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All Journal Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal CoreIT JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Pengabdian Kepada Masyarakat (Mediteg) Jurnal Humaniora Teknologi Jurnal Humaniora Teknologi Brilliance: Research of Artificial Intelligence Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Ininnawa: Jurnal Pengabdian Masyarakat Teknomatika: Jurnal Informatika dan Komputer Journal of Advanced Computer Knowledge and Algorithms
Herfia Rhomadhona
Teknik Informatika, Politeknik Negeri Tanah Laut
Religion Aerospace Engineering Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Design and Development of a Web-Based Correspondence Management Information System at Politeknik Negeri Tanah Laut Rhomadhona, Herfia; Noor Hayatie, Marliza; Pebriana, Rina
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4878

Abstract

Correspondence at Politeknik Negeri Tanah Laut (Politala) is currently still done manually in the vertical delivery process between work units. This manual process results in inefficiency, especially in monitoring the status of documents such as Staff Review Documents. Staff Review is a document that must be made by the department to the director as a basis for requesting assignment letters, decrees, recommendation letters and the others. These documents often require repeated checking, causing delays in the workflow. In addition, paper-based correspondence archives increase the risk of losing documents and make it difficult to find them again. Therefore, the implementation of the Correspondence Management Information System (SiMantan) is needed to improve the efficiency of the correspondence administration process by providing electronic document management and real-time status monitoring. This information system is built using the waterfall development model and designed with the Unified Modeling Language (UML) in the form of Usecase Diagrams. While the programming language used is the PHP programming language with the Code Ignitor 3 framework and MySQL database. Functional testing of the system is carried out using the black box testing and user acceptance testing (UAT) method which shows that all features in the information system function properly according to the expected specifications.
PELATIHAN PEMBUATAN GAME SEDERHANA SEBAGAI MEDIA PEMBELAJARAN UNTUK PENGAJAR SMP BERBASIS ARTIFICIAL INTELEGENT Sabella, Billy; Rhomadhona, Herfia; Rusadi Arrahimi, Ahmad
Jurnal Widya Laksmi: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 2 (2023): Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat)
Publisher : Yayasan Lavandaia Dharma Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59458/jwl.v3i2.59

Abstract

Pengabdian kepada masyarakat dilakukan di Desa Bumijaya Kecamatan Pelaihari Kabupaten Tanah Laut Provinsi Kalimantan Selatan. Sasaran dari pengabdian ini adalah pada pengajar Sekolah Menengah Pertama (SMP) di Desa Bumijaya. Sebagian besar pengajar menggunakan media pembelajaran yang masih konvensional. Dimana para pengajar belum menggunakan teknologi sebagai media pembelajaran. Oleh sebab itu, dibutuhkan sebuah pelatihan media pembelajaran menggunakan teknologi. Teknologi yang dimaksud adalah Artificial Intelegent yang diterapkan dalam pembuatan game sederhana dengan Scratch sebagai media pembelajaran. Tahapan pelaksanaan dalam kegiatan tersebut adalah pemaparan materi artificial intelegent, pembuatan akun scratch, membuat game kemudian evaluasi. Evaluasi pelatihan pembuatan game sederhana dilakukan oleh 10 (sepuluh) pengajar dengan 30 soal yang terdiri dari soal pretest dan postest. Soal yang digunakan untuk pretest dan postest merupakan soal yang sama guna mengukur tingkat pehaman pengajar. Berdasarkan hasil evaluasi menunjukan peningkatan pengetahuan tentang coding Artificial Intelegent dan scratch.
Implementation of KNN and AHP-TOPSIS as Recommendation System for Mustahik Selection Aprianti, Winda; Permadi, Jaka; Rhomadhona, Herfia; Amelia, Noor
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.3883

Abstract

The National Amil Zakat Agency (BAZNAS) has the task of managing zakat on a national scale, including zakat. The number of prospective zakat recipients is greater than the availability of zakat funds distributed, which has an impact on the need for a selection process for mustahik. In this research, to assist the mustahik selection process, KNN will be used to classify mustahik candidates who meet the requirements, AHP to obtain consistent weights, and TOPSIS to provide recommendations for the order of mustahik whose zakat will be distributed. The dataset used in the research consisted of 77 data consisting of the criteria for number of dependents, husband's job, wife's job, total income, total expenses, and acceptance status of mustahik candidates. The application of KNN produced 15 data that were declared worthy of being considered mustahik. In the next stage, using AHP, the weights for each criterion were obtained at 12.66%, 9.23%, 10.10%, 45.96% and 22.04%. These weights were used in the TOPSIS decision support system and the results obtained were that the 76th mustahik candidate was the first ranked candidate to be proposed as a mustahik. In this research, a system was also built using KNN and AHP-TOPSIS using the PHP programming language as a recommendation system tool.
RAKERNAS ADAKSI 2025 sebagai Langkah Strategis dalam Perjuangan Keberlanjutan Kesejahteraan Dosen ASN Sampetoding, Eliyah Acantha Manapa; Rhomadhona, Herfia; Kurniawan, Rio; Adiasti, Nindya; Darwis, Hamris; Aufi, Ahmad Umam; Tampubolon, Jonris; Pongtambing, Yulita Sirinti
Ininnawa : Jurnal Pengabdian Masyarakat Vol. 3 No. 2 (2025): Vol. 3 No. 2 (2025): Volume 03 Nomor 02 (Oktober 2025)
Publisher : Program Studi Manajemen FEB UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/ininnawa.v3i2.9583

