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All Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah EDUMATIC: Jurnal Pendidikan Informatika Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Data and Science Buletin Sistem Informasi dan Teknologi Islam
Hasanuddin, Tasrif
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Mathematics

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ANALISIS PERFORMA METODE K-NEAREST NEIGHBOR UNTUK IDENTIFIKASI JENIS KACA Baharuddin, Mus Mulyadi; Azis, Huzain; Hasanuddin, Tasrif
ILKOM Jurnal Ilmiah Vol 11, No 3 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (637.025 KB) | DOI: 10.33096/ilkom.v11i3.489.269-274

Abstract

Nowadays, the industry makes various types of goods that have glass-based materials, float car window panes, non-float building windows, lamps, jars, and tableware. These glasses have the same production material, the difference between one and the other is the composition of the production material. K-Nearest Neighbor (KNN) algorithm which is one of the classification methods in data mining and also a supervised learning algorithm in machine learning is a method for classifying objects based on learning data that is the closest distance to the object.. This study discusses the performance measurement (accuracy, precision, recall and f-measure) of the KNN method with a variety of values on 1000 glass type production data objects obtained from the central UCI Machine Learning Repository dataset. The conclusion of this research is the results of the value of K = 3 to K = 9, the best performance values obtained at K = 3, where the level of accuracy reaches 64%, 63% precision, 71% recall, and F-Measure of 67%.
PENERAPAN METODE EXACT MATCH PADA APLIKASI ALQUR’AN DAN HADITS BERBASIS ANDROID Suardi, Citra; Wibawa, Aji Prasetya; Hasanuddin, Tasrif; Mude, Muhammad Aliyazid; Cokrowibowo, Sugiarto
ILKOM Jurnal Ilmiah Vol 11, No 3 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (499.956 KB) | DOI: 10.33096/ilkom.v11i3.438.184-190

Abstract

Exact Match is used to bring up sentences only on certain keywords. This study aims to apply the Exact Match method in the Al-qur'an and Hadith applications to find conformity between verses and hadiths. This research simplify for the people to increase their knowledge of the Qur'an and Hadith. This study uses interview techniques for some Muslims regarding the need to learn the quran and the hadith, observation technique is to do a comparison of several hadiths by asking for recommendations from the ustadz/ustazah, identify what are the shortcomings of existing hadith applications, and literature study techniques that are collecting data obtained from the Qur'an and the Hadith. The results of this study are (1) Created an application to match Hadiths that are in accordance the verse with the Exact Match method (2) Showing hadith related to the contents of the selected verse (3) Speed to produce a match in the Application of the Qur'an and Hadith depends on the internet network and the amount of data (4) The number of hadiths that appear is influenced by the number of available hadiths.
Decision Support System for Ranking Active Waste Bank in Makassar City Using TOPSIS and VIKOR Methods Papua, Ahmad Ruslandia; Hasanuddin, Tasrif; Hasnawi, Mardiyyah
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2158

Abstract

In the city of Makassar, there were initially around 1000 waste banks, but this number has decreased significantly, and by 2023 only 381 waste banks remain active. The decline in the number of waste banks is primarily due to the society's lack of knowledge regarding the utilization of waste banks. This research aims to rank active waste banks in Makassar using the MCDM (Multi-Criteria Decision Making) technique. Two MCDM methods will be utilized in this study: the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method and the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) method. Both methods share a common goal of finding the closest value to the ideal solution, but they differ in their normalization and aggregation functions. TOPSIS calculates the criteria weight values first, followed by the criteria values, whereas VIKOR starts with the highest criteria values and then calculates the criteria weights. The results of this research indicate that some alternatives received the same ranking using TOPSIS and VIKOR methods. The criteria used to calculate data for Waste Banks are Operational Hours, Operational Schedule, Total Customers, Total Employees, and Amount of Collected Waste. These criteria are determined based on Regulation Minister of Environment and Forestry Republic of Indonesia Number 14 of 2021 concerning Waste Management at Waste Banks.
Analisis Perbandingan Performa Metode Simple Moving Average dan Exponential Moving Average untuk Peramalan Jumlah Penderita Covid-19 Litha Sari, Nurul; Hasanuddin, Tasrif
Indonesian Journal of Data and Science Vol. 1 No. 3 (2020): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ijodas.v1i3.19

