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Gamification Design of Computer Network Virtual Laboratory Using SAGD-VL Framework Sany, Diny Syarifah
MULTINETICS Vol. 9 No. 1 (2023): MULTINETICS Mei (2023)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v9i1.5165

Abstract

Building gamification in a virtual laboratory of the computer network will help students to be able to do practicums anywhere and be able to meet the needs of practicum tools and materials. However, researchers have not found a gamification design in a virtual laboratory of the computer network laboratory that can assist developers in building virtual laboratory gamification. Based on these problems, the researcher proposes a gamification design for a virtual laboratory of the computer network using components from the SAGD-VL framework. The SAGD-VL framework is a framework for building games in virtual laboratories. This study does not take all the elements of SAGD-VL but adjusts the results of the analysis from data collection. Technology analysis aims to produce fast and true-to-life virtual laboratory gamification technology designs. This study implements the proposed design in a virtual computer network laboratory to test the proposed design. This study tested the black box, pre-test, and post-test. This test resulted in an average increase in student scores of 32.353 with the highest increase of 60. So that the proposed design of a computer network virtual laboratory gamification using SAGD-VL can help improve students' understanding of practical learning. The questionnaire results in this application being fast in computation and the UI/UX of this application is like the original.
PERANCANGAN MEMORY MECHANIC PADA GAMIFIKASI SEBAGAI MEDIA PROMOSI PADA COMPANY PROFILE APP (STUDI KASUS : PT TROPHY PLAYER MANAGEMENT) Sany, Diny Syarifah; Zikri, Fauzan; Syarif, Ahmad Fakhri
Jurnal Administrasi Bisnis (JUBIS) Vol 2, No 2 (2022): December
Publisher : Program Studi Administrasi Bisnis Internasional, FASTER, UNSUR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/jubis.v2i2.2811

Abstract

Pembaharuan metode promosi didalam bisnis merupakan hal yang sangat penting di era ini. Promosi konvensional berubah menjadi promosi daring salahsatunya dengan menggunakan aplikasi. Gamifikasi kini juga digunakan di berbagai jenis aplikasi, salah satunya adalah promosi. Gamifikasi mengadaptasi mekanik game untuk diterapkan di non-game. Memory merupakan mekanik game yang kegiatan utamanya adalah berhubungan dengan daya inngat pemain. Trophy Player Management merupakan sebuah agensi pemain bola keturunan Indonesia baik yang tinggal di luar negeri ataupun didalam negeri. Promosi pemain bola sangat diperlukan untuk mengenalkan dan menaikkan rate dari pemain bola itu sendiri sehingga klub bola akan tertarik untuk mengontrak pemain tersebut. Pada penelitian ini diusulkan sebuah rancangan gamifikasi menggunakan mekanik memory sebagai media promosi pemain bola di Trophy Player Management. Setelah melakukan pengujian, penggunaan mekanik memory ini memberikan dampak positif terhadap kegiatan promosi di Trophy Player Management.
Dynamic Difficulty Adjustment Using Reinforcement Learning for Adaptive Gameplay Experience in Resik Diny Syarifah Sany; M Malwan Angkasa
Media Jurnal Informatika Vol 17 No 2 (2025): Media Jurnal Informatika
Publisher : Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.6106

Abstract

The development of educational games holds significant potential for interactively instilling environmental conservation concepts, such as reduce, reuse, and recycle (3R). However, varying player skill levels often lead to boredom when a game is too easy, or frustration when it is too difficult. Although Reinforcement Learning (RL)-based Dynamic Difficulty Adjustment (DDA) has proven effective in balancing difficulty levels in action or MOBA genres, its application in educational waste management games remains underexplored. This study aims to develop an educational game titled "Resik" and implement a DDA mechanism using the Proximal Policy Optimization (PPO) RL algorithm, enabling the game's difficulty to adjust to player proficiency adaptively and in real-time. This research employs a Research and Development (R&D) and experimental approach. The adaptation parameters include the waste spawn rate, mission timer, sorting error rate, and NPC speed. The RL model was developed and integrated into the Unity Engine for the Android platform. Evaluation was conducted through bot simulations (15 iterations) and field trials involving 50 students from SMKS Bina Bangsa Pertiwi. The integration of the PPO RL algorithm into the game engine was successfully implemented, allowing the game to respond to player performance and dynamically adjust the difficulty. The application of RL-based DDA proved effective in maintaining the gameplay experience within the adolescent players' flow zone. These findings contribute to the development of adaptive educational games while simultaneously supporting the improvement of waste management literacy.
ANALISIS PERILAKU CART ABANDONMENT PADA TOKO ONLINE CREATROKA MENGGUNAKAN ALGORITMA RANDOM FOREST UNTUK OPTIMASI PEMASARAN LAYANAN Fauzan Zikri; Diny Syarifah Sany
Jurnal Administrasi Bisnis (JUBIS) Vol. 6 No. 1 (2026): June
Publisher : Universitas Suryakancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/jubis.v6i1.6301

