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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) SITEKIN: Jurnal Sains, Teknologi dan Industri JUSIFO : Jurnal Sistem Informasi Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Sistemasi: Jurnal Sistem Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Inotera JURIKOM (Jurnal Riset Komputer) Jurnal Sistem Cerdas Building of Informatics, Technology and Science Jurnal Sistem Informasi dan Informatika (SIMIKA) Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Indonesian Journal of Data and Science Jurnal Teknik Informatika (JUTIF) KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Indonesian Journal of Informatic Research and Software Engineering Malcom: Indonesian Journal of Machine Learning and Computer Science CONSEN: Indonesian Journal of Community Services and Engagement Journal of Informatics, Electrical and Electronics Engineering The Indonesian Journal of Computer Science INOVTEK Polbeng - Seri Informatika Jurnal Ilmu Komputer dan Teknik Informatika Jurnal Pengabdian Masyarakat Berdampak
Inggih Permana
Universitas Islam Negeri Sultan Syarif Kasim Riau
Religion Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Inggris Alfaridzi, Gemma Tahmid; Nur Salisah, Febi; Permana, Inggih
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.765

Abstract

Pharmacy sales transaction data contain valuable information on customer purchasing patterns; however, in practice, such data are often used merely as operational records, making relationships between purchased drugs difficult to identify. This study analyzes drug purchasing patterns using the Apriori and FP-Growth algorithms based on sales transaction data from Apotek Gadi Lamba Condet for the period January to June 2025. The transaction data were processed through data cleaning, drug name standardization, and transformation into transaction format, resulting in 7,038 transactions with 1,495 drug items. Association rule mining was performed using a minimum support of 0.01 and a minimum confidence of 0.17. The results show that the Apriori and FP-Growth algorithms generate ten identical association rules with the same support, confidence, and lift values, and all rules have lift values greater than one. Paracetamol 500 MG emerges as the most frequently involved drug in the association rules. These findings demonstrate that, for medium-scale pharmacy transaction datasets, Apriori and FP-Growth have equivalent capability in identifying drug purchasing patterns, with the primary difference lying in computational efficiency rather than the quality of the generated patterns.
Machine Learning Based Prediction of Health Risks in Pregnant Women Devi, Rahma; Inggih Permana; Novita, Rice; Febi Nur Salisah
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.766

Abstract

Pregnancy is an important phase that requires optimal health monitoring to prevent complications that are risky for both mother and fetus. The high maternal mortality rate in Indonesia emphasizes the importance of early detection of pregnancy risks. The use of machine learning offers an effective predictive approach to quickly and accurately identify pregnancy risks. This study aims to compare the performance of five machine learning algorithms, namely Logistic Regression, Decision Tree C4.5, Random Forest, Support Vector Machine, and Naive Bayes, using the Maternal Health Risk Dataset. The hold-out validation method with data sharing of 80% training data and 20% test data was used in this study. Model evaluation is conducted based on accuracy, precision, recall, and F1-score metrics. The results showed that Random Forest had the best performance with an accuracy of 93%, followed by Decision Tree at 93%, SVM at 82%, Logistic Regression at 76%, and Naive Bayes at 72%. Thus, Random Forest is rated as the most optimal algorithm in predicting pregnancy risk and potentially supporting the development of decision support systems for health workers. This research is expected to be the basis for the development of a machine learning-based decision support system to increase the effectiveness of health services for pregnant women.
Co-Authors Aditya Nugraha Yesa Agus Buono Ahsyar, Tengku Khairil Al Kiramy, Razanul Alfakhri, Rezky Alfaridzi, Gemma Tahmid Aliya, Rahma Andi Darlianto Andriyani, Dwi Ratna Anggi Widya Atma Nugraha Anggia Anfina Anisah Fitri Anjani, Yulia Merry Annisa Ramadhani Aprijon Arif Marsal Arif Marsal Arif Marsal Arifah Fadhila Andaranti Arifin, Abdullah Aufa Zahrani Putri Aulia Dina Bib Paruhum Silalahi Chinthia, Maulidania Mediawati Dedi Pramana Dessi Cahyanti Detha Yurisna Detha Yurisna Devi, Rahma Dzul Asfi Warraihan Eka Pandu Cynthia Eki Saputra Eki Saputra Endah Purnamasari Esis Srikanti Fadhilah Syafria Fadil Rahmat Andini Farahdina Risky Ramadani Febi Nur Salisah Febi Nur Salisah Fiki Fikri, M. Hayatul Fitriah, Ma’idatul Fitriah, Ma’idatul Fitriani Muttakin Fitriani Muttakin Fitriani Muttakin Gathot Hanyokro Kusuma Gurning, Umairah Rizkya Hafiz Aryan Siregar Hasbi Sidiq Arfajsyah Hendri, Desvita Hilda Mutiara Nasution Husaini, Fahri Idria Maita Idria Idriani R, Nova Ikhsani, Yulia Imam Muttaqin Intan, Sofia Fulvi Ismail Marzuki Jazma, Muhammad Jazman , Muhammad Jazman, Muhammad Kusuma, Gathot Hanyokro M Afdal M Afdal M Zaky Ramadhan Z M. Afdal M. Afdal M. Afdal M. Afdal M. Afdal Maulana, Rizki Azli Megawati Megawati - Mona Fronita, Mona Muhammad Afdal Muhammad Fikry Muhammad Jazman Muhammad Jazman Muhammad Jazman Muhammad Naufal, Muhammad Muhammad Zacky Raditya Mukmin Siregar Mundzir, Mediantiwi Rahmawita Munzir, Medyantiwi Rahmawita Mustakim Mustakim Mustakim Mustakim Mustakim Mustakim Mutia, Risma Muttakin, Fitriani Nabillah, Putri Nardialis Nardialis Nasution, Nur Shabrina Naufal Fikri, R. Adlian Negara, Benny Sukma Nesdi Evrilyan Rozanda Nesdi Evrilyan Rozanda Nisa', Sayyidatun Norhavina Norhavina Nunik Noviana Kurniawati Nurainun Nurainun Nuraisyah Nuraisyah Nurfadilla, Nadia Nurkholis Nurkholis nursalisah, febi Octavia, Sania Fitri Pratama, Arya Yendri Priady, Muhamad Ilham Pristiawati, Andani Putri Puput Iswandi Putra, Moh Azlan Shah Putra, Tandra Adiyatma Rahman, Eman Rahmawita M, Medyantiwi Rangga Arief Putra Rayean, Rival Valentino Restu Ramadhan Ria Agustina Rice Novita Rice Novita Rizka Fitri Yansi Rizki Pratama Putra Agri Rozanda, Nesdi Evrilyan Sabillah, Dian Ayu Salisah, Pebi Nur Sania Fitri Octavia Sanusi Shir Li Wang Siti Monalisa Sofia Fulvi Intan Susanti, Pingki Muliya Tasya Marzuqah Tengku Khairil Ahsyar Triningsih, Elsa Tshamaroh, Muthia Uci Indah Sari Ula, Walid Alma Vicky Salsadilla Wenda, Alex Wido Purnama Winda Wahyuti Windy Amelia Putri Wira Mulia, M. Roid Yusmar Yusmar Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly