuskan solusi potensial untuk mengatasi hambatan tersebut. Melalui wawasan holistik ini, artikel ini memberikan wawasan mendalam tentang bagaimana platform digital memiliki potensi untuk meningkatkan kinerja, ekspansi pasar, dan keberlanjutan UMKM di era yang didorong oleh teknologi
Analisis Sentimen, Text Mining Penerapan Analisis Sentimen Dan Naive Bayes Terhadap Opini Penggunaan Kendaraan Listrik Di Twitter Agustian, Adittia; Tukino; Nurapriani, Fitria
Jurnal Tika Vol 7 No 3 (2022): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v7i3.1550

Abstract

Twitter is the most popular social media today. Can find out various Twitter responses that fall into the positive, neutral, or negative categories. Technological advances at this time are so rapid that vehicles will provide fuel for electric power or are called electric vehicles. Indonesia has become a country that encourages acceleration in the use of electric vehicles, according to the Minister of State-Owned Enterprises circular letter. The advancement of electric-powered vehicles is an innovation and technology that will continue to develop and transform. With the presence of the electric vehicle, the Indonesian government will serve as an important guest vehicle at the G20 Summit activities in Bali, Indonesia. The purpose of this study is to determine the public's response to electric vehicles which are currently widely used among the people of Indonesia. To find out the public response, sentiment analysis is needed through the responses of Twitter users. By generating positive, neutral, or negative categories. Based on the results of the classification of sentiment analysis on the support of electric vehicles. Data collection uses the Twitter API as an open source that can retrieve Twitter user responses, then the data cleaning process is carried out, converting Indonesian to English, then tested using the Naïve Bayes algorithm, and visualizing twitter data using python. Based on the classification results, public response to electric vehicles is more positive with 82% precision and 44% recall. By having 80% data accuracy through the Naive Bayes confusion matrix through the text mining process, python text blob, and word cloud as the relationship between words and twitter text
Klasterisasi Kesiapan Digital Daerah: Studi Kasus Indeks SPBE di Jawa Barat, Indonesia Agustia Hananto; Tukino Tukino; Elfina Novalia
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 5 No. 1 (2025): Maret-Juni : Jurnal Ilmiah Teknik Informatika dan Komunikasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v5i1.979

Abstract

Public sector digital transformation requires a deep understanding of the digital readiness of each administrative region. The Electronic Government System (EGIS) Index is used by the Government of Indonesia as a measuring tool to assess the digital maturity of government agencies. This study aims to cluster districts/cities in West Java Province based on their 2023 EGIS scores to identify hidden patterns of digital readiness. Three unsupervised learning algorithms—K-Means, DBSCAN, and Agglomerative Clustering—are used to explore data-driven regional segmentation. The analyzed dataset includes 27 administrative regions and a number of numerical features related to the EGIS dimensions. The results show that each method is able to form clusters that reflect variations in digital readiness, with DBSCAN producing the most detailed segmentation and being able to detect outliers. Agglomerative Clustering shows good hierarchical separation, while K-Means provides a fairly representative general division. This study provides an analytical basis for contextual and targeted cluster-based policy making in developing regional digital transformation.
Analysis of the Use of Distance Learning Technology in Universities in the Riau Islands Province with the Technology Acceptance Model (TAM) Sama, Hendi; Wibowo, Tony; Tukino
Jurnal Penelitian Pendidikan IPA Vol 9 No 12 (2023): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i12.5836

Abstract

The problem that is the focus of the research is the use of distance learning technology at universities in the Riau Islands Province using the Technology Acceptance Model approach. This research aims to analyze user perceptions on ease of use, usability, usage behavior, and use of distance learning technology. This research aims to determine user perceptions of distance learning technology in universities in the Riau Islands Province. Apart from that, this research also aims to evaluate the influence of the ease of use perspective, usability perspective, and usage behavior on the use of distance learning technology. The research results show that research respondents, who are academics and staff at universities in the Riau Islands Province, have a high perception of distance learning technology. From the test results, it was found that there was no significant influence between the ease of se perspective and the usability perspective on the use of distance learning technology. However, usage behavior has a significant influence on the use of distance learning technology. Apart from that, these three variables together have an influence of 69.70% on the use of distance learning technology.
Co-Authors Abdul Latif Agustian, Adittia alfannisa annurrallah fajrin Alfannisa Annurrallah Fajrin Alfannisa Annurrullah Fajrin Alfannisa Annurullah Fajrin Alfannisa Fajrin Algifanri Maulana, Algifanri Algifari Maulana Ali Abrar Amrizal . Amrizal Amrizal Amrizal Amrizal Anggia Arista Anggia Dasa Putri April Lia Hananto Argo Putra Prima Arif Rahman Hakim Arif Rahman Hakim Arnomo, Sasa Ani Arsyad, Fachry Baenil Huda Bahariandi Aji Prasetyo Baru Harahap Bayu Priatna Bayu Yoga Astario Citra Indah Asmarawati Dede Kuswanda Dharmawan, Hafizh Dian Efriyenti Dian Efriyenti Difa Prakoso Fuadi, Muhammad Djumhadi Djumhadi Elisa, Erlin Elsya Tarigan Paskaria Loyda Tarigan Elva Susanti Erlin Elisa Fitria Nurapriani Hananto, Agustia Handoko, Koko Harman, Rika Hasanah, Haprilianh Hayati, Cucu Henry Adam Hibatullah, Muhammad Hafizh Hilabi, Shofa Shofiah Huban Kabir Huda, Baenil Ihsan, Mohammad Maftuh Ilham Fariz Asya Mubarok Imam Zaenuddin Jabar Sanjaya Juniardi Karniawulan, Ismi Lestari, Renita M Irhash Erlangga Meiti Subardhini Melisa Mildawati, Milly Muhamad Bayu Aditya Pratama Muhammad Khaerudin Muhammad Taufik Syastra NANDA HARRY MARDIKA Nofriani Fajrah, Nofriani Novalia, Elfina Nurafriani, Fitria Nurapriani, Fitria Olvia Nursaadah P, Shafira Putri Kusuma Priyatna, Bayu Purnomo, Andromedo Cahyo Ratna Juwita, Ayu Realize, Realize Rizki Prakasa Hasibuan Rohana, Tatang Rohman Nurafan Putra Pratama Ronald Wangdra Roza Yenita Ruliansyah Ruliansyah, Ruliansyah Sabrina Amanda Salsabila Saepul Aripiyanto Sama, Hendi Sandi Ahmad Shidiq, Faisal Shofa Shofia Hilabi Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Silvana Nazuah Sri Watini Steven Famy Subarkah, Ade Surala, Lyvia Suvianto Wangdra Syaeful Akbar Syahril Effendi Tony Wibowo, Tony Versanudin Hekmatyar Wibisono, Eko Gunawan Widyanti, Tyas Winarni Winda Yohanna Siahaan Young, Filbert Yovika Aprianti Yvonne Wangdra Zulkifli, Mohamad