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All Journal AKADEMIKA Jurnal Nasional Komputasi dan Teknologi Informasi Specta Journal of Technology JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) International Journal of Engineering, Science and Information Technology Journal La Multiapp Bulletin of Computer Science Research Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Ilmu Komputer Jurnal Teknologi Informasi Indonesia Journal of International Multidisciplinary Research Riau Jurnal Teknik Informatika Jurnal Karya untuk Masyarakat (JKuM) Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Repositor

Wahyudin Hasyim

Universitas Muhammadiyah Gorontalo

Author-ID : 4159728

Aerospace Engineering Humanities 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 Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Transportation Other

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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.

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

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.

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.

Prediction of Elementary School Students' Mental Health using Decision Tree Algorithm with K-Fold Cross-Validation in Bone Bolango Regency, Gorontalo Province Liputo, Salahuddin; Tupamahu, Franky; Hasyim, Wahyudin; Sabiku, Sri Ariyanti; Parman, Rahmawaty; Hanapi, Aan
Journal La Multiapp Vol. 4 No. 6 (2023): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v4i6.1005

Mental health is a fundamental component of the World Health Organization's definition of health, encompassing not only freedom from illness but also well-being in physical, mental, and social dimensions. In today's modern society, mental health has become a paramount issue, as its soundness enables individuals to realize their own potential, cope with normal life pressures, work productively, and contribute effectively to their communities. In Indonesia, mental health-related challenges are associated with the absence of a reliable mental health detection tool. Conversely, abroad, there has been a substantial amount of research focused on innovative technology-based mental health detection using Machine Learning. This study aims to predict mental health using the Social Emotional Health Survey-Secondary (SEHS-S) as the evaluation criterion for prediction through Machine Learning. The Decision Tree algorithm is employed, and the prediction model is tested using K-Fold Cross-Validation, resulting in 8 folds with an accuracy rate of 78.61%.

Penerapan Technology Acceptance Model (TAM) Pada Sistem Informasi Akademik (SIA) Universitas Muhammadiyah Gorontalo Hasyim, Wahyudin; Biya, Indrawati
SPECTA Journal of Technology Vol. 8 No. 3 (2024): SPECTA Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v8i3.790

This study aims to examine user satisfaction through the application of technology acceptance models in academic information systems. The population of this study is active students who use academic information systems as many as 2,282. The technique used in determining the sample size of a population is using the slovin technique. The sample in this study was 500 samples. The analysis technique used is quantitative analysis. The results of this study indicate The perceived usefulness variable has a significant value of 0.054 > 0.05, so it can be concluded that the hypothesis is rejected. 2) Variable Perceived Ease of use (ease of use) obtained a significant value of 0.000 <0.05, it can be concluded that the hypothesis is accepted. 3) Variable Attitude Toward Using Technology (attitude) obtained a significant value of 0.000 <0.05, it can be concluded that the hypothesis is accepted. 4) Behavioral Intention to Use (intention) variable obtained a significant value of 0.220 > 0.05, so it can be concluded that the hypothesis is rejected.

PENERAPAN DATA MINING DALA MENGKLASIFIKASI RESIKO PENYAKIT STROKE MENGGUNAKAN METODE MACHINE LEARNING Bakari, Sitti Nurfatimah; Lasarudin, Alter; Hasyim, Wahyudin
Jurnal Ilmu Komputer (JUIK) Vol 5, No 2 (2025): JUNE 2025
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v5i2.4186

Stroke adalah kondisi saraf yang ditandai dengan tanda klinis yang berkembang pesat, termasuk gangguan saraf lokal dan global yang parah, bertahan selama 24 jam atau lebih, dan berakibat fatal ketika tidak ada penyebab yang jelas selain vaskular. Penelitian ini bertujuan untuk menerapkan algoritma Support Vector Machine (SVM) dan Artiticial Neural Network (ANN) untuk mengklasifikasi risiko penyakit stroke dan mengukur tingkat akurasi dari masing-masing algoritma. Hasil penelitian menggunakan algoritma Support Vector Machine dan Artiticial Neural Network dengan jumlah record data 200 maka akan diperoleh nilai akurasi Support Vector Machine sebesar 97.46%, dan tingkat akurasi Artiticial Neural Network sebesar 98.75%. Paling algoritma Artificial Neural Network mendapatkan nilai akurasi yang tertinggi dibandingkan algoritma Support Vector Machine dalam pengklasifikasian data risiko penyakit stroke.

Co-Authors Alter Lasarudin Bagus Setio Raharjo Bakari, Sitti Nurfatimah Biya, Indrawati Citra Ayu Desi A Yusuf Dian Lestari R Djainab Humolungo Dwi Fanti Utina Fatiya Ointu Fatmawati Meilan Harun Frangky Tupamahu Gani, Hilmansyah Habie, Khairul Fathan Hadi Pratomo Hanapi, Aan Handayani, Tri Pratiwi Hapsa Husain Hasanah, Ika Nur Hendra Agus Ibrahim, Irawan Ivone Djafar Lasarudin, Alter Masri, Muhamad Mohamad Ilyas Abas Natalia R Simon Novi Bouti Noviyanti Patak Lembang Nunu Fadna Adam Nursetiawati Nursetiawati Parman, Rahmawaty Rahmatia Mohi Rapia Yakob Ingahu Renata H. Salalu Rindiyani Saputri Agu Rizal Lamusu Roy Dumako Roy Dumako Rubiyanto Maku Sabiku, Sri Ariyanti Salahuddin Liputo, Salahuddin Siti Juliana Pakaya Stevie Eka Putri Lamato Syahrial Syahrial Tri Pratiwi Handayani Tupamahu, Franky Verliana Kiayi Widya Eka Pranata

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