Garuda - Garba Rujukan Digital

PERANCANGAN SISTEM INFORMASI E-LIBRARY PADA SMA NEGERI 2 TARUTUNG BERBASIS WEB DENGAN TEKNOLOGI RESPONSIF Sihotang, Vemmy Joshi Apfia; Harianja, Eva Julia Gunawati; Nainggolan, Rena
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 3 No 2 (2023): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol3No2.pp177-189

Library data processing at SMA Negeri 2 Tarutung is still done manually. This is a problem of SMA N 2 Tarutung library, such as limited book collection, difficulty accessing books, inability to present information optimally in terms of speed, accuracy, and smooth system, and other problems related to traditional libraries. The purpose of this final project research is to design a web-based library for SMA Negeri 2 Tarutung that can be used to encourage students to read more books and make it easier for students to access books, namely through digital books (E-Library) Research methodology to collect information about library information system design includes reading scientific papers, conducting interviews, and making observations. Interviews and observations are used to analyze information system needs, which is then followed by creating databases, web inputs and outputs, and PHP software. The development phase includes PHP program development, database design, input and output design for the web, and Data Flow Diagrams (DFDs). Trials are run to assess the system as a whole. The results of the design of the E-library information system show that the application of this system can improve the quality of student reading by facilitating access to books through the web platform.

SISTEM INFORMASI PENGGAJIAN GURU DAN PEGAWAI DI SEKOLAH DASAR ADVENT 2 MEDAN BERBASIS WEB Hutahaean, Artauli Meypia; Harianja, Eva Julia Gunawati; Purba, Eviyanti Novita
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 3 No 2 (2023): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol3No2.pp190-197

The Design Information System of Payroll for Teachers and Employees in Medan Adventist 2 Elementary School is a research that has the goal of developing an information system that can be used efficiently to process the payroll process for teachers and employees of Medan Adventist 2 Elementary School. This information system is designed to facilitate the web-based payroll process which does not require a lot of time to process payroll, whereas previously the payroll process was done manually using a ledger which took quite a long time. The results of this study are a payroll information system for teachers and employees that can assist cashiers as admins in carrying out the payroll process and issuing salaries that will be received by teachers and employees accurately and systematically. This system is also equipped with a security feature that ensures that only the main admin, namely the cashier, has the authority to make payroll.

MODEL BIDIRECTIONAL LSTM UNTUK PEMROSESAN SEKUENSIAL DATA TEKS SPAM Siringoringo, Rimbun; Jamaluddin, Jamaluddin; Perangin-angin, Resianta; Harianja, Eva Julia Gunawati; Lumbantoruan, Gortap; Purba, Eviyanti Novita
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp265-271

This study examines the LSTM-based model for processing spam in text data. Spam poses several dangers and risks, both for individuals and organizations. Spam can be a nuisance that hampers both individual and organizational productivity. Much spam contains fraudulent or phishing attempts to obtain sensitive information. Spam detection using deep learning involves the utilization of algorithms and deep neural network models to accurately classify messages as either spam or not spam. Typically, spam detection systems use a combination of these methods to improve the accuracy of identifying spam messages. This study applies the Bi-LSTM deep learning model to sequentially process text (sequencing). The performance of the model is determined based on the loss and accuracy. The data used are the Spam SMS and Spam Email datasets. The test results show that the Bi-LSTM model demonstrates better performance on all tested datasets. Bi-LSTM is able to capture textual patterns from both the context and the text itself, as it can combine information from both directions. The test results prove that the Bi-LSTM model is more effective in text comprehension. So we need to use Snort to maintain network security. Snort is a useful software for observing activity in a computer network. Snort can be used as a lightweight Network Intrusion Detection System (NIDS). Detection is carried out based on the rules that have been described by the administrator in the directory rules contained in the configuration file. Snort can analyze real time alerts, where the mechanism for entering alerts can be in the form of a user syslog, file or through a database. So we can detect attacks on computer networks early.

Sistem Informasi Pemesanan Makanan/Minuman pada Coffee Hitam Putih Berbasis Web Sinaga, Nillasari; Nainggolan, Rena; Harianja, Eva Julia Gunawati
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 1 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No1.pp61-66

Currently, Coffee Hitam Putih still uses manual recording. Manual order recording is less efficient in terms of time and cost. So, to realize consumer satisfaction in ordering food, a food/beverage ordering information system on web-based Coffee Hitam Putih was created. This information system provides a list of food menus, prices, descriptions, and availability. This information system makes it easier for the management of Coffee Hitam Putih to provide effective and efficient services. It can produce fast, precise and accurate information because it uses a database. The methods used in data collection are: a. Literature method, which is a method of collecting data with the help of books from the library or documents and reports related to this research. b. The observation method, which is observing the running system directly on the object to be studied, in order to provide clear and precise information about the process and activities related to ordering menus at Coffee Hitam Putih. c. Interview method, namely conducting questions and answers directly with the manager of Coffee Hitam Putih. The advantage of this technological development is that it is very helpful for people's daily activities. The existence and role of information technology in all sectors of life have an impact on the economic, social, and cultural aspects of human beings.

UTILITY VECTORS TO FUZZY PREFERENCE RELATION DENGAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) DALAM PENENTUAN POSISI KERJA KARYAWAN Harianja, Eva Julia Gunawati; Ketaren, Eliasta
Jurnal TIMES Vol 5 No 1 (2016)
Publisher : STMIK TIME

Penempatan kerja bukanlah masalah sederhana, sebab kesalahan penempatan dapat mempengaruhi operasi perusahaan. Masalah utama yang dihadapi dalam menyeleksi karyawan adalah masih kurangnya ketepatan dan kecepatan proses penilaian kinerja masing-masing karyawan guna memenuhi posisi tertentu. Penilaian kinerja karyawan yang didasarkan pada kriteria-kriteria tersebut sering kali menjadi masalah dalam proses pengambilan keputusan. Untuk mengekspresikan preferensi pengambil keputusan pada alternatif yang paling diinginkan, dapat dilakukan dengan transformasi format preferensi Utility Vectors to Fuzzy Preference Relation. Selanjutnya memilih metode SAW untuk menentukan nilai bobot untuk setiap atribut, yang dilanjutkan dengan proses perangkingan untuk menyeleksi alternatif terbaik, dalam hal ini adalah alternatif yang cocok untuk menentukan posisi kerja karyawan yang sesuai dengan kriteria-kriteria yang telah ditentukan. Dengan metode ini diharapkan penilaian akan lebih tepat dan akurat karena didasarkan pada nilai kriteria dan bobot yang telah ditentukan.

Pendekatan Level Data untuk Menangani Ketidakseimbangan Data Menggunakan Algoritma K-Nearest Neighbor Perangin-angin, Resianta; Harianja, Eva Julia Gunawati; Jaya, Indra Kelana
Jurnal TIMES Vol 9 No 1 (2020)
Publisher : STMIK TIME

Dalam penelitian ini digunakan dataset yang memiliki tingkat ketidakseimbangan yang berbeda beda mulai dari 16.40, 8.60, 2.06, 2.78, 1.87, tentu hal ini dapat menurunkan kinerja algoritma klasifikasi. Secara umum ketidakseimbangan kelas dapat ditangani dengan dua pendekatan, yaitu level data dan level algoritma. Pendekatan level data ditujukan untuk memperbaiki keseimbangan kelas, sedangkan pendekatan level algoritma ditujukan untuk memperbaiki algoritma atau menggabungkan (ensemble) pengklasifikasi agar lebih konduktif terhadap kelas minoritas. Pada penelitian ini diusulkan pendekatan level data dengan resampling, yaitu random oversampling (ROS), dan random undersampling (RUS), Pengklasifikasi yang digunakan adalah k-near neighbors. Hasil penelitian menunjukkan bahwa model ROS+KNN dan RUS+KNN didapat dengan selisih G-Means sebesar 13% dan F-Measure 2,08%, dari, hal ini menunjutkan bahwa RUS+KNN dan ROS+KNN bisa meningkatkan akurasi dari G-Mean dan F-Measure namun tidak memiliki perbedaan yang signifikan.

