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All Journal CESS (Journal of Computer Engineering, System and Science) SMATIKA JURNAL MEDIA INFORMATIKA BUDIDARMA J-SAKTI (Jurnal Sains Komputer dan Informatika) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Jurnal Mantik INTI Nusa Mandiri Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Abdimas Bina Bangsa J-SAKTI (Jurnal Sains Komputer dan Informatika) JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Ira Diana Sholihati
Universitas Nasional
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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DIAGNOSA DEPRESI PADA MAHASISWA MENGGUNAKAN METODE CERTAINTY FACTOR DAN FORWARD CHAINING Ibnu Nur Khawarizmi; Agung Triayudi; Ira Diana Sholihati
INTI Nusa Mandiri Vol 14 No 2 (2020): INTI Periode Februari 2020
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v14i2.1173

Abstract

Many person are not aware of the dangers of depression. It's hard to know the symptoms and overcome depression early on. In this case adolescents are the most vulnerable to the disease because at that time humans are in a transition phase from childhood to adulthood. WHO says every second there is a case of suicide due to severe depression. Based on these cases the researchers aimed to make an application to help the community, especially students, to be able to recognize and diagnose depression from an early age. The system in this application is an expert system using the Certainty Factor and Forward Chaining method. Inputs received by this application are biodata and psychological questions about the symptoms experienced by the user. The resulting output is the diagnosis, as well as the percentage of possible diseases suffered by user.
Forward Chaining Algorithm and Simple Additive Weighting (SAW) in Smart HelpDesk Ticketing Information System Ucup Maulana; Fauziah Fauziah; Ira Diana Sholihati
CESS (Journal of Computer Engineering, System and Science) Vol 7, No 1 (2022): January 2022
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v7i1.29750

Abstract

Tujuan dari penelitian ini adalah menjadi solusi membantu tim helpdesk dalam mengelola proses dari membuat tiket hingga penyelesaiannya. Penelitian ini menggunakan algoritma kombinasi Forward Chaining untuk mengelola SLA (Service Level Agreement) pengerjaan tiket dan Simple Additive Weighting (SAW) untuk prioritas pengerjaan tiket. Pengujian telah dilakukan sebanyak 600 data, metode forward chaining mencatat SLA pengerjaan tiket seperti urutan 1 sampai 20 berdurasi 7.9 jam indikator warna hijau, 21 sampai 40 durasi 6 jam berindikator kuning, 41 sampai 70 berdurasi 3 jam indikator hijau, 71 sampai 172 berdurasi 7 hari 19 jam indikator merah, 173 sampai 174 durasi 4 hari, 175 sampai 230 durasi 2 hari 21 jam, 231 sampai 260 berdurasi 8 jam berwarna kuning, 261 sampai 305 4 jam berwarna hijau, 306 sampai 325 berdurasi 7 hari 19 jam indikator merah, 326 sampai 345 berdurasi 12.6 jam berwarna kuning, 346 sampai 356 berdurasi 6.5 jam warna hijau, 357 sampai 469 berdurasi 7 hari 19 jam indikator merah, 470 sampai 475 berdurasi 4 hari, 476 sampai  556 berdurasi 2 hari 19 jam indikator merah, 557 sampai 576 berdurasi 23.9 jam berwarna kuning dan 577 sampai 600 berdurasi 7 jam serta berwarna hijau. Metode SAW mengurutkan prioritas pengerjaan berdasarkan bobot dan nilai awal yang telah ditentukan. Urutan 1 sampai 70 bernilai 100 diperingkat kesatu, 71 sampai 305 bernilai 55 diperingkat kedua, 306 sampai 356 dengan nilai 25 diperingkat ketiga, dan 357 sampai 600 bernilai 10 serta diperingkat keempat.
Scrum Framework and Greedy Algorithm in Product Backlog Wedding Application Planner (Wepplan) Activities Muhamad Iqbal Wasta Purnama; Fauziah Fauziah; Ira Diana Sholihati
CESS (Journal of Computer Engineering, System and Science) Vol 7, No 1 (2022): January 2022
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (696.704 KB) | DOI: 10.24114/cess.v7i1.30625

Abstract

Abstrak—Semakin berkembangnya teknologi maka semakin banyaknya kebutuhan yang diperlukan ini bisa menjadi peluang yang mampu dimanfaatkan untuk mendukung suatu pengembangan teknologi. Pada penelitian ini menerapkan salah satu model dalam perancangan aplikasi dengan mengimplementasikan Scrum framework dan Algoritma Greedy pada aktivitas product backlog Wedding Application Planner (Wepplan). Dimana hal tersebut membentuk 271 jam waktu kerja pada 23 aktivitas product backlog yang terbagi menjadi 4 sprint dengan memberikan solusi optimal pada permasalahan penjadwalan pembagian waktu kerja masing-masing developer. Hasil yang didapat yaitu developer 1 mendapatkan 70 jam waktu kerja, developer 2: 68 jam waktu kerja, developer 3: 69 jam waktu kerja, dan developer 4: 64 jam waktu kerja dalam pengerjaannya. Pada pengujian terhadap nilai response time aplikasi, hasil tercepat pada daftar uji Test Daftar: 27.386 (s), Test Login: 15.378 (s), Test Wedding: 24.433 (s), dan Test Engagement 25.841 (s) didapat menggunakan katalon, pada daftar uji Test Venue: 26.104 (s), Test Catering: 29.244 (s), Test Top Up: 26.617 (s), dan Test Edit Profile: 27.239 (s) menggunakan Testproject. Disimpulkan penelitian ini dapat memberikan manfaat terutama kepada para developer untuk mengefisiensi penjadwalan waktu kerja terhadap rancangan aktivitas dalam membangun sebuah produk aplikasi.Kata Kunci—Wepplan, Android, Scrum Framework, Algoritma Greedy. Abstract—Development of a technology, the more needs that are needed this can be an opportunity that can be used to support a technology development. In this study, one of the models in application design is implemented by Scrum framework and Greedy Algorithm in the Wedding Application Planner (Wepplan) product backlog activity. Where this forms 271 hours of work time on 23 product backlog activities which are divided into 4 sprints by providing optimal solutions to the scheduling problem of each developer's work time division. The results obtained are developer 1 gets 70 hours of work time, developer 2: 68 hours of work time, developer 3: 69 hours of work time, and developer 4: 64 hours of work time in the process. In testing the application response time value, the fastest results on the Test List Signup Test: 27,386 (s), Login Test: 15,378 (s), Wedding Test: 24,433 (s), and Engagement Test 25,842 (s) were obtained using Katalon, while in Venue Test: 26,104 (s), Catering Test: 29,244 (s), Top Up Test: 26,617 (s), and Profile Update Test: 27,239 (s) using Testproject. It is concluded that this research can provide benefits, especially for developers to make work time scheduling efficient for the design of activities in building an application product.
E-Recruitment Menggunakan Metode Simple Additive Weighting dan Algoritma K-Nearest Neighbor Tasya Khaerani Janubiya; Septi Andryana; Ira Diana Sholihati
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.434

Abstract

Along with the increasing number of PT Midi Utama Indonesia Tbk outlets, the company's human resource needs are also increasing. Therefore, the recruitment of new employees is very important to support the company's operations. In order to select prospective new employees to fill various positions needed by the company. Recruitment of new employees has not been carried out professionally. This is because there is no systematic method to assess the suitability of new employees. The application of a decision support system uses a combination of the Simple Additive Weighting (SAW) method and the K-Nearest Neighbor (K-NN) algorithm. This method determines the weight value and ranking results of each candidate. Then, the company conducts the process of selecting candidate data based on the value closest to the old prospective employee to determine the final classification results. In this case, prospective new employees who qualify as employees are based on predetermined criteria. Then this decision support application is built using the PHP programming language and MySQL database. The conclusion in this study by combining the SAW and K-NN methods in the recruitment process is very helpful because the administrative and assessment processes are carried out online. So that decision makers can make choices quickly and accurately.
Model Addie Pada Augmented Reality Hewan Purba Bersayap Menggunakan Algoritma Fast Corner Detection Dan NFT Pramesti Sifa Aisya Nuha; Septi Andryana; Ira Diana Sholihati
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 6, No 2 (2021)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v6i2.1958

