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All Journal Teknika Techno.Com: Jurnal Teknologi Informasi Jurnal Informatika PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING IT JOURNAL RESEARCH AND DEVELOPMENT Indonesian Journal of Artificial Intelligence and Data Mining JRST (Jurnal Riset Sains dan Teknologi) Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jusikom : Jurnal Sistem Komputer Musirawas ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) Jurnal Teknologi Sistem Informasi dan Aplikasi JSiI (Jurnal Sistem Informasi) IJISTECH (International Journal Of Information System & Technology) Journal on Education JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknik Elektro dan Komputer TRIAC Jurnal Riset Informatika INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi METIK JURNAL Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Jurnal Mantik JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Journal of Information Systems and Informatics INFOKUM U-NET Jurnal Teknik Informatika Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Artificial Intelligence and Robotics (IJAIR) Jurnal Pendidikan dan Teknologi Indonesia Journal La Multiapp KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Info Sains : Informatika dan Sains Jurnal IPTEK Bagi Masyarakat Journal of Computer Science and Informatics Engineering Journal Of Human And Education (JAHE) Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram SWARNA International Conference on Sciences Development and Technology STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Innovative: Journal Of Social Science Research Information Technology Education Journal Jurnal Pengabdian Masyarakat VISA: Journal of Vision and Ideas Bigint Computing Journal Cosmic Jurnal Teknik
Muhammad Siddik Hasibuan
Universitas Islam Negeri Sumatera Utara
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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SISTEM PAKAR DIAGNOSIS AWAL PENYAKIT FARINGITIS DAN LARINGITIS MENGGUNAKAN METODE FORWARD CHAINING DAN CERTAINTY FACTOR Muhammad Siddik Hasibuan; Triase Triase; Dio Wahyu Habibi Hutabarat
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 7 No. 3 (2024): August 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i3.2144

Abstract

Ada banyak berbagai macam penyakit pernapasan kronis, diantaranya adalah penyakit faringitis dan laringitis yang sering dikaitkan dalam dunia medis karena masih dalam ruang lingkup radang tenggorokan. Faringitis dan laringitis adalah dua jenis peradangan yang terjadi pada saluran pernapasan bagian atas. Faringitis terjadi ketika tenggorokan mengalami peradangan, sementara laringitis terjadi ketika pita suara mengalami peradangan. Untuk melakukan diagnosis pada penyakit faringitis dan laringitis pasti harus bertemu seorang dokter secara langsung, oleh karena itu penulis membuat penelitian agar mempermudah pasien yang datang ke klinik dan dapat membantu pasien agar memahami dan mengidentifikasi gejala awal yang sedang diderita serta dapat membantu pasien apabila terkendala oleh waktu untuk bertemu seorang dokter. Penerapan aplikasi sistem pakar ini menggunakan metode forward chaining untuk melakukan diagnosis penyakit sesuai dengan aturan serta ketentuan yang telah ditetapkan oleh pakar langsung dan juga menggunakan metode certainty factor untuk menyelesaikan perhitungan persentase nilai tingkat keyakinan hasil penyakit yang didiagnosis, dengan menggunakan bobot pakar yang telah diberikan oleh pakar. Tingkat keyakinannya diantaranya yaitu, Tidak Tahu, Mungkin Tidak, Mungkin Iya, Kemungkinan Besar, Hampir Pasti, Pasti. Maka aplikasi dapat menyimpulkan hasil nilai persentase penyakit tersebut. Aplikasi sistem pakar ini dibangun berbasis web dapat mempermudah penggunaan, serta mempermudah pakar untuk mengubah atau mengedit secara langsung.
PENERAPAN ALGORITMA K-MEANS CLUSTERING UNTUK PENCATATAN PENCAPAIAN KINERJA KARYAWAN Imam Utomo; Ilka Zufria; Muhammad Siddik Hasibuan
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 7 No. 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2311