Comparison Detection Edge Lines Algoritma Canny dan Sobel Perangin-angin, Resianta; Harianja, Eva Julia Gunawati
Jurnal TIMES Vol 8 No 2 (2019)
Publisher : STMIK TIME

Deteksi tepi adalah pendekatan paling umum yang digunakan untuk mendeteksi tingkat abu-abu diskontinuitas. Ini karena titik atau garis yang terisolasi tidak terlalu sering dijumpai dalam aplikasi praktis. Idealnya, teknik yang digunakan untuk mendeteksi diskontinuitas hanya menghasilkan satu piksel yang terletak di wilayah batas. Salah satu teknik pengolahan citra yang digunakan adalah deteksi tepi. Deteksi tepi sering terjadi pada pengolahan citra digital karena merupakan salah satu langkah awal dalam segmentasi citra yang bertujuan untuk mempresentasikan objek yang terdapat pada citra. Deteksi tepi berfungsi untuk mengidentifikasi batas-batas suatu objek dengan latar belakang yang tumpang tindih. Oleh karena itu, ketika garis besar gambar dapat diidentifikasi secara akurat, semua objek dapat ditemukan dan properti dasar seperti luas, bentuk, dan ukuran objek dapat diukur. Ada beberapa jenis metode deteksi tepi yang dapat digunakan untuk mendeteksi garis besar suatu citra, seperti algoritma Sobel, Prewitt, Canny dan homogenitas. Masing-masing metode tersebut memiliki kelebihan dan kekurangannya masing-masing. Dalam penelitian ini akan diambil dua algoritma yaitu algoritma Canny dan Sobel. Berdasarkan kekuatan dan kelemahan kedua metode tersebut akan dilakukan analisis terhadap kedua metode tersebut untuk melihat hasil pendeteksian yang keduanya akan digunakan sebagai pembanding. Dilihat dari hasil yang didapat dari algoritma deteksi tepi Canny dan Sobel secara jelas terlihat lebih baik algoritma cannya pada hasil pendekteksian tepi, dimana algoritma Canny mempunyai hasil yang lebih halus dan lebih spesifik mendekteksi garis tepi suatu objek citra. Sedangkan algoritma pendektesian garis tepi sobel masih meregang pada daerah yang tidak berbatasan. Dilihat dari struktur hasil pendeteksian algoritma Canny lebih baik daripada algoritma Sobel.

SISTEM PENDUKUNG KEPUTUSAN PEMBERIAN BANTUAN SEMBAKO BAGI JEMAAT GEREJA HKI TERDAMPAK COVID-19 MENGGUNAKAN METODE TOPSIS STUDI KASUS: HKI RESORT SIGALINGGING Harianja, Eva Julia Gunawati; Lumbantoruan, Gortap; Nainggolan, Rena
Jurnal TIMES Vol 10 No 2 (2021): Jurnal TIMES
Publisher : STMIK TIME

Berbagai sektor kehidupan manusia yang terdampak Covid-19 secara khusus dapat dirasakan pada sektor perekonomian, seperti yang dialami oleh masyarakat Indonesia saat ini. Pemerintah maupun berbagai pihak lainnya berupaya meringankan beban masyarakat yang terdampak Covid-19 dengan menyelenggarakan berbagai program bantuan, seperti halnya penyaluran sembako kepada masyarakat. Gereja Huria Kristen Indonesia (HKI), khususnya Resort Sigalingging juga turut mengambil peran dengan menyalurkan bantuan sembako bagi warga jemaatnya yang terdampak Covid-19. Sebagai penyelenggara penyalur bantuan tersebut, diharapkan Gereja HKI lebih selektif dalam proses penyeleksian calon penerima bantuan agar penyaluran bantuan tepat pada sasarannya. Penentuan warga jemaat Gereja HKI sebagai calon penerima bantuan sembako yang terdampak Covid-19 didasarkan pada kriteria-kriteria tertentu sering kali menjadi masalah dalam proses pengambilan keputusan. Untuk mengekspresikan preferensi pengambil keputusan pada alternatif yang paling diinginkan, dapat dilakukan dengan menerapkan Technique For Order Preference by Similarity to Ideal Solution (TOPSIS). Metode TOPSIS akan di kombinasikan dengan logika fuzzy untuk menentukan nilai bobot pada setiap atribut kriteria, yang dilanjutkan dengan proses perangkingan untuk menyeleksi alternatif terbaik, dalam hal ini adalah alternatif yang valid sebagai penerima bantuan yang sesuai dengan kriteria. Dengan metode ini diharapkan proses penilaian akan lebih tepat dan akurat karena didasarkan pada nilai kriteria dan bobot yang telah ditentukan.

Logic Test Educational Game for Children Based on Multimedia Ndruru, Yufita Friska; Jamaluddin, Jamaluddin; Simamora, Roni Jhonson; Harianja, Eva Julia Gunawati
Journal of Computer Science and Research (JoCoSiR) Vol. 2 No. 1 (2024): Jan: CNN and Artificial
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65126/jocosir.v2i1.21

Along with the development of information technology, the rapid use of technology as a learning media is very good to apply. Many ways can be done to improve the quality of education. This research was conducted by creating an interactive learning media product in the form of a logic test educational game where students are required to learn to solve existing logic problems. The multimedia-based logic test educational game for children is designed to develop children's logic, measure intelligence levels, and become an alternative means of fostering students' interest in learning. The research method used is the method of literature study, interviews, and observations, the stages of analysis and definition of needs, the stages of system and software design, the stages of implementation, and unit testing. The appearance of educational games is designed to be attractive, which is accompanied by images and quizzes that improve student memory and provide new experiences for students. The implementation of this educational game has been carried out on students of SD Negeri 060934 and the results show the enthusiasm level of the students towards the educational game used.

MODEL BIDIRECTIONAL LSTM UNTUK PEMROSESAN SEKUENSIAL DATA TEKS SPAM Siringoringo, Rimbun; Jamaluddin, Jamaluddin; Perangin-angin, Resianta; Harianja, Eva Julia Gunawati; Lumbantoruan, Gortap; Purba, Eviyanti Novita
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp265-271

This study examines the LSTM-based model for processing spam in text data. Spam poses several dangers and risks, both for individuals and organizations. Spam can be a nuisance that hampers both individual and organizational productivity. Much spam contains fraudulent or phishing attempts to obtain sensitive information. Spam detection using deep learning involves the utilization of algorithms and deep neural network models to accurately classify messages as either spam or not spam. Typically, spam detection systems use a combination of these methods to improve the accuracy of identifying spam messages. This study applies the Bi-LSTM deep learning model to sequentially process text (sequencing). The performance of the model is determined based on the loss and accuracy. The data used are the Spam SMS and Spam Email datasets. The test results show that the Bi-LSTM model demonstrates better performance on all tested datasets. Bi-LSTM is able to capture textual patterns from both the context and the text itself, as it can combine information from both directions. The test results prove that the Bi-LSTM model is more effective in text comprehension. So we need to use Snort to maintain network security. Snort is a useful software for observing activity in a computer network. Snort can be used as a lightweight Network Intrusion Detection System (NIDS). Detection is carried out based on the rules that have been described by the administrator in the directory rules contained in the configuration file. Snort can analyze real time alerts, where the mechanism for entering alerts can be in the form of a user syslog, file or through a database. So we can detect attacks on computer networks early.

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