Garuda - Garba Rujukan Digital

p-Index From 2020 - 2025

1.978

P-Index

This Author published in this journals

All Journal Specta Journal of Technology Jurnal Repositor JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) International Journal of Engineering, Science and Information Technology Journal La Multiapp Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Ilmu Komputer Jurnal Teknologi Informasi Indonesia Journal of International Multidisciplinary Research

Wahyudin Hasyim

Universitas Muhammadiyah Gorontalo

Author-ID : 4159728

Aerospace Engineering Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 12 Documents Claim Missing Document

Claim Missing Document

Articles

1 2

SISTEM INFORMASI MUTASI PEGAWAI PADA DINAS PENDIDIKAN DAN KEBUDAYAAN KABUPATEN GORONTALO Wahyudin Hasyim
Jurnal Ilmu Komputer (JUIK) Vol 1, No 1 (2021): February 2021
Publisher : Universitas Muhammadiyah Gorontalo

An information systems of employee mutation is vitally nevessary. Because it is very helpful, facilitate the implementation of the tasks, especially in making the draft of SK teacher mutation or `employee mutation created using by visual basic version 6.0 is software commonly used by programmers to create application for a variety of needs. This application is made simple and completed with an employee database that will be used as a database for employee mutation. The last conclusion of this simple appliccation is expected to simplify the work creating a draft decree of employee mutation because it is supported by a database that is maintained.

PREDIKSI PENERIMAAN NEGARA BUKAN PAJAK (PNBP) MENGGUNAKAN ALGORITMA NEURAL NETWORK DI LPP RRI GORONTALO Djainab Humolungo; Wahyudin Hasyim; Alter Lasarudin
Jurnal Ilmu Komputer (JUIK) Vol 2, No 1 (2022): February 2022
Publisher : Universitas Muhammadiyah Gorontalo

Penerimaan Negara Bukan Pajak (PNBP) adalah salah satu sumber penerimaan negara yang sangat penting disamping penerimaan perpajakan.Maka dalam hal ini Prediksi merupakan hal penting dalam mengetahui jumlah Penerimaan Negara Bukan Pajak (PNBP) di LPP RRI Gorontalo apakah dapat memenuhi Target yang telah ditentukan oleh LPP RRI Pusat atau tidak. Data yang digunakan dalam penelitian ini sebanyak 240 data. Dengan menggunakan Algoritma Neural Network bahwa tingkat akurat Algoritma Neural Network dalam memprediksi PNBP tidak baik. Hal ini dibuktikan dengan tingkat RMSE terkecil saja masih di angka 0.076. dan setelah dilakukan pengujian menggunakan perhitungan di Microsoft Excel terlihat bahwa hasil prediksi dari 48 minggu di Tahun 2020 dan range error data hasil denormalisasi data dengan nilai range dari 23855200 sampai dengan -104726900

ANALISIS KEPUASAN MASYARAKAT TERHADAP LAYANAN SIARAN RRI GORONTALO MENGGUNAKAN ALGORITMA C4.5 Alter Lasarudin; Wahyudin Hasyim
Jurnal Ilmu Komputer (JUIK) Vol 1, No 2 (2021): October 2021
Publisher : Universitas Muhammadiyah Gorontalo

Radio broadcasting is one of the mass media that is closely related to the needs of the community that can provide various kinds of information, entertainment, and education. Community's satisfaction is the main thing in broadcasting services and becomes a benchmark in improving radio broadcasting services. Sample data used 339 data of respondents. The test results from the model that have been carried out by testing the level of accuracy using the Confusion Matrix, the results of the measurement accuracy are 97.94%, class precision for the satisfaction category is 98.39% and the NOT SATISFIED category is 93.10%. therefore concluded that C4.5 alogarithm can be applied to the process of analyzing public satisfaction with the broadcast service of RRI Gorontalo.

SISTEM INVENTARISASI ASET UNIVERSITAS MUHAMMADIYAH GORONTALO BERBASIS WEB Muhamad Masri; Mohamad Ilyas Abas; Wahyudin Hasyim; Irawan Ibrahim
Jurnal Ilmu Komputer (JUIK) Vol 2, No 2 (2022): October 2022
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v2i2.1712

Penelitian ini bertujuan untuk merancang sebuah sistem informasi inventaris aset berbasis web agar dapat memberikan solusi terhadap masalah-masalah yang dihadapi oleh pihak pegawai perlengkapan Universitas Muhammadiyah Gorontalo. Sistem ini akan membantu melakukan penataan aset yang dimiliki secara rapi, tepat serta efisien, baik dari segi waktu, tenanga maupun biaya. Dimana sistem yang akan dirancang mempunyai fasilitas untuk mengelompokkan aset, memasukkan jumlah aset, keterangan maupun kondisi dari aset. Metode yang digunakan dalam penelitian ini yakni prototype karena yang memudahkan proses perancangan mulai dari Communication, Quick Plan, Modeling Quick Design, Construction of Prototype, sampai dengan Deployment Delivery & Feedback. Hasil dari peneltian ini dapat mempermudah kinerja bagian perlengkapan dalam pendataan aset secara digital dan lebih rapi sesuai tujuan yang diharapkan.

