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All Journal Format : Jurnal Imiah Teknik Informatika Jurnal Ilmiah FIFO JURNAL PENDIDIKAN TAMBUSAI JSAI (Journal Scientific and Applied Informatics) Building of Informatics, Technology and Science Jurnal Teknik Informatika (JUTIF) Bulletin of Data Science Batara Wisnu : Indonesian Journal of Community Services Journal of Computing and Informatics Research Journal Of Technology and Information System (J-TIS) IPSIKOM
Sah, Andrian
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mathematics Social Sciences

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PENERAPAN METODE WATERFALL DALAM PENGEMBANGAN SISTEM INFORMASI E-LEARNING (Studi Kasus : SMP NEGERI 5 JAYAPURA) Robo, Salahudin; Sah, Andrian; Sidarmawan, Andri Tri
JSAI (Journal Scientific and Applied Informatics) Vol 4, No 2 (2021): Juni 2021
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v4i2.1618

Abstract

Permasalahan yang terjadi di SMP Negeri 5 Jayapura adalah selama ini proses pembelajaran antara guru dan siswa sangat terbatas. Proses pembelajaran berlangsung dari hari Senin sampai dengan Jumat. Tiap harinya terdapat 3 sampai 4 mata pelajaran yang diajarkan dan untuk satu mata pelajaran hanya berkisar 1 sampai 2 jam. Akibat hal ini interaksi antara guru dan siswa menjadi kurang interaktif, siswa tidak memiliki banyak waktu dalam mengerjakan soal dan mendalami materi yang diberikan. Sehingga jika terjadi kendala, seperti siswa kurang paham mengenai materi pelajaran, akan kesulitan jika ingin mengulangi materi dan bertanya kepada guru yang bersangkutan secara langsung.Siswa juga tidak mendapatkan materi pelajaran dan tugas apabila guru berhalangan hadir, ini menyebabkan penyampaian materi pelajaran menjadi terhambat. Siswa hanya mendapatkan materi pelajaran dari guru maupun referensi buku di perpustakaan sekolah, sehingga terjadi keterbatasan tempat dan waktu untuk mengaksesnya. E- learning dapat digunakan sebagai alternatif atas permasalahan dalam bidang pendidikan, baik sebagai tambahan, pelengkap maupun pengganti atas kegiatan pembelajaran yang sudah ada.Dilihat dari kenyataan tersebut, diperlukan suatu sarana penunjang yang mampu meningkatkan efektivitas dan efisiensi sistem mengajar di SMP Negeri 5 Jayapura dalam meningkatkan pembelajaran siswa
Sistem Informasi Manajemen Pengelolaan Nilai Siswa pada SMK Hikmah Yapis Jayapura Nurhayati, Siti; Suharto, Emilda; Tonggiroh, Mursalim; Sah, Andrian
Journal Of Technology and Information System (J-TIS) Vol 1 No 1 (2022): Juli 2022
Publisher : Program Studi Sistem Informasi, Universitas Yapis Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70129/jtis.v1i1.236

Abstract

Pengolahan nilai siswa, seperti nilai harian, nilai penilaian tengah semester (PTS) dan nilai Penilaian Akhir Semester (PAS) pada SMK Hikmah masih menggunakan aplikasi Microsoft Excel yang memiliki kekurangan, yakni terformatnya setiap kolom ataupun baris yang ada akan menyebabkan penggabungan nilai dari penambahan materi jika struktur kurikulum berganti, belum terintegrasi dari guru ke guru lainnya membuat pemberian informasi nilai masih menggunakan flash disk sehingga waktu yang dibutuhkan untuk mengolah nilai cukup lama, presensi siswa masih menggunakan buku presensi, aplikasi tidak menyediakan proses pengolahan nilai harian. Maka diperlukan sebuah sistem informasi manajemen nilai siswa yang dapat mengolah semua nilai siswa dengan mengintegrasikan setiap alur pada proses pengolahan nilai siswa. Adapun metode yang digunakan untuk menganalisis permasalahan serta memberikan solusi dari permasalahan tersebut adalah metode PIECES, metode perancangan yang digunakan adalah UML. Dari penelitian ini dihasilkan Sistem Informasi Manajemen Pengelolaan Nilai Siswa yang mengintegrasikan nilai antar guru sehingga dapat mengefektifkan waktu dalam mengolah nilai siswa.
Sistem Informasi Pas Lintas Batas (Studi Kasus : Pos Lintas Batas Tradisional Hamadi) Sukriyan, Mohamad Maulidin; Sah, Andrian
Journal Of Technology and Information System (J-TIS) Vol 1 No 1 (2022): Juli 2022
Publisher : Program Studi Sistem Informasi, Universitas Yapis Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70129/jtis.v1i1.237

