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All Journal Jurnal Sarjana Teknik Informatika IJIIS: International Journal of Informatics and Information Systems Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen
Prasetio, Agung Budi
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Computer Science & IT Decision Sciences, Operations Research & Management

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ANALISIS TINGKAT KEMATANGAN SISTEM INFORMASI MANAJEMEN AKADEMIK DAN KEMAHASISWAAN IAIN PALANGKA RAYA MENGGUNAKAN COBIT 5 Pamungkas, Sapto; Kusrini, Kusrini; Prasetio, Agung Budi
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 11 No 2 (2021): September 2021
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (266.924 KB) | DOI: 10.33020/saintekom.v11i2.212

Abstract

The use of Information Technology (IT) at a university is needed at this time. There are many advantages in using IT and have a good impact on a university. The use of IT in a university has different roles according to their needs. The utilization of IT in Higher Education theoretically provides appropriate and efficient administration systems (Fernandes Andry and Christianto, 2018). IAIN Palangka Raya is one of the universities that has implemented IT, in this case, the academic and student management information system. The information system at IAIN Palangka Raya is one of the IT applications that is often used to carry out IT governance, however, there are several problems that occur in the information system, including features or tools that are not yet functional. For this reason, the researcher will analyze the information system to get the level of maturity and recommendations so that IAIN Palangka Raya can follow up on the results of this analysis and improve it to get the goal of good information system governance. In this study, the COBIT 5 framework is used with a focus on the EDM domain (Evaluate, Direct, and Monitor). The results of the analysis showed that the capability level was 2.86 (established), which means that the process was carried out, achieved goals, and well managed. With a balance value of 0.96, which means that the expected distance with the current distance is not too far so that features or tools that are not yet functioning are functional. So that the academic and student management information system of IAIN Palangka Raya runs according to its goals and is better.
Segmentasi Luka Diabetes Menggunakan Algoritma Contour Image Processing Roshandri, Wien Fitrian; Utami, Ema; Prasetio, Agung Budi
Jurnal Sarjana Teknik Informatika Vol. 9 No. 2 (2021): Juni
Publisher : Program Studi Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v9i2.20226

Abstract

Pengukuran luas luka pada penderita diabetes masih menggunakan cara manual dengan penggaris luka. Sedangkan penggaris yang ditempelkan keluka akan menjadi contaminated agent yang dapat menularkan infeksi pada penderita lain. Metode pengukuran digital diperlukan agar masalah tersebut bisa terselesaikan. Tetapi untuk memperjelas batas antara luka dan kulit diperlukan ketelitian dan akurasi yang tinggi. Untuk itu diperlukan metode pencitraan yang dapat melakukan segmentasi antara batas luka dan kulit paada pasien diabetes berbasis digital yang dinamakan digital planimetry. Penelitian ini menggunakan algoritma contour image processing dari nilai hue, saturation, value (HSV).  Kemudian melakukan iterasi sebanyak 5 kali dan filter gamma. Sehingga mendapatkan hasil segmentasi luka. Kesimpulan akhir dari penelitian ini adalah segementasi dengan metode ini belum dapat melakukan segementasi luka dengan baik dan diperlukan tambahan nilai masking yang lebih luas, akan tetapi hasil iterasi ke 5 mendapatkan error terkecil yaitu 0.002%. Pencitraan digital yang dilakukan dalam penelitian ini dapat dikembangkan untuk menjadi alat ukur luas luka pasien diabetes berbasis digital.
Interpretable Product Recommendation through Association Rule Mining: An Apriori-Based Analysis on Retail Transaction Data Prasetio, Agung Budi; Aboobaider, Burhanuddin bin Mohd; Ahmad, Asmala bin
International Journal of Informatics and Information Systems Vol 8, No 2: March 2025
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v8i2.252

Abstract

The rapid growth of e-commerce has generated vast amounts of transactional data, creating opportunities for data-driven decision-making in retail environments. This study presents an interpretable product recommendation approach based on association rule mining using the Apriori algorithm. Unlike complex black-box recommender models, the proposed method emphasizes transparency and explainability in identifying purchasing relationships. The Groceries dataset comprising 38,765 transactions was analyzed to discover frequent itemsets and generate actionable association rules. After applying minimum thresholds of 0.02 for support and 0.4 for confidence, a total of 67 frequent itemsets and 45 strong rules were obtained. The rule {whole milk, sausage, rolls/buns} → {yogurt} achieved the highest lift value of 1.66, revealing meaningful co-purchasing behavior. Visualization tools, including heatmaps and network graphs, were employed to illustrate rule strength and product interconnections, facilitating business interpretation. The findings demonstrate that interpretable rule-based recommendations can effectively support product bundling, cross-selling, and retail layout strategies. This study highlights the continuing relevance of Apriori in creating transparent, data-driven insights and proposes future integration with hybrid models to address personalization and scalability challenges in modern recommendation systems.
Co-Authors Aboobaider, Burhanuddin bin Mohd Ahmad, Asmala bin Ema Utami Kusrini, Kusrini Pamungkas, Sapto Roshandri, Wien Fitrian