Abstract

Pengenalan objek menggunakan Augmented Reality sudah menjadi trend di dunia media promosi kepada anak-anak usia dini hingga masyarakat umum. Objek yang digunakan berupa hewan, tumbuhan, huruf, angka dan lain lain. Penelitian ini menggunakan objek berupa hewan purbakala yang sudah punah sejak jutaan tahun yang lalu. Tujuan penelitian ini yaitu berfokus pada pengenalan hewan-hewan purbakala utnuk anak-anak bahwa terdapat hewan reptil yang berpostur raksasa telah hidup di zaman dahulu. Meskipun reptil ini telah punah, mereka akan menggunakan Augmented Reality pada penelitian ini sebagai media informasi yang menarik. Model ADDIE dikembangkan pada penelitian ini yang disusun oleh Natural Feature Tracking (NFT) menggunakan Algoritma FAST Corner Detection ke arah tingkat keberhasilan yang tinggi. Hasil pengujian pada beberapa versi android berupa objek gambar memiliki tingkat keakuratan yang tinggi melalui perhitungan FAST Corner Detection dan pengujian metode NFT. Semakin tinggi rating objek yang ditunjukkan pada vuforia, maka semakin tinggi ketelitian dalam mendeteksi objek pada marker.
RANCANG BANGUN GAME EDUKASI PECAH BALON BERBASIS ANDROID MENGGUNKAN ALGORITMA FICHER-YATES irfan muttaqim; Septi Andryana; Ira Diana Sholihati
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 6, No 2 (2021)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v6i2.2020

Abstract

Game merupakan salah satu perkembangan yang sangat pesat dalam bidang ilmu komputer. Game merupakan salah satu bentuk aplikasi edukatif yang artinya dapat digunakan sebagai media pembelajaran yang dalam prosesnya dapat diselesaikan melalui konsep pembelajaran dan game. Game edukasi pecah balon meledak ini adalah salah satunya. Dalam permainan tersebut, orang tua dapat mengajari anaknya bermain sambil belajar memahami ejaan huruf. Game edukatif adalah alat pembelajaran dengan tujuan tertentu. Kebanyakan game edukasi mirip dengan menebak. Dalam game ini, pengguna harus memecahkan balon yang tersedia, dan hasil akhirnya adalah skor yang didapat pengguna. Pada penelitian ini algoritma Fisher-Yates dipilih karena merupakan metode pengacakan yang lebih baik, atau dapat dikatakan cocok untuk pengacakan huruf, dengan waktu eksekusi yang cepat dan tidak membutuhkan waktu yang lama untuk pengacakan
Analisis Sentimen Gofood Berdasarkan Twitter Menggunakan Metode Naïve Bayes dan Support Vector Machine Melati Indah Petiwi; Agung Triayudi; Ira Diana Sholihati
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 1 (2022): Januari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i1.3530

Abstract

The Covid-19 pandemic in Indonesia has an impact on every sector of life, including the economy. The government implements social activities that make people have to carry out activities at home. Because of this, humans choose to do everything digitally, including ordering food. With the application of public interest in ordering food online, the income of one of the food orders, namely Gojek (Gofood) has increased. However, Gofood has many pros and cons in the community. In this case, many people give their opinion about the use of social media, especially twitter. The purpose of this study was to analyze public opinion on the performance of Gojek (Gofood) in Indonesia. The grouping into three classes, namely positive, negative and neutral classes were tested using the Naïve Bayes and SVM methods and compared the two methods. The analysis of public sentiment regarding Gofood on Twitter resulted in 92.8% worthy neutral, 5.2% worthy positive and 2.0% worthy negative. Comparing the accuracy results, the Support Vector Machine method has greater accuracy than the Naïve Bayes method, with the Support Vector Machine accuracy values of 83% and 98.5%, while the Nave Bayes accuracy values are 74.6% and 91.5% respectively.
Aplikasi Pembelajaran Interaktif Augmented Reality Tata Surya Sekolah Dasar Menggunakan Metode Marker Based Tracking Ismi Naili Qurrotul Aini; Agung Triayudi; Ira Diana Sholihati
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 1 (2020): Januari 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i1.1875