Abstract

Abstract: This study aims to classify employee performance using the K-Means method. Employee data includes total orders, average order processing time, customer satisfaction, delivery errors, absences, successful projects, and training attended. The clustering process begins with calculating the initial centroid distance and grouping the data based on the nearest distance, repeated until there are no significant changes in the centroid positions. Clustering results are displayed in the "Result" feature with three performance categories: Excellent (C1), Satisfactory (C2), and Poor (C3). The final centroids are as follows: Centroid 1 (C1) = [0.53, 0.40, 0.64, 0.33, 0.31, 0.55, 0.50], Centroid 2 (C2) = [0.11, 0.82, 0.24, 0.78, 0.75, 0.13, 0.00], and Centroid 3 (C3) = [0.89, 0.12, 0.93, 0.11, 0.08, 0.87, 0.83]. The analysis shows 185 employees in cluster C1 (Excellent), 67 employees in cluster C2 (Satisfactory), and 383 employees in cluster C3 (Poor). These results can be used as a basis for managerial decision-making, such as training, promotion, or other actions to improve productivity and efficiency. The K-Means method has proven effective for employee performance clustering and can be well integrated into employee management systems. It is recommended to conduct a longitudinal study to observe changes in employee performance over time and measure the effectiveness of managerial interventions based on these clustering results. Keywords: K-Means Clustering, Employee Performance, Data Analysis, Performance                  Categories Abstrak: Penelitian ini bertujuan mengelompokkan kinerja karyawan import bagian opersional menggunakan metode K-Means. Data karyawan meliputi total order, rata-rata waktu proses order, kepuasan pelanggan, kesalahan pengiriman, absensi, proyek sukses, dan pelatihan yang diikuti. Proses clustering dimulai dengan menghitung jarak centroid awal dan mengelompokkan data berdasarkan jarak terdekat, diulang hingga tidak ada perubahan signifikan pada posisi centroid. Hasil clustering ditampilkan dalam fitur "Result" dengan tiga kategori kinerja: Baik (C1), Cukup (C2), dan Kurang (C3). Centroid akhir adalah sebagai berikut: Centroid 1 (C1) = [0.53, 0.40, 0.64, 0.33, 0.31, 0.55, 0.50], Centroid 2 (C2) = [0.11, 0.82, 0.24, 0.78, 0.75, 0.13, 0.00], dan Centroid 3 (C3) = [0.89, 0.12, 0.93, 0.11, 0.08, 0.87, 0.83]. Analisis menunjukkan 185 karyawan dalam cluster C1 (Baik), 67 karyawan dalam cluster C2 (Cukup), dan 383 karyawan dalam cluster C3 (Kurang). Hasil ini dapat dijadikan dasar untuk pengambilan keputusan manajerial, seperti pelatihan, promosi, atau tindakan lainnya yang meningkatkan produktivitas dan efisiensi. Metode K-Means terbukti efektif untuk pengelompokan kinerja karyawan dan dapat diintegrasikan dengan baik dalam sistem manajemen karyawan. Disarankan melakukan studi longitudinal untuk melihat perubahan kinerja karyawan dari waktu ke waktu dan mengukur efektivitas intervensi manajerial berdasarkan hasil clustering ini. Kata kunci: Pengelompokan K-Means, Kinerja Karyawan, Analisis Data, Kategori Kinerja  
PERBANDINGAN METODE AUTOREGRESIF INTEGRATED MOVING AVERAGE (ARIMA) DAN ALGORITMA MONTE CARLO UNTUK MEMPREDIKSI SUATU HARGA BAHAN POKOK M. Naufal Rangkuti; Yusuf Ramadhan Nasution; Muhammad Siddik Hasibuan
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 7 No. 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2315