Abstract

Rapat Kerja Nasional (RAKERNAS) Aliansi Dosen ASN Indonesia (ADAKSI) Tahun 2025 diselenggarakan sebagai forum strategis untuk memperkuat konsolidasi organisasi dan memperjuangkan hak-hak dosen ASN di seluruh Indonesia. Kegiatan ini dihadiri oleh Ketua Umum ADAKSI, Dewan Pakar, serta Ketua Badan Kepegawaian Negara (BKN) yang memberikan legitimasi formal atas eksistensi ADAKSI sebagai organisasi profesi. Agenda utama meliputi pelantikan Dewan Pengurus Pusat (DPP) periode 2025–2028, pengesahan 19 Dewan Pengurus Wilayah (DPW), pembahasan program kerja 2025–2026, serta diskusi panel tematik yang menyoroti isu kesejahteraan, karier, dan profesionalisme dosen ASN. Melalui forum ini, disepakati sejumlah rekomendasi strategis, antara lain pemerataan tunjangan kinerja, advokasi kenaikan tunjangan fungsional, penyusunan roadmap jenjang karier, serta penguatan riset dan publikasi akademik. Rekomendasi tersebut disusun berbasis data dan pengalaman lapangan, sehingga dapat menjadi landasan advokasi berbasis bukti (evidence-based advocacy). Hasil RAKERNAS menunjukkan bahwa ADAKSI memiliki peran penting sebagai mitra strategis pemerintah dalam meningkatkan kesejahteraan dan pengakuan profesionalisme dosen ASN. Dengan kepengurusan yang sah dan representatif, RAKERNAS 2025 diharapkan menjadi pijakan bagi perjuangan berkelanjutan dalam mewujudkan keadilan, kepastian karier, serta kontribusi dosen ASN bagi pembangunan sumber daya manusia Indonesia.
Prediction Active Case of Covid-19 with ERNN Aprianti, Winda; Permadi, Jaka; Rhomadhona, Herfia
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 1 (2022): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i1.4874

Abstract

SARS-CoV-2 is known as Covid-19 has been spread in all world since end of 2019. Indonesia, including South Kalimantan has detected first Covid-19 in March 2020. This pandemic has affected in all entirely live in Indonesia. This makes Covid-19 be the main focus of the government. The government has provided aid and imposed restrictions on activities. These policies require planning that can be a solution. Careful planning requires an overview of the data on active cases that are positive for Covid-19. This overview can be obtained through prediction. In this research, Elman Recurrent Neural Network (ERNN) was used to predict active cases of Covid-19. Architecture of ERNN was used ERNN with 3 input nodes, 2 hidden nodes, and 2 context nodes. The data used is 277 data, which is then divided into training data and testing data, respectively 90%-10%, 80%-20%, and 70%-30%. ERNN with a learning rate of 0.1 until 0.9 is applied to data on active cases of Covid-19, then Mean Absolute Percentage Error (MAPE) is calculated to find out performance of model generated by ERNN. The results showed that all of MAPE were below 10% with the smallest MAPE as 3.21% for scenario 90:10 and learning rate 0.6. MAPE value which is less than 10% indicates that ERNN has very good predictive ability. 
Co-Authors Adiasti, Nindya Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Umam Aufi Amelia, Noor Cut Agusniar Darwis, Hamris Eliyah Acantha Manapa Sampetoding Fathurrahmani Fathurrahmani Hendrik Setyo Utomo herpendi, herpendi Jonris Tampubolon Kusrini, Wiwik Muhammad Alfian, Muhammad Mulya Ulfa, Septia Noor Amelia Noor Hayatie, Marliza Noor, Agustian Permadi, Jaka Rakhmilawati Faznur Rina Pebriana, Rina Rio Kurniawan Sabella, Billy Supriyanto, Arif Winda Aprianti Wiwik Kusrini Yulita Sirinti Pongtambing