Abstract

Pegawai Imigrasi atau petugas Imigrasi yang bertugas di Pos Lintas Batas Negara maupun Tradisional merupakan pegawai Imigrasi dibawah SubSeksi Pemeriksa Keimigrasian dan dibawah Seksi Lalulintas Keimigrasian pada Unit kerja Kantor Imigrasi di daerah tersebut,salah satu tugasnya yaitu melaporkan data perlintasan orang yang keluar maupun masuk melalui Pos Lintas Batas. Pada tugas akhir ini, peneliti mencoba untuk menganalis pokok-pokok permasalahan yang ada, dan mencoba memberikan panduan kepada petugas di pos untuk dapat memulai mengembangkan sistem informasi perlintasan yang ada menggunakan metode perancangan UML dan menggunakan metode pengembangan waterfall. Aplikasi yang dihasilkan berupa aplikasi web “Sistem Informasi Pas Lintas Batas”, yang ditujukan untuk memberikan kemudahan bagi petugas yang bertugas di pos untuk mengelola data perlintasan dan mempermudah dalam membuat laporan perlintasan yang ada. Disamping itu peneliti juga menganjurkan agar kedepanya bisa mengembangkan aplikasi yang penulis buat saat ini.
SISTEM INFORMASI CUTI PEGAWAI (STUDI KASUS : KANTOR SEKRETARIAT DPRD KOTA JAYAPURA) Putra, Andika; Sah, Andrian; Ponto, Sahrul
Journal Of Technology and Information System (J-TIS) Vol 1 No 1 (2022): Juli 2022
Publisher : Program Studi Sistem Informasi, Universitas Yapis Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70129/jtis.v1i1.239

Abstract

Sekretariat Dewan Perkawilan Rakyat Daerah Kota Jayapura dipimpin oleh seorang Sekretaris Dewan yang secara teknis operasional berada dibawah dan bertanggung jawab kepada Pimpinan DPRD dan secara administratif bertanggung jawab kepada Walikota melalui Sekretaris Daerah. Dalam proses pengajuan cuti masih dinilai belum efektif, karena semua pemrosesan data khususnya pada bagian kepegawaian masih dilakukan secara manual dimana dalam proses pengajuan cuti masih menggunakan kertas, sehingga sering kali menghadapi permasalahan dalam kegiatan operasionalnya. Penelitian ini menghasilkan Sistem Informasi cuti Pegawai Pada Kantor Sekretariat DPRD Kota Jayapura yang menggunakan metode analisis PIECES, melakukan perancangan menggunakan metode Unified Modelling Language (UML), menggunakan metode pengembangan Waterfall dan metode pengujian Black Box.
Pengembangan Sistem Pendukung Keputusan Menggunakan Pendekatan PIPRECIA-S dan ARAS untuk Pemilihan Wireless Repeater Sah, Andrian; Tanniewa, Adam M.
Bulletin of Data Science Vol 4 No 1 (2024): October 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v4i1.6368

Abstract

A wireless repeater is one of the solutions to extend signal range and reduce dead spot areas. However, selecting the right device often poses challenges for users due to the variety of products available in the market, each with differing specifications, performance, and prices. This study aims to develop a decision support system (DSS) based on the PIPRECIA-S and Additive Ratio Assessment (ARAS) methods. The PIPRECIA-S method is used to determine criterion weights in a structured manner, while the ARAS method evaluates alternatives based on their relative utility. The study resulted in a web-based application designed to enable users to access and manage data anytime and anywhere. A case study demonstrated that TP-Link TL-WA850RE (A4) ranked first with a score of 0.9395, followed by Prolink N300 (A3) with a score of 0.8571, Mercusys MW300RE (A1) with a score of 0.7770, and Tenda A9 (A2) in the last position with a score of 0.7141. The system's calculation results were consistent with manual calculations, proving the system's reliability and validity in providing recommendations. System testing using the black-box testing method showed that all features functioned as specified, including data management, input evaluation, and alternative ranking calculations. This study contributes a systematic solution to assist users in selecting the most suitable wireless repeater for their needs, while also enhancing efficiency in the multi-criteria decision-making process.
Pengembangan Model Prediksi Diabetes Melitus Menggunakan Metode Stochastic Gradient Boosting Sah, Andrian; Niesa, Chaeroen; Damuri, Amat; Hasma, Nur Amalia
FORMAT Vol 14, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i1.002