Abstract

Pada penelitian bertujuan untuk memprediksi jumlah penderita covid-19 menggunakan metode Moving Average (SMA, dan EMA). Pengolahan data tersebut digunakan untuk memprediksi jumlah penderita covid-19. Adapun akurasi permalan yang digunakan dalam penelitian ini yaitu MAD, MSE, RMSE , dan MAPE. Model Moving Average Model yang akan digunakan pada penelitian ini merupakan metode untuk memperkirakan kondisi pada masa yang akan datang dengan menggunakan kumpulan data-data masa lalu. Periode waktu yang akan dikumpulkan data tersebut dapat berupa Tahunan, Bulanan, Mingguan, bahkan Harian. Hasil pengujian Simple Moving Average (SMA) pada line graph menunjukkan peramalan nilai lebih dekat dengan data real dibandingkan dengan Exponential Moving Average (EMA). Pengunaan SMA 2 hingga SMA5 menunjukkan hasil peramalan SMA 2 paling mendekati dari data real.
PROTOTYPE SISTEM PENGAWASAN PARKIRAN DAN KONTROL GERBANG MENGGUNAKAN ESP 32 CAM DENGAN NOTIFIKASI TELEGRAM Qurrahman, Nur Taufiq; Hasanuddin, Tasrif; Mude, Muh Aliyazid
Buletin Sistem Informasi dan Teknologi Islam Vol 4, No 4 (2023)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v4i4.1755

Abstract

Sistem Keamanan merupakan hal yang sangat dibutuhkan seiring dengan semakin banyaknya jumlah kendaraan di kota- kota besar. Keamanan merupakan bagian yang penting dalam kehidupan manusia. Sistem keamaman dan pengawasan di Sebuah area parkiran perlu disediakan untuk pengendara.Kejadian Pencurian di area parkiran biasa terjadi Ketika pengawasannya kurang optimal, oleh karena itu hingga saat ini teknologi sistem keamanan terus dikembangkan oleh para peneliti untuk menciptakan teknologi yang dapat menjamin rasa aman ke pengguna. Namun teknologi yang ada masih perlu di tingkatkan fungsi dan kualitasnya, salah satunya untuk meningkatkan teknologi tersebut dengan mengaplikasikan sistem pengawasan parkiran dengan menggunakan aplikasi telegram di mana kita bisa mengontrol, mengakses dan mendapatkan laporan tentang kondisi pengendara pada saat memasuki parkiran. Pada penelitian ini bertujuan merancang prototype sistem pengawasan parkiran dan kontrol gerbang parkiran otomatis menggunakan Esp 32 Cam dengan notifikasi telegram, dimana Ketika sensor PIR ( Passive Infraret) dan sensor Ultrasonik mendeteksi objek, maka esp 32 cam mengambil foto dan mengirimkan hasilnya kepada pengguna melalui aplikasi telegram lalu palang servo akan terbuka dengan delay 5 detik lalu tertutup kembali. Dari hasil pengujian yang dilakukan, di dapatkan hasil berupa jarak maksimum sensor untuk mendeteksi objek adalah 10 cm, dan untuk waktu pengiriman notifikasi ke telegram mendapatkan hasil rata – rata 4,98 /detik. Dari pengujian yang dilakukan terbukti sistem mampu bekerja mendeteksi, mengambil foto dan mengirim hasilnya ke pengguna.
Fog computing in classrooms: boosting efficiency, responsiveness, user experience Hasanuddin, Tasrif; Hadi, Mokh Sholihul; Sujito, Sujito; Rosnani, Rosnani
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp1287-1295

