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All Journal Jurnal Nasional Komputasi dan Teknologi Informasi Specta Journal of Technology Jurnal Repositor KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Teknologi Informasi Cyberku Jurnal Ilmu Komputer Riau Jurnal Teknik Informatika Jurnal Nasional Komputasi dan Teknologi Informasi
Alter Lasarudin
Universitas Muhammadiyah Gorontalo, Gorontalo
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Neuroscience Transportation

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Analisis Pelanggaran Disiplin dan Kode Etik Anggota Polri Menggunakan Decision Tree C4.5 Fahriyadi Purnama Thaib; Frangky Tupamahu; Alter Lasarudin; Hilmansyah Gani
Riau Jurnal Teknik Informatika Vol. 5 No. 2 (2026): Juli 2026
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v5i2.4711

Abstract

Disciplinary and ethical violations committed by police officers can affect organizational professionalism and reduce public trust in law enforcement institutions. The management of violation records at Polresta Gorontalo Kota remains largely administrative, making it difficult to identify violation patterns and support data-driven decision-making. This study aims to analyze disciplinary and ethical violation data using the Decision Tree C4.5 algorithm to develop a classification model and decision rules. The dataset consists of police disciplinary and ethical violation records collected between 2022 and 2026. The results indicate that the violation category attribute serves as the root node of the decision tree, with the highest Gain Ratio value of 0.694. The resulting model successfully classifies violations into three sanction levels—minor, moderate, and severe—while generating interpretable decision rules. Model evaluation using a confusion matrix achieved an accuracy of 70.8%. The findings demonstrate that the C4.5 algorithm is capable of identifying patterns between violation types and sanction levels, indicating its potential as a decision-support tool for managing disciplinary and ethical violations within the Indonesian National Police.
Usability Sistem Informasi Aparatur Sipil Negara (SIASN) Menggunakan Metode System Usability Scale (SUS) pada BKPSDM Kabupaten Gorontalo Arifin Ahudulu; Alter Lasarudin; Frangky Tupamahu; Hilmansyah Gani
Riau Jurnal Teknik Informatika Vol. 5 No. 2 (2026): Juli 2026
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v5i2.4713

Abstract

The acceleration of digital transformation in the public sector requires reliable personnel information systems to support efficient and integrated administrative services. The State Civil Apparatus Information System (SIASN) serves as a national platform for managing personnel data and administrative processes of civil servants in Indonesia. However, its implementation at the Regional Civil Service and Human Resource Development Agency (BKPSDM) of Gorontalo Regency still faces several technical and usability-related challenges that may affect user experience and service effectiveness. This study aims to identify user constraints, measure the usability level of SIASN, and provide recommendations for system improvement. A quantitative descriptive approach was employed through data collection using questionnaires, in-depth interviews, and field observations. The study involved 30 active SIASN users, and usability data were analyzed using the System Usability Scale (SUS) instrument. The results indicate that the main obstacles experienced by users include data storage failures, slow system access during peak hours, data updates that have not taken place in real-time, complexity of menu navigation, and limitations of account recovery features. The results of the usability measurement resulted in an average SUS score of 76.4 which is included in the Good category with an Acceptable acceptance rate. These findings show that SIASN is able to support personnel administration activities well and is accepted by users. However, improving the quality of the system is still necessary through optimizing server performance, simplifying the user interface, synchronizing data in real-time, and developing a password reset feature independently. The results of this research are expected to be evaluation materials for developers to improve the quality of digital-based personnel services.
PREDIKSI TINGKAT KEKERASAN PADA PEREMPUAN DAN ANAK DI KABUPATEN GORONTALO MENGGUNAKAN MACHINE LEARNING Citra Ayu; Alter Lasarudin; Wahyudin Hasyim
Jurnal Ilmu Komputer (JUIK) Vol 5, No 3 (2025): OCTOBER 2025
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v5i3.4182

Abstract

Kekerasan terhadap perempuan dan anak merupakan isu sosial yang masih perlu mendapatkan perhatian khusus, terutama di Kabupaten Gorontalo yang memiliki angka kasus tertinggi di Provinsi Gorontalo. Penelitian ini bertujuan untuk memprediksi tingkat kekerasan terhadap perempuan dan anak menggunakan metode Machine Learning dengan algoritma Naïve Bayes dan Regresi Linier Berganda. Hasil penelitian menunjukkan bahwa Naïve Bayes menghasilkan RMSE sebesar 0.174 untuk kasus perempuan dan 0.254 untuk kasus anak. Sementara itu, Regresi Linier Berganda menghasilkan RMSE yang sangat kecil yaitu 0.000, baik untuk kasus perempuan maupun kasus anak. Dari hasil tersebut, dapat disimpulkan bahwa algoritma Regresi Linier Berganda lebih akurat dalam memprediksi tingkat kekerasan. Dengan hasil penelitian ini, diharapkan dapat membantu pemerintah dan lembaga terkait dalam mengambil langkah pencegahan serta tindakan yang lebih cepat, sehingga kasus kekerasan terhadap perempuan dan anak di Kabupaten Gorontalo dapat dicegah.
PERBANDINGAN ALGORITMA NAIVE BAYES, LOGISTIC REGRESSION DAN ARTIFICIAL NEURAL NETWORK UNTUK KLASIFIKASI TINGKAT KESEJAHTERAAN KELUARGA Natalia R Simon; Alter Lasarudin; Wahyudin Hasyim
Jurnal Ilmu Komputer (JUIK) Vol 5, No 3 (2025): OCTOBER 2025
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v5i3.4931

Abstract

Desa Batu Hijau adalah salah satu desa di pesisir pantai yang ada diKecamatan Bonepantai Kabupaten Bone Bolango. Saat ini klasifikasi tingkat kesejahteraan keluarga di wilayah tersebut belum sepenuhnya tepat, yang mengakibatkan distribusi subsidi yang tidak tepat sasaran. Oleh karena itu, sangat penting untuk memahami tingkat kesejahteraan keluarga di Desa tersebut. Dalam penelitian ini, penulis menggunakan algoritma Naive Bayes, Logistic Regression, dan Artificial Neural Network. Berdasarkan hasil percobaan menggunakan tool rapidminer dan google colab algoritma naive bayes, logistic regression, dan artificial neural network memiliki nilai akurasi yang sama yaitu 100%, precision 100%, serta recall 100%. Berdasarkan Hasil pengujian menggunakantoolrapidminerdangooglecolabalgoritmaNaiveBayes,LogisticRegression,danArtificialNeural Network mampu mengklasifikasikan data tingkat kesejahteraan keluarga dengan sempurna yang menunjukkan bahwa model mampu mengklasifikasikan data tanpa kesalahan. 
Co-Authors Arifin Ahudulu Bagus Setio Raharjo Bakari, Sitti Nurfatimah Citra Ayu Djainab Humolungo Dwi Fanti Utina Fahriyadi Purnama Thaib Fatiya Ointu Frangky Tupamahu Gani, Hilmansyah Handayani, Tri Pratiwi Hapsa Husain Hasanah, Ika Nur Ibrahim, Irawan Ivone Djafar Miranda A. Hasan Misran Tomayahu Mohamad Ilyas Abas Natalia R Simon Noviyanti Patak Lembang Polapa, Risman Purwanto Purwanto Rindiyani Saputri Agu Roy Dumako Rubiyanto Maku Sitnasanti Yane Tri Pratiwi Handayani Wahyudin Hasyim Yulanda Yunus