Abstract

Diabetes mellitus is one of the global health issues with a continuously increasing prevalence. Its high prevalence significantly impacts economic burdens and healthcare systems, as it often leads to severe complications such as cardiovascular diseases and kidney failure. Therefore, early prediction and detection of diabetes mellitus are crucial in mitigating its adverse effects. Data mining and machine learning technologies offer innovative solutions for processing complex medical data, providing deeper insights, and supporting data-driven decision-making. This study aims to develop a diabetes mellitus prediction model using the Stochastic Gradient Boosting (SGB) algorithm. The model utilizes a dataset comprising clinical variables such as glucose levels, blood pressure, body mass index (BMI), and genetic history to identify diabetes risk. The results indicate that the developed prediction model demonstrates high performance across various dataset splitting ratios: 70:30, 80:20, and 90:10. The model achieved the highest accuracy of 95.50% at the 70:30 ratio, with an AUC (Area Under the Curve) value of 0.9862, showcasing its ability to effectively differentiate between positive (diabetes) and negative (non-diabetes) classes. At the 80:20 and 90:10 ratios, the model achieved accuracies of 92.75% and 92.31%, with AUC values of 0.9767 and 0.9777, respectively, indicating consistent performance. The model’s high accuracy is attributed to the iterative boosting approach in the SGB algorithm, which adaptively corrects prediction errors at each iteration. Additionally, regulatory mechanisms such as learning rate and subsampling help prevent overfitting, making the algorithm effective for datasets with complex patterns.
Pengembangan Sistem Pakar Diagnosis Jenis Stres Menggunakan Pendekatan Dempster-Shafer Theory Sah, Andrian; Heriyani, Nofitri; Jafar Rumandan, Rhaishudin; Lasiyono, M. Munawir
Journal of Computing and Informatics Research Vol 4 No 2 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v4i2.1941

Abstract

Stress is a psychological issue commonly experienced in society and can develop into more serious disorders if not properly addressed. However, access to professional services remains limited due to constraints such as time, cost, and unequal distribution of mental health professionals. Therefore, the objective of this study is to develop an expert system using a web-based Dempster-Shafer Theory (DST) approach capable of diagnosing stress types based on user-reported symptoms. DST enables the integration of various pieces of evidence to produce conclusions with measurable confidence levels. The system is equipped with functionality for managing symptom data, stress types, and the ability to provide diagnostic results accompanied by recommended solutions. Testing results demonstrated an accuracy level of 93.33%, placing this system in the "Good" category according to standard performance evaluation classifications. The implementation of DST has proven effective in managing data uncertainty and supporting confidence-based decision-making. This research contributes to the development of DST-based diagnostic technology that can be widely accessed via a web platform, providing a reliable alternative for early detection of stress types.
PELATIHAN OPTIMALISASI PENGOLAHAN DATA KESEHATAN DI PUSKESMAS KANDA Rasna, Rasna; Nurhayati, Siti; Sah, Andrian; Tonggiroh, Mursalim; Widiyantoro, Riandi; Prasetianingrum, Septyana
Batara Wisnu : Indonesian Journal of Community Services Vol. 5 No. 2 (2025): Batara Wisnu | Mei - Agustus 2025
Publisher : Gapenas Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53363/bw.v5i2.392

Abstract

Primary health care in Indonesia, especially in regions like Papua, faces major challenges in managing accurate, complete, and timely health data. At Puskesmas Kanda, data management is still done manually or semi-digitally using basic Microsoft Excel, which causes the recording and reporting process to be slow and error-prone. This condition has a negative impact on the quality of reports and data-based decision making by the management of the Puskesmas and the Health Office, contrary to the mandate of Permenkes No. 31 of 2019 concerning Health Information Systems. The purpose of this Community Service (PkM) activity is to increase the capacity of health workers at the Kanda Health Center in optimizing the use of Microsoft Excel for health data processing. The training provided included data validation techniques, the use of logical and statistical functions, the creation of visual graphs and dashboards, and the development of data recap templates that fit the real needs in the field. The results of the training showed significant improvement in participants' ability to manage and analyze health data efficiently. The evaluation showed a very high level of participant satisfaction with the benefits of the training (90%), the quality of the materials (89%), and the relevance to daily work needs (92%). With participatory learning methods and hands-on practice, the training successfully supported the digital transformation of health services.
Analisis Model Prediksi Penyakit Jantung Menggunakan Adaptive Boosting, Gradient Boosting, dan Extreme Gradient Boosting Sah, Andrian; Niesa, Chaeroen; Jafar, Rhaishudin Rumandan; Muharrom, Muhammad
Jurnal Ilmiah FIFO Vol 17, No 1 (2025)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2025.v17i1.006