Abstract

In the context of rapidly advancing smart education systems, the effective management and optimization of modern classroom remain critical challenges. This research presents a novel methodology leveraging cloud and fog computing-based simulations, with a specific focus on the implementation of iFogSim. Empirical findings validate the efficacy of fog computing in monitoring classrooms, demonstrating significant improvements in performance metrics compared to traditional cloud computing architectures. Specifically, fog computing ensures remarkably low latency, with a mere 7 milliseconds, even with scalable integration across multiple classrooms. In contrast, cloud computing infrastructures exhibit considerably higher initial latencies, starting at 210 milliseconds, which further escalate with the increasing number of monitored classrooms. Furthermore, our analysis reveals substantially lower network overhead associated with fog computing, measuring at 5,231.8 kilobytes, in sharp contrast to the significantly higher network usage of 80,808 kilobytes observed with cloud computing solutions. These findings underscore the potential of fog computing as a promising solution for efficient and real-time management classroom in smart education environments.
Teknologi Blockchain berbasis Non Fungible Token sebagai Penghargaan Partisipasi Donor Darah Moleo, Alif Safa; Hasanuddin, Tasrif; Darwis, Herdianti; Harlinda, Harlinda
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 2 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i2.28005

Abstract

Non-fungible tokens (NFTs) are a technological innovation that has been widely used to provide a form of digital reward. However, the application of NFTs in the social domain, especially in blood donation programs, has not been widely explored. This research aims to develop an NFT-based reward system using blockchain technology as an appreciation for blood donors. The system is designed and developed using the Ethereum test network due to its stability in decentralized applications. This research uses the research and development (R&D) method with the 4D model approach, which consists of the Define, Design, Develop, and Disseminate stages. In the Define stage, a needs analysis was conducted to determine the system specifications. The Design stage involves the design of a web-based system3 to support NFT management. In the Develop stage, the system was developed using the Ethereum testing network. The Disseminate stage includes system testing using the black box method to ensure that all key features, such as NFT claims and data transparency, function properly. The result of the research is an NFT-based blockchain application that allows blood donors to easily claim their NFTs as a form of digital recognition. The evaluation showed an acceptability score of 61.34%, indicating that this application is acceptable to the community and has the potential to increase blood donor motivation. The implementation of this system is expected to have a sustainable positive impact on increasing blood donor participation in the future.
PENERAPAN TEKNOLOGI VIRTUAL REALITY (VR) UNTUK PENGENALAN WORKINGSPACE FAKULTAS ILMU KOMPUTER UNIVERSITAS MUSLIM INDONESIA Riyadi, Rahmat; Hasanuddin, Tasrif; Abdullah, Syahrul Mubarak
Buletin Sistem Informasi dan Teknologi Islam Vol 5, No 3 (2024)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v5i3.2198

Abstract

Media Informasi terus berkembang dengan seiring kemajuan teknologi yang semakin memudahkan manusia dalam menyampaikan pesan-pesan yang relevan, cepat, dan bermanfaat. Virtual Reality (VR) adalah teknologi yang semakin populer yang memungkinkan pengguna untuk mengalami dan berinteraksi dengan lingkungan yang disimulasikan secara digital secara immersif. Media informasi pada lingkungan gedung kampus menjadi salah satu topik yang dibahas dalam penelitian ini. Penelitian ini mengambil studi kasus gedung yang terdapat pada salah satu bangunan Workingspace Fakultas Ilmu Komputer Universitas Muslim Indonesia. Tujuan dari penelitian ini adalah penerapan teknologi Virtual Reality pada bangunan Workingspace beserta tata ruang dan penyampaian konten informasi yang dinamis dan interaktif. Metode yang digunakan dalam penelitian ini adalah Multimedia Development Life Cycle (MDLC). Berdasarkan hasil rancangan yang telah dilakukan pada sistem Virtual Reality Workingspace diperoleh hasil bahwa alat berjalan sesuai dengan yang diinginkan, penyampaian konten dinamis dan informasi untuk teks, suara dan gambar sesuai yang diinginkan.
Implementasi K-Nearest Neighbor (KNN) pada Sistem Pakar Diagnosa Penyakit Untuk Menentukan Kelayakan Sapi sebagai Hewan Qurban Berbasis Web Arsyad, Muh Arya; Hasanuddin, Tasrif; Hasnawi, Mardiyyah
Buletin Sistem Informasi dan Teknologi Islam Vol 3, No 3 (2022)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v3i3.632

