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All Journal Justek : Jurnal Sains Dan Teknologi Insearch: Information System Research Journal Knowbase : International Journal of Knowledge in Database The Indonesian Journal of Computer Science
Lizar, Yaslinda
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Social Sciences Other

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Penerapan Metode CPM dan PERT pada Sistem Informasi Manajemen Proyek Pembuatan Website Akreditasi dan Mutu Fakultas Sains dan Teknologi UIN Imam Bonjol Padang Lizar, Yaslinda; Rosmita, Ummi
Justek : Jurnal Sains dan Teknologi Vol 7, No 1 (2024): Maret
Publisher : Unversitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/justek.v7i1.21455

Abstract

Abstract: The Faculty of Science and Technology of UIN Imam Bonjol Padang is preparing for institutional and study program accreditation. One of the requirements is the provision of a complete accreditation and quality website. To ensure timely completion, the website project needs careful planning. This research applies the Critical Path Method (CPM) and Program Evaluation and Review Technique (PERT) to management information systems for planning and scheduling accreditation website projects. CPM is used to determine the set of critical project activities while PERT calculates the probabilistic project duration. The application results show that the information system is able to help the accreditation website project management to be completed according to the deadline. In addition to planning and scheduling features, the system is equipped with a module for monitoring and evaluating project achievements. By applying CPM and PERT to the project management information system, project planning and control become more directed and reliable.Abstrak: Fakultas Sains dan Teknologi UIN Imam Bonjol Padang tengah mempersiapkan akreditasi institusi dan program studi. Salah satu persyaratan adalah penyediaan website akreditasi dan mutu yang lengkap. Untuk memastikan pengerjaan tepat waktu, proyek website perlu perencanaan yang matang. Penelitian ini menerapkan metode Critical Path Method (CPM) dan Program Evaluation and Review Technique (PERT) pada sistem informasi manajemen untuk perencanaan dan penjadwalan proyek website akreditasi. CPM digunakan menentukan rangkaian aktivitas kritis proyek sedangkan PERT melakukan perhitungan durasi proyek probabilistik. Hasil penerapan menunjukkan sistem informasi mampu membantu manajemen proyek website akreditasi agar selesai sesuai tenggat waktu. Selain fitur perencanaan dan penjadwalan, sistem dilengkapi modul monitoring dan evaluasi capaian proyek. Dengan menerapkan CPM dan PERT pada sistem informasi manajemen proyek, perencanaan dan pengendalian proyek menjadi lebih terarah dan terpercaya.
Pengambilan Keputusan Pemilihan Guru Terbaik Menggunakan Metode Analytical Hierachy Process (AHP) Lizar, Yaslinda; Adli, Imam
Insearch: Information System Research Journal Vol 3, No 02 (2023): Insearch (Information System Research) Journal
Publisher : Fakultas Sains dan Teknologi UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/isrj.v3i02.6831

Abstract

Penting bagi sekolah untuk menyediakan guru terbaik untuk menungkatkan kinerja sekolah. Selama ini proses pemilihan guru terbaik diseleksi berdasarkan rasa suka tidak suka saja, kurangnya laporan penilaian guru juga mengurangi motivasi dalam meningkatkan kinerja. Tujuan penelitian ini untuk membangun sebuah DSS (Decision Support System) untuk pemilihan guru terbaik, yang akan menghasilkan penilaian yang lebih objektif dan meningkatkan kualitas pengajaran di sekolah. Metode Analytical Hierarchy Process (AHP) akan digunakan dalam penelitian ini dengan beberapa kriteria tambahan dalam menentukan bobot, seperti orientasi pelayanan, integritas, komitmen, kedisiplinan, dan kerjasama, untuk menentukan bobot penilaian. Hasil penelitian menghasilkan sebuah sistem DSS untuk pemilihan guru terbaik, untuk meminimalisir kesalahan penilain dalam metode yang digunakan. Hasil dari metode pemilihan ini dapat juga menjadi motivasi dan bahan pembelajaran untuk para guru agar dapat bisa meningkatkan kualitas kinerja sehingga bisa memenuhi kategori guru terbaik
Data Mining Analysis to Predict Student Skills Using Naïve Bayes Method Lizar, Yaslinda; Firrizqi, Alya Sahira; Guci, Asriwan; Sunadi, Joko
Knowbase : International Journal of Knowledge in Database Vol. 3 No. 2 (2023): December 2023
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v3i2.7481