Abstract

Abstract: The most frequently consumed staple food by humans is staple food which is a mandatory menu for humans. Staple food is also commonly called sembako which is an abbreviation of nine staple foods whose names are already familiar to Indonesia. Autoregressive Integrated Moving Average (ARIMA) and Monte Carlo use data from the Medan City Trade Office. Based on the Monte Carlo method, the price prediction results using the application produce price prediction results in the range of 12000 to 13000 on the first, fifth and sixth days worth 13000 and the other days are 12000, then when the MSE value calculation is carried out with the predicted price and actual price, the Monte Carlo method produces an MSE value of 300000. Then based on the Arima Method when the data stationarity test is carried out, the ACF and PACF plot tests are obtained, the possible models are Arima (1,1,0), Arima (2,1,0), Arima (3,1,0), Arima (0,1,1), Arima (1,1,1), Arima (2,1,0) and Arima (3,1,0). Then when the best model test is carried out by comparing the smallest MSE value in the possible models, the best model is the Arima method with Model 3,1,1 which produces a stable price prediction at a price of 12000 in the price prediction forecast on day 1 to day 10. And when the predicted price calculation is carried out with the actual price, it produces an MSE value of 0. Keywords: Website, Staple Materials, Arima, Monte Carlo Methods, Python. Abstrak: Bahan pokok yang paling sering dikonsumsi oleh manusia adalah bahan pokok yang merupakan menu wajib untuk manusia. Bahan pokok juga biasa disebut dengan sembako yang merupakan singkatan dari sembilan bahan pokok yang namanya sudah tidak asing lagi bagi Indonesia. Autoregressive Integrated Moving Average (ARIMA) dan Monte Carlo menggunakan data dari Dinas Perdagangan Kota Medan. Berdasarkan metode Monte Carlo, hasil prediksi harga dengan menggunakan aplikasi menghasilkan hasil prediksi harga dalam rentang 12000 hingga 13000 di hari pertama, kelima dan ke enam senilai 13000 dan hari lainnya adalah 12000, kemudian ketika di lakukan perhitungan nilai MSE dengan harga prediksi dan harga actual, metode Monte Carlo menghasilkan nilai MSE sebesar 300000. Kemudian berdasarkan Metode Arima ketika dilakukan uji stasioneritas data, uji plot ACF dan PACF didapatkan model memungkinkannya adalah Arima (1,1,0), Arima (2,1,0), Arima (3,1,0), Arima (0,1,1), Arima (1,1,1), Arima (2,1,0) dan Arima (3,1,0). Lalu ketika dilakukan pengujian model terbaik dengan membandingkan nilai MSE terkecil pada model yang memungkinkan tersebut, model terbaiknya adalah metode Arima dengan Model 3,1,1 yang menghasilkan prediksi harga yang stabil di harga 12000 pada peramalan prediksi harga pada hari ke 1 hingga hari ke 10. Dan ketika dilakukan perhitungan harga prediksi dengan harga aktual menghasilkan nilai MSE sebesar 0. Kata kunci: Website, Bahan Pokok, Metode Arima, Monte Carlo, Python  
Maturity Assessment at a University IT Center Using COBIT 2019 EDM and APO Domains Ilka Zufria; Muhammad Siddik Hasibuan
Information Technology Education Journal Vol. 5, No. 1, February (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i1.262

Abstract

Purpose – This study evaluates the capability of IT governance at Pustipada UIN Sumatera Utara Medan to determine whether current technology practices are aligned with institutional strategic objectives, particularly in terms of resource optimization, governance structure, and innovation. The study addresses the gap between existing governance performance and expected capability levels within higher education institutions.  Design – A descriptive qualitative design was employed. Data were collected through in-depth interviews with key stakeholders identified using RACI Chart mapping, analysis of SOP and KPI strategic documents, and direct observation of objective alignment. The evaluation focused on selected COBIT 2019 domains, namely EDM04 (resource optimization), APO01 (management framework), and APO04 (innovation).  Findings – The results indicate that the EDM04 domain achieved a capability level of 3 with a score of 2.24, below the expected level 4 (2.60), resulting in a gap of 0.36. The APO01 domain also reached level 3, indicating moderate maturity in governance structure, while the APO04 domain recorded a lower score of 1.58, reflecting weak innovation governance. These findings confirm that IT governance implementation remains suboptimal and requires systematic improvement.  Research implications – The study is limited to a single institutional context, which restricts generalizability. The reliance on qualitative data and the absence of integrated financial SOPs may also affect the comprehensiveness of governance evaluation and limit deeper performance validation.  Originality – This research provides a quantified baseline of IT governance capability within a higher education context in North Sumatra, offering actionable insights and strategic recommendations, particularly in formalizing resource documentation and strengthening governance processes as a roadmap for similar institutions.
OCR-LSTM-Based Detection of Pork-Derived Non-Halal Ingredients from Food Labels Muhammad Siddik Hasibuan; Suhardi Suhardi; Bagus Ageng Alfahri
Bigint Computing Journal Vol 4 No 2 (2026)
Publisher : Ali Institute of Reseach and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/bigint.v4i2.1856