Analisis Kepuasan Masyarakat Terhadap Layanan Siaran RRI Gorontalo Menggunakan Algoritma C4.5 Alter Lasarudin; Wahyudin Hasyim; Roy Dumako
Jurnal Repositor Vol 4 No 4 (2022): November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/repositor.v4i4.1434

Radio penyiaran merupakan salah satu media massa yang berkaitan erat dengan kebutuhan masyarakat yang dapat memberikan berbagai macam informasi, hiburan, dan pendidikan. Kepuasan masyarakat merupakan hal yang utama di dalam layanan siaran dan menjadi tolok ukur dalam meningkatkan pelayanan siaran radio. Data sampel yang digunakan dalam penelitian ini sebanyak 339 data responden. Hasil pengujian dari model yang telah dilakukan dengan pengujian tingkat akurasi dengan menggunakan Confussion Matrix didapatkan hasil pengukuran akurasi sebesar 97.94%, class precission untuk kategori PUAS sebesar 98.39% dan kategori TIDAK PUAS 93.10%. Sehingga dapat disimpulkan bahwa algoritma C4.5 dapat diterapkan untuk proses analisis kepuasan masyarakat terhadap layanan siaran RRI Gorontalo.

Penerapan Model COBIT 5 dalam Audit Sistem Informasi Penerimaan Negara Bukan Pajak Online Pada Lembaga Penyiaran Publik Radio Republik Indonesia Wahyudin Hasyim; Moh. Ilyas Abas; Rahmatia Mohi
Journal of Information System Research (JOSH) Vol 4 No 4 (2023): Juli 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i4.3853

Audit is an independent and standardized systematic process that completes evidence and compares it objectively to determine the extent to which audit interpretations have been complied with. One of the standards used in the implementation of the information systems audit process is COBIT (Control Objectives for Information and Related Technology). Online PNBP still has identified problems, including that the Online PNBP application does not accommodate all Types and Tariffs for PNBP types. This study aims to conduct an online PNBP information system audit at LPP RRI Gorontalo. This study uses the APO04 (Manage Innovation) domain at COBIT 5 with the research stages using Assessment Process Activities. The data used in this study are secondary data and primary data obtained through the observation phase of interviews and questionnaires. Based on the research results, the average value in the APO04 sub-domain in the current condition (As Is) is 0.24 and the expected condition (To Be) is 0.20 or still at level 0. With the largest gap or gap value is in the APO04.02 sub domain, which is 0.54. With these results it is found that LPP RRI Gorontalo has not carried out IT processes that should have existed, or been added and have not succeeded in achieving the objectives of the IT process and have not been optimal in maintaining understanding of the company's environment, so the suggestion that can be given is to maximize understanding of the environment companies so that they can understand the interests of both consumers and companies so that opportunities enabled by new technologies can be identified

O OPTIMALISASI NEURAL NETWORK BERBASIS PARTICLE SWARM OPTIMIZATION UNTUK MEMPREDIKSI LAMA PENYINARAN MATAHARI DALAM MEMENUHI KEBUTUHAN ENERGI Wahyudin Hasyim; Alter Lasarudin
Jurnal Teknologi Informasi Indonesia (JTII) Vol 4 No 2 (2019): Jurnal Teknologi Informasi Indonesia (November)
Publisher : JURNAL TEKNIK INFORMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30869/jtii.v4i2.391

Tingginya beban listrik yang mencapai 325 MegaWatt, hal ini merupakan perhatian penting bagi pemerintah Provinsi Gorontalo dalam kebutuhan energi listrik, maka perlu memprediksi lama penyinaran matarahari pada suatu daerah, Energi sel surya salah satunya bergantung pada lamanya penyinaran cahaya matahari. Diantaranya dengan melakukan perancangan model prediksi. Metode prediksi yang mimiliki nilai error terkecil adalah Neural Network, akan tetapi masih adanya kelemahan pada waktu pelatihan untuk mencapai konvergen dan overfitting. Maka perlu dilakukan optimalisasi pada bobot jaringan dengan menggunakan Particle Swarm Optimazition, yang merupakan salah satu metode terbaik dalam optimasi. Dengan penggunaan optimasi yang diukur melalui hasil peroleha Root Mean Square Error (RMSE). Hasil pengujian terhadap algoritma menunjukkan bahwa nilai RMSE mengunakan Neural Network 0,131, sedangkan dengan penerapan optimasi dengan particle swarm optimization hasil RMSE 0,127. Dengan penerapan metode optimasi terserbut dapat mengurangi nilai error

ANALISIS JARINGAN INTERNET MENGGUNAKAN PARAMETER QUALITY OF SERVICE (QOS) DI UNIVERSITAS MUHAMMADIYAH GORONTALO Wahyudin Hasyim; Alter Lasarudin; Bagus Setio Raharjo
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 2 (2024): EDISI 20
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i2.4156

Saat ini internet sudah menjadi kebutuhan primer pada era serba digital seperti saat ini. Kebutuhan akan informasi yang cepat membuat internet sangat penting, kebutuhan tersebut harus didukung dengan adanya internet yang selalu tersedia dan stabil. Ketersediaan internet yang stabil dan baik di Universitas Muhammadiyah Gorontalo sangat dibutuhkan oleh staff, dosen, dan mahasiswa untuk proses belajar mengajar, dan juga kegiatan akademik lainnya. Penelitian ini bertujuan untuk melakukan analisis jaringan internet di Universitas Muhammadiyah Gorontalo menggunakan parameter Quality of Service (QOS) untuk mengetahui kualitas serta kemampuan kinerja jaringan yang ada. Pengujian menggunakan software wireshark untuk memperoleh nilai parameter throughput, delay, jitter, dan packet loss. Hasil penelitian menunjukkan kualitas jaringan internet di Universitas Muhammadiyah Gorontalo berada dalam kategori bagus. Dengan nilai throughput = 228,866 bit/s dengan nilai indeks 4, delay = 51,736 ms dengan nilai indeks 4, jitter = 1,026 ms dengannilai indeks 3 dan packet loss = 9% dengan nilai indeks 3.

Comparative Analysis of CNN-RNN Models for Hatespeech Detection Incorporating L2 regularization Handayani, Tri Pratiwi; Hasyim, Wahyudin
International Journal of Engineering, Science and Information Technology Vol 4, No 1 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i1.491

This study aims to address the challenge of detecting hate speech in text data by comparing two experimental CNN-RNN models. The primary issue is achieving a balance between precision and recall in hate speech detection while preventing overfitting and ensuring good generalization. Two different approaches were applied: the first model used standard training techniques, while the second model incorporated L2 regularization and early stopping. The research involved using Keras Tokenizer for text tokenization, layering with CNN and LSTM for feature extraction and temporal context capturing, and applying dropout to prevent overfitting. L2 regularization and early stopping were added to the second model to enhance generalization. The findings reveal that the first model, although exhibiting some overfitting, attained a higher overall accuracy of 78% and more balanced F1-scores for both the "Not Hate Speech" and "Hate Speech" categories. The second model, although achieving higher precision for hate speech (0.81), had lower recall (0.58), resulting in an overall accuracy of 75%. This suggests that regularization and early stopping need careful tuning to avoid reducing sensitivity to hate speech detection.

Preliminary Evaluation of Gaussian Naive Bayes for Multi-Label Hate Speech and Abusive Language Detection on Indonesian Twitter Handayani, Tri Pratiwi; Hasyim, Wahyudin; Wati, Nursetia
Journal of International Multidisciplinary Research Vol. 1 No. 1 (2023): November 2023
Publisher : PT. Banjarese Pacific Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62504/jimr532

Automatic detection of hate speech and abusive language is crucial for combating online toxicity. This study explores Gaussian Naive Bayes for multi-label classification of hate speech on Indonesian Twitter, including target, category, and level. We combined TF-IDF features with contextual BERT embeddings. The model achieved balanced performance for general hate speech and good non-abusive language detection. However, it exhibited limitations with imbalanced data and specific hate speech types. The classifier consistently favored the majority class (non-hateful/non-abusive) across labels, particularly struggling with HS_Gender, HS_Physical, etc. This suggests difficulty detecting less frequent but potentially severe hate speech, likely due to limited training data. Overall accuracy and F1-scores confirm that while Gaussian Naive Bayes is efficient, it lacks robustness for nuanced multi-label classification with imbalanced datasets. This necessitates exploring alternative approaches for effectively detecting specific and less frequent hate speech.

Co-Authors Alter Lasarudin Bagus Setio Raharjo Biya, Indrawati Djainab Humolungo Hanapi, Aan Handayani, Tri Pratiwi Irawan Ibrahim Masri, Muhamad Mohamad Ilyas Abas Nursetiawati Nursetiawati Parman, Rahmawaty Rahmatia Mohi Roy Dumako Sabiku, Sri Ariyanti Salahuddin Liputo, Salahuddin Tupamahu, Franky

Title

Found 12 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 12 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 12 Documents
Search