Abstract

Umat islam melaksanakan ibadah qurban setiap tahun. Sapi adalah salah satu hewan qurban yang disembeli dalam perayaan eid adha. Sapi yang disembeli harus sesuai syariat islam. Beberapa panitia pelaksana pemotongan hewan qurban kurang memiliki pengetahuan mengenai berbagai penyakit yang dapat menyerang sapi dan sulitnya mencari tenaga medis khusus hewan atau dokter hewan sehingga panitia qurban tidak dapat secara cepat menangani sapi yang terkena penyakit. Penelitian ini bertujuan untuk membangun sistem pakar diagnosa penyakit pada sapi dan menentukan kelayakannya sebagai hewan qurban dengan menerapkan K-Nearest Neighbor (K-NN). Sampel penelitian ini menggunakan 13 jenis penyakit dan 43 gejala pada sapi sebagai data latih dan data uji. Data tersebut dihitung jarak terdekat menggunakan Euclidean Distance dan ditentukan banyaknya k tetangga terdekat untuk melakukan klasifikasi data baru. Hasil penelitian berupa aplikasi yang mampu menentukan diagnosa penyakit pada sapi menggunakan K-NN. Berdasarkan pengujian aplikasi menggunakan Black Box Testing menunjukkan tingkat penerimaan aplikasi sebesar 86.66%.
Classification of Lontara Script Using K-NN Algorithm, Decision Tree, and Random Forest Based on Hu Moments and Canny Segmentation Septiani, Berlian; Hasanuddin, Tasrif; Astuti, Wistiani
Indonesian Journal of Data and Science Vol. 6 No. 2 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i2.281

Abstract

Lontara script is a traditional writing system of the Bugis-Makassar people in South Sulawesi, used to write the Bugis, Makassar, and Mandar languages. This system is based on an abugida, in which each letter represents a consonant with an inherent vowel. It was once used to record history, customary law, and literature, but its use has declined due to the influence of the Latin alphabet. Today, the Lontara script is preserved through education and digitization as part of the cultural heritage of the Indonesian archipelago. In this article, the researchers attempt to use a dataset of handwritten Lontara Bugis-Makassar characters. The process begins with the collection of character datasets, which are then processed through Canny segmentation and Hu Moment feature extraction to obtain a representation of the shape that is invariant to rotation and scale. The processed data was divided into training and testing data, then classified using the K-NN, Decision Tree, and Random Forest algorithms. The results showed that the KNN algorithm with 6 neighbors achieved the highest accuracy, precision, and recall of 98%. The Decision Tree algorithm achieved an accuracy of 96.67%, precision of 96.22%, recall of 95.33%, and an F1-score of 95.98%. Meanwhile, Random Forest showed an accuracy of 96.67%, precision of 96.34%, recall of 96%, and an F1-score of 95.98%.
Co-Authors Abdullah, Syahrul Mubarak Aji Prasetya Wibawa Arsyad, Muh Arya Astuti, Wistiani Baharuddin, Mus Mulyadi Citra Suardi Darwis, Herdianti Harlinda, Harlinda Huzain Azis Litha Sari, Nurul Mardiyyah Hasnawi Mokh Sholihul Hadi Moleo, Alif Safa Mude, Muh Aliyazid Muh. Aliyazid Mude Papua, Ahmad Ruslandia Qurrahman, Nur Taufiq Rahmat Riyadi Rosnani Rosnani Septiani, Berlian Sugiarto Cokrowibowo Sujito Sujito