Abstract

Packaged food labels may contain technical and multilingual ingredient terms that complicate preliminary screening for pork-derived non-halal substances. This study develops a web-based pipeline that integrates optical character recognition (OCR), automatic translation, and Long Short-Term Memory (LSTM) text classification. A public dataset of 528,092 labeled ingredient records, comprising 291,920 halal and 236,172 pork-related non-halal records, was used for model development. After text normalization, tokenization, and sequence padding, the data were divided into training, validation, and testing subsets using an 80:10:10 ratio. The final test set contained 52,810 records. The confusion matrix contained 29,182 true negatives, 12 false positives, 41 false negatives, and 23,575 true positives, corresponding to 99.90% accuracy, 99.95% precision, 99.83% recall, and a 99.89% F1-score. The web implementation accepts label images, extracts text, translates non-English content, and applies the trained classifier. The reported metrics evaluate the text classifier rather than the complete OCR-to-classification pipeline; therefore, the system should be treated as a preliminary screening tool and not as a substitute for formal halal certification.
Co-Authors Abdul Halim Hasugian Achyar Zein Ahmad Affandi Rasyad Nasution Ahmad al-Badawi, Abdullah Aidil Alfarizi Aidil Halim Lubis Aidil Halim Lubis Ali Darta Andi Andi Anisa Rahman Anisa Simanjuntak Armansyah Asti, Dini Aulia Nurhasanah, Dhea Aulia, Dhinanda Aulia, M. Arif Bagus Ageng Alfahri Bela Sapitri Br Sembiring, Trisna Amanda Dicky Adityanta Sinuraya Dio Wahyu Habibi Hutabarat Efendi, Ayu Mahriza Agustin Erwin Nasution Fadhli Rizqi Haidar Pane Fatih Muhammad, Aji Haikal, Baginda Fikri Hamzah, Aldiva Handira, Dysa Harahap, Parlindungan Harahap, Raihan Hasibuan, Bunga Lestari Heri Santoso Hisbullah, Riki Hotmaidah Harahap Hutabarat, Dio Wahyu Habibi Ichsan Rafisyah Ilka Zufria Imam Utomo Indah Permata Sari Ivan Prayuda Khairani Ritonga, Putri Kurniawan, Riski Askia Lestari, Rika Dinda Lipantri Mashur Gultom Lorena, Ayu Lubis, Muhammad Taufik Hakim Lubis, Putri Natasya M. Naufal Rangkuti M. Ridwan M.Alexander Agung Manullang Mahdiania, Diania Marpaung, Devi Aryani Mhd Furqan Mhd Ikhsan Rifki Mitha Rosadi Mrg, Ricky Aulia Muhammad Abi Muzaki Muhammad Dedi Irawan Muhammad Fadiga Muhammad Ikhsan Muhammad Zulfahmi Nasution Mukhairi Rizal, Muhammad Nasution, Yusuf Ramadhan Naufal, Rahmad Nazhifa Ahmad Fauzan Nurhanifah Piramida, Piramida Pratama, Dian Agus Rahmat Kurniawan Rahmat Kurniawan R Raissa Amanda Putri Rakhmat Kurniawan R Ramadhan, Rizky Syahrul Rangkuti, M. Naufal Reza Adhitya Budiman Riska Hasibuan Rita Novita Sari Rizkika Ananda Rizky Ananda Pakpahan Rizky Pakpahan Rosadi, Mitha Sandira, Sri Delwis Selian, Suci Nadillah Serdano, Akbar Sholihin, Sazili Siagian, Qori Azmi Ayasy Sinuraya, Dicky Adityanta Siregar, Putri Aprilia Sita Kirana Atikah Siti Nurhaliza Sofyan Sri Wahyuni Sriani Sriani Suendri Suhardi Suhardi suhardi suhardi Suhardi, Suhardi Supiyandi Supiyandi Syahputra, Surya Syahputri, Cindy Novi Syaqila, Saidatus Tanjung, Tajuddin Tarigan, Mayang Safhira Tisna Handayani TM Farrel Davin Aqilah Triase Triase Triase Triase, Triase Utomo, Imam Yudhistira, Yudhistira Yusuf Karim Rambe Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan Zalina Zakaria Zulham Zulham