Abstract

Persaingan industri e-commerce menuntut pelaku usaha, khususnya pada sektor literasi dan edukasi anak, untuk mengoptimalkan tingkat konversi penjualan di tengah tingginya angka cart abandonment. Penelitian ini bertujuan untuk memprediksi perilaku pembatalan pesanan dan mengidentifikasi faktor dominan yang memengaruhinya pada toko online Creatroka. Penelitian ini menggunakan pendekatan kuantitatif dengan metode penambangan data (data mining) terhadap 10.429 data transaksi selama periode Februari hingga April. Teknik analisis data dilakukan melalui pra-pemrosesan berbasis bahasa pemrograman Python dan pemodelan klasifikasi menggunakan algoritma Random Forest. Hasil penelitian menunjukkan bahwa model Random Forest memiliki kinerja prediktif yang andal dengan tingkat akurasi mencapai 76,16% dan presisi sebesar 80,47%. Analisis ekstraksi fitur (Feature Importance) mengungkapkan bahwa "Harga Produk" (36,63%) merupakan variabel pemicu utama pembatalan, diikuti oleh durasi interaksi visual atau "Jumlah Halaman Dilihat" (21,82%) dan sumber kunjungan dari "Fitur Video/Afiliasi" (15,74%). Temuan ini mengimplikasikan perlunya strategi pemasaran layanan (service marketing) yang proaktif, seperti penerapan sistem Customer Relationship Management (CRM) waktu-nyata untuk melakukan intervensi diskon bagi segmen pelanggan yang terdeteksi berada di jalur pembatalan, serta optimalisasi konten visual pada halaman produk untuk menekan rasio cart abandonment secara sistematis.
Penerapan Game Edukasi Berbasis Machine Learning untuk Meningkatkan Kesadaran Pengelolaan Sampah di SMKS Bina Bangsa Pertiwi Cianjur Diny Syarifah Sany; Fauzan Zikri; Bramantyo Eko Putro; M Malwan Angkasa; Raka Moch. Ramlan Assyidiq
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 6 No. 1 (2026): Januari 2026 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v6i1.906

Abstract

Permasalahan pengelolaan sampah masih menjadi isu penting di kalangan siswa sekolah menengah, khususnya di SMKS Bina Bangsa Pertiwi Babakancaringin, Cianjur. Rendahnya kesadaran siswa dalam memilah sampah organik dan anorganik mendorong perlunya pendekatan edukasi yang lebih adaptif. Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan pemahaman siswa melalui penerapan game edukasi ReSIk, yaitu aplikasi berbasis Android yang dilengkapi dengan teknologi machine learning. Metode pelaksanaan meliputi sosialisasi, pelatihan, penggunaan game, serta evaluasi melalui pre-test dan post-test. Sebanyak 50 siswa dilibatkan dalam pengukuran hasil belajar. Data menunjukkan adanya peningkatan rata-rata skor pemahaman dari 53,2  pada pre-test menjadi 76,0 pada post-test, atau terjadi kenaikan sebesar 22,8%. Selain itu, 87% siswa menyatakan game membantu mereka memahami pentingnya prinsip 3R (Reduce, Reuse, Recycle). Temuan ini memperlihatkan bahwa integrasi teknologi digital adaptif dalam pembelajaran dapat menjadi solusi efektif untuk meningkatkan literasi lingkungan siswa.
Implementation of a Finite State Machine for Controlling NPC Customer Behavior in the 2D Game "Cooking Chaos" Syakira Tasya; Diny Syarifah Sany
Journal of Multiscale Materials Informatics Vol. 3 No. 2 (2026): October (In Progress)
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jimat.v3i2.17570

Abstract

Non-Player Characters (NPC) are components in games that can be used to create interactions and gameplay dynamics. NPC behavior control is required to enable characters to respond appropriately to conditions occurring during gameplay. This study aims to implement a Finite State Machine (FSM) to control customer NPC behavior in the Unity-based 2D game Cooking Chaos. The implemented FSM consists of four states: Waiting, Angry, Chasing, and Attack. State transitions are influenced by the customer’s patience system and interaction conditions with the player. When the patience time expires, the customer changes behavior from waiting to becoming angry, chasing, and potentially attacking the player. The implementation was evaluated using Black Box Testing, FSM Transition Testing, and Multi-Customer Testing. The Black Box Testing results showed that all 12 functional scenarios were valid. FSM Transition Testing on seven scenarios, each tested 10 times, resulted in 70 successful trials out of 70. Multi-Customer Testing demonstrated that the order, patience, and FSM mechanisms operated independently with up to three active customers simultaneously. The results indicate that the implemented FSM consistently controls customer NPC behavior transitions under the defined test scenarios and integrates the service mechanism with direct gameplay consequences for the player.