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SISTEM ESTIMASI BIAYA DAN SUMBER DAYA PROYEK PERANGKAT LUNAK BERBASIS COCOMO II MENGGUNAKAN NEURAL NETWORK Irawan, Joko; Chrisnanto, Yulison Herry; Maspupah, Asri
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 3 No. 1 (2019): PROSIDING SEMNAS INOTEK Ke-III Tahun 2019
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v3i1.519

Abstract

Estimasi biaya dan sumber daya perangkat lunak merupakan bagian tak terpisahkan dari proyek perangkat lunak. Saat melakukan estimasi sering menghadapi dua permasalahan yaitu estimasi berlebihan dan estimasi yang kurang. Estimasi berlebihan akan menimbulkan penambahan alokasi biaya dan sumber daya, sedangkan estimasi yang kurang akan mengurangi kualitas produk. Untuk mengantisipasi terjadinya kesalahan estimasi maka dikembangkan suatu metode untuk mengestimasi biaya dan sumber daya proyek perangkat lunak berbasis Constructive Cost Model 1997 (COCOMO II) dengan menggunakan Algoritma Backpropagation Neural Network. COCOMO II menghasilkan nilai estimasi dari data latih, sedangkan Algoritma Backpropagation digunakan untuk menghasilkan nilai estimasi data uji. Hasil dari perhitungan Backpropagation dilakukan penggabungan dengan model COCOMO II sehingga menghasilkan estimasi biaya dan sumber daya proyek perangkat lunak. Jumlah data yang digunakan dalam penelitian ini sebanyak 60 data. Model yang dikembangkan ini dievaluasi menggunakan PRED. Berdasarkan hasil dari penelitian diperoleh bahwa penggunaan model COCOMO II, dan algoritma Backpropagation memiliki kedekatan dalam melakukan estimasi biaya, dan sumber daya proyek perangkat lunak dengan nilai PRED sebesar 75%. Kesimpulan dari penelitian ini model COCOMO II, dan algoritma Backpropagation dapat mengurangi tingkat kegagalan dalam proyek perangkat lunak, berdasarkan estimasi biaya, dan sumber daya.
Comparative analysis of optimization methods for cut order planning in apparel manufacturing Yulison Herry Chrisnanto; Julian Evan Chrisnanto; Jeremia Oktavian
Jurnal Sistem dan Manajemen Industri Vol. 9 No. 2 (2025): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v9i2.10502

Abstract

This study seeks to address the complicated optimization challenge inherent in cut order planning (COP) in the clothing manufacturing business, emphasising fabric consumption, computational economy, and production accuracy. Three optimization approaches were compared: adaptive heuristic scoring optimizer (AHOPS), hybrid metaheuristic optimization with simulated annealing (HIMOSA), and gradient-based penalty-driven (GBPD). The results show that the GBPD method achieved the highest fabric utilization (87.13%), the fewest amount of fabric layers (12), and the maximum computational efficiency (0.022 seconds), significantly outperforming both conventional methods and alternative advanced approaches. AHOPS and HIMOSA, on the other hand, required more layers (15) and produced lower fabric utilization (around 69.70%), with HIMOSA demonstrating noticeably greater computational needs (0.527 seconds). The adaptive heuristic scoring mechanism and the combination of gradient descent and machine learning predictions, which successfully handled the combinatorial difficulties of COP, are responsible for GBPD's exceptional performance. These results offer useful information to manufacturers looking for scalable, effective optimization solutions. They also point to potential avenues for future research, such as extending the applicability of GBPD to more intricate production scenarios and further honing machine learning models for increased efficiency and adaptability.
Assessment of the Level of Software Development Using CMMI-Dev 1.3 on the Unjani Official Web Ghaniiy, Gheral Naza; Chrisnanto, Yulison Herry; Abdillah, Gunawan
Bincang Sains dan Teknologi Vol. 4 No. 03 (2025): Bincang Sains dan Teknologi
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/bst.v4i03.1213

