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All Journal Jurnal Teknologi Informatika dan Komputer Bulletin of Information Technology (BIT)
Arjun, Jennifer
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Computer Science & IT Electrical & Electronics Engineering

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Analisis IT Service Management Layanan GrabFood Menggunakan Framework ITIL V3 Pada PT Grab Teknologi Indonesia Arjun, Jennifer; Sutabri, Tata
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.997

Abstract

Teknologi informasi yang sangat berkembang terutama pada sektor perdagangan dalam bidang kuliner. Penggunaan teknologi dalam bidang kuliner membuat layanan GrabFood menjadi popular dikarenakan cepat, mudah dan praktis. Layanan GrabFood memberikan layanan dimana pengguna dapat memesan makanan dari restoran yang bekerjsama dengan GrabFood, serta terdapat promo yang menarik bagi para pengguna. Layanan ini memungkinkan untuk pengguna dapat memesan makanan apapun walaupun jauh dari pengguna. Layanan ini juga menguntungkan bagi pemilik bisnis pada bidang kuliner karena dapat menambahkan pemasukan serta memperluas jangkauan pembeli dengan menggunakan GrabFood maka bisnis menjadi lebih cepat dan mudah. Penelitian ini menggunakan pengumpulan data melalui kuesioner dan mendapatkan 56 responden. Lalu akan dilakukan perhitungan maturity level atau tingkat kematangan untuk menganalisis apakah layanan GrabFood sudah cukup baik dalam melakukan service operation di masyarakat. Pada penelitian ini peneliti menggunakan framework ITIL V3 untuk menganalisis layanan GrabFood terutama pada Service Operation, yang terdiri dari 5 subdomain yang mendapatkan nilai maturity level sebesar 4.03 untuk subdomain Event Management, nilai maturity level sebesar 3.94 untuk subdomain Incident Management, nilai maturity level sebesar 4.01 untuk subdomain Problem Management, lalu nilai maturity level sebesar 4.02 untuk subdomain Request Fulfillment dan, nilai maturity level sebesar 4.10 untuk subdomain Access Management. Maka dapat dinyatakan semua subdomain berada pada Level 4 yaitu Managed.
Analisis IT Service Management Pada Aplikasi Traveloka Menggunakan Framework ITIL V3 Arjun, Jennifer; Lestari, Fenny; Sutabri, Tata
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1035

Abstract

Information technology nowadays is developing very rapidly, especially in the tourism sector. The use of technology in the tourism sector has made Traveloka's services popular because they can be accessed easily, quickly and reliably. The Traveloka service provides a service where users can order plane tickets from various airlines that collaborate with Traveloka with different price variants. This service makes it easier for people to enjoy their holidays and find out plane ticket prices easily. This research used data collection through questionnaires and obtained 30 respondents. Then a validity and reliability test is carried out to measure the quality level of a statement, after which a maturity level calculation will be carried out to analyze whether Traveloka's services are good enough to carry out service operations in the community. This research uses the ITIL V3 framework to analyze Traveloka services, especially in the Service Operation domain, which consists of 5 subdomains, namely the maturity level in the Event Management subdomain gets a value of 4.41, the maturity level in the Incident Management subdomain gets a value of 4.22, then for the Problem subdomain Management got a maturity level of 4.17, then for the Request Fulfillment subdomain the maturity level got a value of 4.21 and finally for the Access Management subdomain it got a maturity level of 4.30. So it can be seen that based on the results of the maturity level calculation it can be stated that all subdomains are at the Managed Level.
Principal Component Analysis and Bacterial Foraging Optimization for Credit Scoring Arjun, Jennifer; Kisworo, Marsudi Wahyu; Negara, Edi Surya; Ependi, Usman
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 1 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i1.2515

Abstract

Information technology in the current era is developing very quickly. Information systems themselves are found in various aspects of life, such as health, law, education and finance. With the improvement of information systems, systems can be created as considerations for making decisions or agreements. Credit scoring is a status that is usually held by banks or other financial institutions and contains data from debtors who have applied for credit at certain banks or financial institutions. There are many attributes in determining whether someone will get good credit or bad credit status. Therefore, a fast and accurate classification method is needed. This research proposes the use of Principal Component Analysis to reduce several attributes without reducing the attributes that are important or crucial in determining. This research also uses the Bacterial Foraging Optimization algorithm to optimize qualification results on the Support Vector Machine which uses 4 kernels, namely Linear, RBF, Polynomial and Sigmoid. The research results show that the Linear kernel accuracy which only uses Principal Component Analysis gets a value of 79%. Then optimized with Bacterial Foraging Optimization to get an accuracy of 81%. So the Bacterial Foraging Optimization algorithm increases accuracy by 2%. For RBF and Poly kernels, the accuracy is the same, namely 78%. For the Sigmoid kernel, it got the best results in Principal Component Analysis, namely getting an accuracy value of 80%.
Co-Authors Edi Surya Negara Kisworo, Marsudi Wahyu Lestari, Fenny Tata Sutabri Usman Ependi