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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Pilar Nusa Mandiri Krea-TIF: Jurnal Teknik Informatika Building of Informatics, Technology and Science JURNAL TEKNIK JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JIKA (Jurnal Informatika) Tematik : Jurnal Teknologi Informasi Komunikasi Insearch: Information System Research Journal J-Intech (Journal of Information and Technology)
Alamsyah, Dedy
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Kombinasi Metode Rank Reciprocal dan Composite Performance Index Untuk Sistem Pendukung Keputusan Promosi Jabatan Alamsyah, Dedy; Herdiansah, Arief; Wijaya, Hamid; Rusdianto, Hengki
J-INTECH (Journal of Information and Technology) Vol 12 No 1 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i1.1199

Abstract

Dalam konteks globalisasi dan persaingan bisnis yang ketat, promosi jabatan merupakan aspek strategis yang esensial bagi kelangsungan hidup dan pertumbuhan organisasi. Keputusan promosi yang objektif dan merata tidak hanya meningkatkan motivasi karyawan tetapi juga memaksimalkan potensi sumber daya manusia, meningkatkan produktivitas organisasi. Namun, penilaian kelayakan kandidat untuk promosi seringkali dihadapkan pada tantangan evaluasi kriteria yang kompleks dan subjektif. Penelitian ini bertujuan untuk mengembangkan Sistem Pendukung Keputusan (SPK) untuk promosi jabatan yang mempermudah pengambil keputusan menentukan pilihan yang objektif dan efisien dengan menggabungkan metode Rank Reciprocal (RR) dan Composite Performance Index (CPI). Metode RR mengurangi bias penilaian subjektif dengan memberikan bobot terbalik berdasarkan peringkat kriteria, sedangkan CPI mengintegrasikan berbagai dimensi kinerja menjadi satu indeks komprehensif, memungkinkan evaluasi holistik dari setiap kandidat. Output hasil perhitungan SPK yang diperoleh secara manual dalam studi kasus sesuai dengan output sistem, menunjukkan keabsahan perhitungan sistem. Disamping itu, hasil pengujian menggunakan pendekatan black-box testing juga memperlihatkan kemampuan sistem dalam menjalankan fungsinya dengan baik.
Klasifikasi Risiko Diabetes Mellitus Menggunakan K-Nearest Neighbors dengan Peningkatan Performa Melalui Teknik Oversampling ADASYN Bagir, Muhammad; Mayatopani, Hendra; Riyanto, Umbar; Alamsyah, Dedy
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7237

Abstract

Diabetes mellitus is a chronic metabolic disease with a continuously increasing global prevalence. Early detection of diabetes risk is crucial to reduce long-term health complications and the associated healthcare costs. However, a major challenge in applying machine learning models to medical data is the issue of class imbalance, which can lead to model bias toward the majority class. This study aims to develop a diabetes risk classification model by integrating the K-Nearest Neighbors (KNN) algorithm with the Adaptive Synthetic Sampling (ADASYN) technique to address the class imbalance problem. The dataset used was obtained from the Kaggle platform, containing 2,000 patient samples with nine predictive features. Data preprocessing was performed through missing value imputation, outlier handling using winsorizing, and feature normalization using StandardScaler. ADASYN was applied to generate adaptive synthetic samples for the minority class, and the KNN model was trained and evaluated using confusion matrix, precision, recall, F1-Score, accuracy, and ROC-AUC metrics. The results indicate that the implementation of ADASYN improved the ROC-AUC Score by 5.48% (from 91.34% to 96.82%) and the overall accuracy by 2.50% (from 81.50% to 84.00%). The F1-Score for the Diabetes class also increased by 0.40%. The integration of KNN and ADASYN has proven effective in enhancing model performance for detecting high-risk diabetes patients and improving sensitivity toward the minority class.
Rancang Bangun Sistem Informasi Daily Reports Untuk Monitoring Kinerja Section Bushing Hunger Di PT. Aneka Komkar Utama Rusdianto, Hengki; Damayanti, Nova Indah; Wibowo, Agung; Alamsyah, Dedy
Jurnal Teknik Vol 14, No 2 (2025): Juli - Desember 2025
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jt.v14i2.14839

Abstract

The advancement of information technology encourages companies, particularly in the manufacturing industry, to adopt digital systems in order to improve operational efficiency, including in daily production reporting. At PT Aneka Komkar Utama, especially in the production area of the Bushing Hanger section, the reporting process is still carried out manually, which makes it prone to recording errors, delays, and difficulties in data verification and analysis. This condition poses a risk of hampering performance monitoring and managerial decision-making. This study aims to design and develop an integrated and user-friendly web-based daily reporting information system using the Laravel framework. The system is designed using the Spiral model approach, which allows for iterative and gradual development through several phases: communication, planning, risk analysis, engineering, construction and deployment, and user evaluation. This approach is chosen to ensure that the system developed can flexibly adapt to user needs. The result of this research is a system capable of recording and presenting production data in real-time, thereby improving the efficiency, accuracy, and transparency of daily reports. In addition, the system provides users with the convenience of monitoring and identifying potential improvements in production performance more quickly and precisely, ultimately supporting more effective and data-driven decision-making processes.
Co-Authors Agung Wibowo Alfry Aristo Jansen Sinlae Damayanti, Nova Indah Damuri , Amat Damuri, Amat Daniarti, Yeni Dartono, Dartono Destriana, Rachmat Fazrin, Qubaila Ega Fryda Fatmayati Handayani, Nurdiana Herdiansah, Arief Husain, Syepry Maulana Jusmawati Jusmawati, Jusmawati Kencana, Nadila Pilar Lilik Suhery, Lilik Lisnawati, Tuti Mayatopani, Hendra Muhammad Bagir Nurhayati Nurhayati nurnaningsih, Desi Putriana, Epi Reno Saputra Elsi, Zulhipni Rini Nuraini, Rini Riyanto, Umbar Rusdianto, Hengki Satya, Juli Budi Septarini, Ri Sabti Sri Nurhayati Wijaya, Hamid Wijayanti, Rima Rizqi Yudaningsih, Nunik