Abstract

UNJANI website ranked 186 in Webometric ranking. Webometric is a ranking system of universities around the world conducted by Cybermetrics Labs which is useful to determine the ranking in terms of the level of performance indicators of universities, which include Visibility, Openness, Excellence. The purpose of this study was to assess the level of maturity of the software development process on the UNJANI website using CMMI Dev 1.3. This study uses quantitative methods, with a survey approach to the person in charge and manager of the UNJANI website. Quantitative research is a way to obtain research data measured using tools such as surveys, questionnaires, or experiments, and analysed with statistical methods to find certain patterns, relationships, or trends. The results of this study found that out of 7 CMMI Dev.1.3 process areas, some areas are in accordance with the standard process of making the UNJANI website and some process areas are not in accordance with the CMMI Dev 1.3 framework. The maturity level of the UNJANI website is in the category of partially implemented in most process areas, with the highest GAP (50%) in Configuration Management (CM) and the lowest GAP (30%) in Project Monitoring and Control (PMC). The conclusion of this research reveals that UNJANI website still needs improvement in configuration management, change recording, and feature quality evaluation before release.
Co-Authors Adam, Marcellino Ade Kania Ningsih Ade Kania Ningsih Ade Kania Ningsih, Ade Kania Aditya Prakasa Adryansyah Adryansyah Agung Wahana Agus Komarudin Andhika Karulyana Febrian Asep Id Hadianna Asep Saepul Ridwan Ashaury, Herdi Asri Maspupah Azzahra, Cynthia Nur Bania Amburika Benedictus Benny Sihotang Cahyaningrum, Amellia Fahezha Cecep M Zakariya Darmawan, Raja Dewi, Liony Puspita Didik Garbian Nugroho Drl, Indra Raja Eina, Muhammad Fikri eka rahmawati Emia Rosta Br. Sebayang Fadilah, Rifal Fahmy Akhmad Firdaus Faiza Renaldi, Faiza Fajar Tresnawiguna Fajri Rakhmat Umbara Farhan Naufal Febry Ramadhan Fitaloka, Intan Fuji Astari, Dhea Gerliandeva, Alfin Ghaniiy, Gheral Naza Gita Mahesa Gunawan Abdillah Gunawan Abdillah Gunawan Abdillah Gunawan Abdillah, Gunawan Gunawan Abdullah Gunawan Gunawan Hadiana, Asep Id Haikal, Ahmed Hanafi, Willy Hanief Kuswanto, Muhammad Rafi Hendro Pudjiantoro, Tacbir Herdi Ashaury Herlina Napitupulu Herlinda Padillah Ibadirachman, Rifqi Karunia Id Hadiana , Asep Irawan, Joko Irma Santikarama Jeremia Oktavian Julian Evan Chrisnanto Julian Evan Chrisnanto Kamal, Angga Mochamad Kania Ningsih, Ade Kasyidi, Fatan Kharisma Jevi Shafira Sepyanto Kholidah Syaidah Kukuh Yulion Setia Prakoso Luthfia Oktasari Mahendra, Lucky Syahroni Melina Melina Melina Mubarak, Muhammad Munzir Rizkya Muhamad Afnan, Zikri Muhammad Rendy Raihan Mukti Kinani Mulianti, Adhani Musa Asyari Hidayat Jati Nabilla, Ulya Naufal, Farhan Nida Ulhasanah Norizan Mohamed Permana, Hary Permatasari, Nissa Aulia Prawira, Angga Puspita Nurul Sabrina Puspita Nurul Sabrina Puspita Nurul Sabrina Puspita Nurul Sabrina Puspita Nurul Sabrina Puspita Nurul Sabrina, Puspita Nurul Puspo Dewi Dirgantari Putri Alifianti Wiyono, Tiara Putri Eka Prakasawati Raflialdy Raksanagara Rahandanu Rachmat Raja Darmawan Razaki, Adam Rd Muhammad Alfajri Reza Noviandi Rezki Yuniarti Ridwan Ilyas RIDWAN INDRANSYAH Riyadi, Saiful Faris Rizal Dwiwahyu Pribadi Santikarama, Irma Santoso, Enrico Budi Sepyanto, Kharisma Jevi Shafira Siska Vadilah Sukono Sukono Sumantri, Fithra Aditya Taufiq Akbar Herawan Teguh Munawar Ahmad Tiara Rahmawati Valentina Adimurti Kusumaningtyas Wahyu Pratama, Raka Wawan Setiawan Widinastia, Audila Gumanty Widiyantoro, Widiyantoro Wildah Fatma Lestari Wina Witanti Wisnu Uriawan, Wisnu Yosia Oktavian Pailan Zizilia, Regitha