Abstract

Along with the times, the learning media also continues to grow. In solar system subjects usually, the media is used is books, where students can only see 2D forms. The purpose of this research is to build an application that can create a 3D object accompanied by an explanation, so as to make learning more interactive and easily understood using Augmented Reality (AR) technology. In previous journals, a solar system learning application has been made using AR technology, and this research will be developed by creating a quiz menu and true or false to find out how far students understand the material being taught. To ensure the application runs well, testing images, distance and angle markers, application features, and questionnaires using a black box. Marker test results can be distinguished well, markers can be detected well at a distance of 30-90 cm with an angle of 45ᴼ-90ᴼ, then questionnaires to 10 elementary school students related to this application 100% like the solar system AR application as a learning medium.
Analisis Sentimen Terhadap Layanan Indihome Berdasarkan Twitter Dengan Metode Klasifikasi Support Vector Machine (SVM) Rian Tineges; Agung Triayudi; Ira Diana Sholihati
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 3 (2020): Juli 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i3.2181

Abstract

In the year 2018, 18.9% of the population in Indonesia mentioned that the main reason for their use of the Internet is social media. One of the social media with an active user of 6.43 million users is Twitter. Based on the surge of information published via Twitter, it is possible that such information may contain the user's opinions on an object, such objects may be events around the community such as a product or service. This makes the company use Twitter as a medium to disseminate information. An example is an Internet Service Provider (ISP) such as Indihome. Through Twitter, users can discuss each other's complaints or satisfaction with Indihome's services. It takes a method of sentiment analysis to understand whether the textual data includes negative opinions or positive opinions. Thus, the authors use the Support Vector Machine (SVM) method in sentiment analysis on the opinions of the Indihome service user on Twitter, with the aim of obtaining a sentiment classification model using SVM, and to know how much accuracy the SVM method generates, which is applied to sentiment analysis, and to see how satisfied the Indihome service users are based on Twitter. After testing with SVM method The result is accuracy 87%, precision 86%, recall 95%, error rate 13%, and F1-score 90%
Kombinasi Metode Certainty Factor dan Forward Chaining untuk Identifikasi Jenis Kulit Wajah Berbasis Android Syavira Cahyaningsih; Agung Triayudi; Ira Diana Sholihati
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2591

Abstract

Using skincare and facial skin care must be in accordance with the type of facial skin, because if it is not suitable, it can cause problems such as facial skin breakouts, dry skin, irritated skin, and acne prone skin. To find out the type of facial skin, you have to do an examination with a skin and genital specialist, but the high cost of consultation and the long queue process is an obstacle for everyone. Therefore, the authors created an expert system to identify facial skin types using a combination of certainty factor methods with forward chaining techniques. The diagnostic results from calculations using an expert system application and the results of manual calculations from one of the respondent data from 100 respondent data, namely producing the same level of confidence, each of which produces a percentage of 99.45% and the diagnostic results state that the user has a normal skin type.
Co-Authors Aceng Supriyadi Achmad Syirod Aditya Pratama Agung Triayudi Ahmad Avivanto Andriansyah Utomo Anhar Hawari Bagus Widiyanto Cintya Damayanti Della Diniyati Dewi Janetta Az Zahra Dimas Fathulyaqin Dwi Yulian Rizki Saputra Fadhil Muhammad Supriyanto Fauziah Fauziah Ibnu Nur Khawarizmi irfan muttaqim Iskandar Fitri Ismi Naili Qurrotul Aini Lili Dwi Yulianto Melati Indah Petiwi Mochammad Januar Finandi Moh Dani Ariawan Mohammad Iwan Wahyuddin Muhamad Iqbal Wasta Purnama Muhammad Andhika Maulana Muhammad Jordy Muhammad Rizki Zidan Nur Hayati Pramesti Sifa Aisya Nuha Rafi Syahputra Ratih Mardianti Resa Wahyu Adi Pujianto Rian Tineges Rima Tamara Aldisa Rio Al Dzahabi Yunas Riska Setiawati Rizki Pebrian Septi Andryana Seza Rifsahadi Anugrah Sita Widad Muqsithoh Syavira Cahyaningsih Tasya Khaerani Janubiya Tika Aenun Nadila Ucuk Darusalam Ucup Maulana Vivimaryati Vivimaryati Yana Tania Haryanto Yudhi Setiawan