Abstract

Deteksi dini penyakit jantung merupakan langkah penting untuk meningkatkan kualitas diagnosis dan perawatan pasien. Namun, metode prediksi manual yang sering digunakan tenaga medis memiliki keterbatasan dalam efisiensi waktu, akurasi, dan kemampuan menangani volume data yang besar. Dalam bidang kecerdasan buatan, algoritma machine learning seperti Adaptive Boosting (AdaBoost), Gradient Boosting, dan Extreme Gradient Boosting (XGBoost) menawarkan potensi untuk meningkatkan akurasi prediksi, terutama dalam mengatasi tantangan pada dataset kecil yang sering mengalami ketidakseimbangan kelas dan risiko overfitting. Penelitian ini bertujuan untuk menganalisis kinerja ketiga algoritma boosting tersebut dalam memprediksi penyakit jantung. Hasil penelitian menunjukkan bahwa XGBoost memberikan performa terbaik dengan akurasi sebesar 84.78% dan ROC-AUC 0.9410, menjadikannya algoritma paling efektif dalam menangani pola data yang kompleks. Gradient Boosting menjadi model paling efisien dengan waktu pelatihan tercepat, yaitu 0.3655 detik, dengan akurasi dan ROC-AUC yang kompetitif. Sementara itu, AdaBoost menunjukkan kelemahan dalam menangani ketidakseimbangan kelas tetapi tetap memberikan hasil yang baik untuk kelas mayoritas. Berdasarkan evaluasi precision, recall, dan F1-score, XGBoost direkomendasikan untuk aplikasi prediksi penyakit jantung, terutama dalam situasi yang memerlukan akurasi tinggi, sedangkan Gradient Boosting cocok untuk kebutuhan real-time.
Kombinasi Metode Rank Order Centroid dan Additive Ratio Assessment Untuk Pemilihan Aplikasi Manajemen Inventaris Tanniewa, Adam M; Sah, Andrian; Kurniawan, Robi; Prayogo, M Ari
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.6347

Abstract

Selecting an appropriate inventory management application is a challenge for business actors, especially SMEs, due to the variety of features, costs, and complexities offered. Manual selection is often carried out without a clear systematic approach and tends to be influenced by bias, resulting in suboptimal decisions. This study aims to integrate the Rank Order Centroid (ROC) and Additive Ratio Assessment (ARAS) approaches in developing a Decision Support System (DSS) to determine the best inventory management application. ROC is used to assign proportional weights to criteria based on priority ranking, while ARAS evaluates alternatives using these weights and relative utility values against the ideal solution. The developed system includes key features such as data management for criteria, alternatives, and values, as well as the ability to generate recommendations through alternative ranking. Based on a case study, the best alternative identified is Sortly: Inventory Simplified, with the highest utility score of 0.8627, followed by Housebook - Home Inventory (0.8528), inFlow Inventory (0.8336), and Inventory Stock Tracker (0.7056). Usability testing showed an average user acceptance rate of 91%, categorized as "Excellent". The main contribution of this research is the implementation of a practical and efficient combination of ROC and ARAS for selecting inventory management applications. The findings can be adopted by businesses to support more accurate and efficient decision-making.
Co-Authors Andi ilham, Andi Andika Putra Chaeroen Niesa Damuri, Amat Hakim, Jamaludin Heriyani, Nofitri Jafar Rumandan, Rhaishudin Jafar, Rhaishudin Rumandan Jusmawati Jusmawati, Jusmawati Lasiyono, M. Munawir M. Ari Prayogo Matdoan, Irjii Muhammad Muharrom Muhammad Riandi Widiyantoro Nur Amalia Hasma Rasna, Rasna Robi Kurniawan Robo, Salahudin Sahrul Ponto Septilia, Tiara Indah Septyana Prasetianingrum Sidarmawan, Andri Tri Siti Nurhayati Suharto, Emilda Sukriyan, Mohamad Maulidin Tanniewa, Adam M Tanniewa, Adam M. Tonggiroh, Mursalim Widiyantoro, Muh. Riandi