Abstract

The possession of specific skills by students not only has a positive impact on the students themselves but also on the Study Program within a Faculty and the University as a whole. However, Study Programs sometimes face difficulties in determining the skills of numerous students even after they have completed 7 semesters of study. Therefore, a method to extract available data in order to determine student skills quickly and accurately is essential. This research aims to apply a data mining method to predict student skills in the Information Systems Study Program at UIN Imam Bonjol Padang. The study focuses solely on predicting student skills in the fields of data processing and programming. The method employed in this data mining analysis is the Naïve Bayes method. Data will be collected from student course grades related to data processing and programming. The data will be processed using an application and subsequently tested using a Confusion Matrix. The research results indicate that predicting the determination of student skills in the Information Systems Study Program at UIN Imam Bonjol can be achieved using the Naïve Bayes algorithm, which yielded a Naïve Bayes model accuracy of 93%, precision of 81%, and recall of 81%. The obtained model can be implemented in the form of an application to determine decision-making strategies for students.
Tren Global Penelitian Tentang Digital Twin: Analisis Bibliometrik Lizar, Yaslinda; Mal Novizam, Defa; Butar-Butar, Mhd Sufiananda; Guci, Asriwan
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3513

Abstract

Penelitian ini bertujuan untuk menganalisis perkembangan publikasi ilmiah bidang digital twin. Metode penelitian adalah kajian bibliometrik terhadap 16.504 artikel jurnal internasional terindeks Scopus periode 2014-2023. Hasil menunjukkan terjadi peningkatan publikasi yang signifikan dalam satu dekade terakhir, didominasi oleh Tiongkok, Jerman, Amerika Serikat, Inggris dan Italia. Sebagian besar publikasi adalah conference papers dan articles di bidang Engineering dan Computer Science. Berdasarkan analisis kata kunci, tema utama meliputi smart systems, machine learning, cloud computing, augmented reality, automation, dan big data. Kesimpulannya, antusiasme peneliti terhadap digital twin tercermin dari lonjakan publikasi global. Hal ini diperkirakan mendorong perluasan riset digital twin ke berbagai disiplin di masa depan.
Tren Riset Sistem Informasi Dalam Publikasi Internasional: Analisis Bibliometrik Menggunakan VosVIEWER Lizar, Yaslinda; Siregar, Elfi Ramadani; Rosmita, Ummi; Silvia Ariati; Masyaratul Hayati
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.3615

Abstract

Sistem informasi pada era ini sedang sangat hangat diperbincangkan dalam dunia IT. Tentunya hal ini akan berdampak pada peningkatan minat para peneliti untuk mempelajari serta mendalami pemahaman terkait sistem informasi dalam kurun waktu 5 tahun terakhir. Jurnal ini dibuat dengan maksud untuk memetakan tren penelitian sistem informasi melalui kajian bibliometrik terhadap 20.000 artikel jurnal internasional terindeks Scopus dalam jangka tahun 2019-2023. Analisis kejadian bersama kata kunci dengan VOSviewer mengidentifikasikan 4 kelompok utama dalam penelitian sistem informasi ini. Cluster dengan kepadatan tertinggi pada topik gis, patient, theory, dan outcome. Dan topik seperti magnesium, annual percent change, lightgbm, postoperative length tidak terlalu banyak diteliti. Pemetaan ini diharapkan dapat memberikan pengetahuan tentang arah penelitian sistem informasi di masa depan, terutama pada topik-topik yang masih sedikit dieksplorasi.
Data Mining Analysis to Predict Student Skills Using Naïve Bayes Method Lizar, Yaslinda; Firrizqi, Alya Sahira; Guci, Asriwan; Sunadi, Joko
Knowbase : International Journal of Knowledge in Database Vol. 3 No. 2 (2023): December 2023
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v3i2.7481

Abstract

The possession of specific skills by students not only has a positive impact on the students themselves but also on the Study Program within a Faculty and the University as a whole. However, Study Programs sometimes face difficulties in determining the skills of numerous students even after they have completed 7 semesters of study. Therefore, a method to extract available data in order to determine student skills quickly and accurately is essential. This research aims to apply a data mining method to predict student skills in the Information Systems Study Program at UIN Imam Bonjol Padang. The study focuses solely on predicting student skills in the fields of data processing and programming. The method employed in this data mining analysis is the Naïve Bayes method. Data will be collected from student course grades related to data processing and programming. The data will be processed using an application and subsequently tested using a Confusion Matrix. The research results indicate that predicting the determination of student skills in the Information Systems Study Program at UIN Imam Bonjol can be achieved using the Naïve Bayes algorithm, which yielded a Naïve Bayes model accuracy of 93%, precision of 81%, and recall of 81%. The obtained model can be implemented in the form of an application to determine decision-making strategies for students.
Co-Authors Adli, Imam Butar-Butar, Mhd Sufiananda Firrizqi, Alya Sahira Guci, Asriwan Mal Novizam, Defa Masyaratul Hayati Rosmita, Ummi Silvia Ariati Siregar, Elfi Ramadani Sunadi, Joko